If there’s one thing Mac users are blessed with, it’s a variety of great email apps. In fact, depending on the day, I’ll often flit between the Gmail web app, Mimestream, Spark, and Outlook for work.

As we covered last year, Notion’s AI-adjacent Notion Mail tried to do some cool things. Sadly, it seemingly didn’t find an audience, with its developer deprecating the app soon because it believes more people use agentic AI to manage their inbox without opening the app.

And honestly? I was a little bummed. Notion Mail had a unique UI that felt right at home next to the company’s main app and Notion Calendar. And, while browsing my inbox, I spotted an email from the team at Slashy that might just fill the gap.

Slashy doesn’t want you to open your inbox

A quick glance at Slashy will show that it’s definitely cut from a similar cloth to Notion Mail. For one, its clean design makes it a looker — it’s easy to navigate, with options for highlighting important emails or everything.

What makes it unique is that Slashy will attempt to learn from a user’s emails and reply frequency to highlight what’s important, and use their voice to make responses feel more natural.

If that sounds dystopian, then yes, you’re not alone. I had the same thought, and we’ll touch on how successful it is in that regard in a moment. But, as someone swamped with press releases daily (not a complaint, keep ‘em coming!) I was impressed by how well Slashy categorises and labels my emails.

In many ways, it feels akin to Notion Mail’s labels, but Slashy wants you to handle your email from a distance, if at all. It automatically runs scheduling workflows to help identify meeting times, and can lean into Model Context Protocol (MCP) to tie in nicely with Claude, something I’m yet to fully get to grips with.

All of this is to say it’s an email app that looks great, and yet it wants you to leave its processes to handle your inbox - and it does so remarkably well.

With zero setup, it pulled through a bunch of handy contact info, complete with contextual history, for more than 20 people I’d emailed in recent weeks. It also highlighted my scheduling, including the days I work in a London office and when I’m home, and when my upcoming vacation is.

Put simply, it knows me better than I know myself.

“Your voice, not GPT slop”

I recently waxed lyrical about Cotypist, a Mac app that makes writing in certain situations simpler by using predictive text. I was impressed at the time by how much it’s attuned itself to my voice, to the point where, once again, it predicts my sentences (or maybe I’m very predictable).

I still use Cotypist across other apps, but when opening an email to reply, I genuinely thought I’d drafted something already in Slashy.

The use of humour, the tone, the friendly nature (if I do say so myself), it was all, well, me. Aside from the existential dread of being a writer who relies on personable copy to stand out from the AI content-absorbing machine, and who has now seemingly had my card numbered, I couldn’t quite believe it.

Every email I tried to reply to, Slashy had basically laid out exactly what I was going to say, albeit with a prompt to change it if I wanted to, like turning a positive response to a negative one, or amending the tone to be more professional.

There’s even a handy sidebar that allows you a sandbox to draft a reply, find specific emails related to the current thread, or just summarize the whole thing using Claude.

Add to that integrations with Notion so it can read and write to Notion databases, Slack, and even iMessage (albeit the last one isn’t working for me in macOS Golden Gate beta), and it can do a really great job at ensuring you barely ever need to look at your emails.

If you’re interested in Slashy, it’s available now for Gmail accounts, with Outlook coming soon. It’ll cost you $30 per month or $300 per year for unlimited inboxes and AI usage.

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• I use Gemini Spark daily — here are 7 prompts that show what it can really do

My AI stack of tools is composed of Claude, ChatGPT and Gemini. So when I heard that Google was expanding access to Gemini Spark, I couldn't wait to see what the "always on" AI agent could do.

For those new to Gemini Spark, it's an AI agent that can monitor your inbox, organize files, build documents, schedule calendar events and complete multi-step tasks across Google's apps. Best of all, you don't have to have your laptop open. Google recently began rolling the feature out more broadly, including to subscribers in India, after initially launching it for U.S. Google AI Ultra users.

Naturally, I wanted to see whether this actually feels different from using ChatGPT or the regular Gemini chatbot. Turns out, it's completely different in the best ways.

7 prompts worth trying first

1. Plan my week

Prompt: Review my calendar, unread emails and task list. Identify any scheduling conflicts, prioritize my work, and create a realistic plan for the next five days.

After using this prompt I checked to see if it actually understood priorities (meetings vs. social events) or did it just rearrange my calendar. To my suprise, it not only gave me a quick look at all my meetings, but also showed me the emails I needed to respond to. Talk about a productivity game changer!

2. Inbox zero

Prompt: Go through my inbox from the past seven days. Archive anything that isn't actionable, highlight emails requiring a response and draft replies where appropriate.

While the first prompt tackled the urgent emails, this one takes on the rest. Using this prompt lets the AI know what you want to do with unread emails or emails that you have read, just haven't done anything with yet. Basically, it's the fastest way to find out if you missed anything important.

When I tried this, I realized I had missed a note from my son's school reminding me to send over updated vaccination forms before the start of the school year.

3. Prepare me for tomorrow

Prompt: Every evening at 7 p.m., summarize what I accomplished today, tell me what's on my calendar tomorrow, list the emails I should read first and remind me of anything I haven't finished.

I use various versions of this prompt. It helps to prioritize for the next day while also reflecting on the work I've done. Other versions include gathering news updates I may have missed or finding tech blogs that may interest me. Either way, Gemini Spark is great when it comes to rounding up information you need.

4. Vacation planner

Prompt: Plan a three-day family trip within three hours of my home. Compare hotels, estimate costs, build an itinerary and put everything into a Google Doc.

I've used AI to plan for vacations and weekend getaways before, but with Gemini Spark, things felt different. The finalized Google Doc meant that I could easily share notes with my husband and save in a folder for future planning. Beyond vacation planning, this prompt works any time you want to use AI for multi-step reasoning.

5. Research assistant

Prompt: Research the latest developments in AI agents. Read multiple sources, identify the biggest trends, summarize the findings in a Google Doc and include links to the original reporting.

As a journalist in the tech industry, I'm constantly seeing news about new AI models, features and gadgets. Keeping everything organized used to be a headache, but thanks to Gemini Spark, all of my notes and interests are tackled together in a Google Doc. I can see the links and bullet point summaries, which help me determine what news to report on first.

6. Budget helper

Prompt: Review my recent receipts and purchases. Group them into spending categories, identify unusual expenses and suggest three realistic ways I could save money next month.

As someone who frequently shops on Amazon, keeping my orders organized was a bit of a challenge. This helps me stay within my budget and keep track of spending, which is sometimes hard to do with three kids who are always asking for the latest squishy toy!

7. My favorite

Prompt: Every morning, prepare a briefing for me with today's calendar, unread emails, breaking AI news, weather and a prioritized to-do list.

This use case makes me feel like I genuinely have a personal assistant. It's the kind of "personal chief of staff" workflow I haven't seen with other AI models.

Bottom line

After spending time with Spark, my eyes were opened to new possibilities. For those who haven't strayed from using AI as a chatbot, I urge you to try any or all of these prompts. The real surprise is that you don't have to babysit the AI. It can gather the information it needs without you there.

Spark changes that dynamic completely. At first, I wondered if I could trust it. After all, giving an AI background access to your inbox and calendar sounds incredibly useful —and slightly terrifying.

Google appears to recognize that concern. Spark is designed to work strictly under your direction and is built to check with you before taking major actions, rather than quietly sending emails or finalizing purchases on its own.

Whether people are comfortable giving AI that much responsibility is another question entirely. But after trying Spark, I finally understand why every major AI company is racing to build agents.

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In case you hadn’t noticed, AI is having a bit of a backlash moment. More and more people are opposed to data center construction where they live, for example, and a lot of consumers (especially Gen Z) are questioning the need for generative AI overall.

Samsung seems to be tuned in to this sentiment with the launch of the Galaxy Z Fold 8 and Galaxy Z Fold 8 Ultra. Instead of hitting people over the head with ‘Galaxy AI,’ the company is focusing on a handful of features that it believes have real-world benefits.

“We don’t want to overwhelm the consumer with AI,” Samsung EVP Jay Kim told me. “A lot of industry focus on AI is sort of as itself as a technology, but I think it’s shifting from technology to benefits. We’re looking at how you make this meaningful, how do you make this more easy to access?”

Subtler AI

One example is Now Nudge. Say you get an incoming text that references an upcoming appointment with the date. The Z Fold 8 and Z Fold 8 Ultra are smart enough to present a little Calendar button. When you tap that, the Calendar app will automatically open in Split View on the right side of the display.

“You're looking at the screen, and then it understands where you're looking at, and then it actually provides the next action, it suggests your action,” Kim said. “Before you have to go through extra steps to make that work, but now it's instant. We’re just trying to help consumers get things done in a more easy way.”

Another example of AI that’s less in your face is My FanCam. When editing a video on the Galaxy Z Fold 8 and Fold 8 Ultra, you can select a subject and the phone will recut the video so that it “follows” only that person. You can even choose your preferred aspect ratio. And it works seamlessly based on my testing.

To access this feature you have to select the AI icon first. One might argue it’s too subtle and not easily discoverable enough.

“We’re looking at consumers and we're looking at how they behave and how they use a device,” said Kim. “We just want to make sure that they get what they need at the right time, without sort of thinking too much about whether it's coming from AI.”

Automating the everyday

The Galaxy Z Fold 8 series is even letting AI do stuff for you in the background with Gemini Intelligence task automation, which now supports 40 apps. This includes shopping, restaurant reservations, travel booking and event tickets.

For example, you can tell your Fold 8 to help book you a vacation and give it some parameters, and it will start working with Expedia to make it happen. You can jump in at any time, and Gemini Intelligence won’t make any purchases without your approval.

“When we put automation in place it has to work right,” Kim said. “The consumer needs to understand how it works. So we’re taking it one step at a time and we’re not rushing, because the experience is more important.”

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There have been plenty of times when a new dilemma enters my life and my brain space gets cluttered by all the solutions I could apply to it.

It can be something as simple as deciding what recipes I should add to my weekly rotation or more complex issues, such as deciding the best questions to present to a high-profile interviewee. Every week, I sit in complete silence and contemplate the best routes to take in response to my latest conundrum — thankfully, the best solutions arise once I spend a few hours talking about my problems with friends and family.

The humans in my life provide plenty of serviceable advice. And after I have a chat with them, I boot up ChatGPT to see the sort of solutions the AI can also provide me with.

Over time, I've learned to use the seven prompts below to transform ChatGPT into my personal strategist. Appointing it a specific role, giving it a decision framework to work with and making sure it challenges my way of thinking works more often than not.

Getting dependable advice with the “Leverage Maximizer” prompt

After asking ChatGPT to generate a collection of prompts that help it roleplay as a strategist, the one I immediately put into action is this one:

Every time I ask for help, identify the 20% of actions that will create 80% of the results. Tell me what to ignore, eliminate, automate, delegate, or postpone, so I focus only on high-leverage work.

When I needed help with finding the best moving company in New York City, I attached this problem to that prompt and got a wealth of serviceable guidance. ChatGPT told me it’s not worth spending hours reading hundreds of reviews — instead, get three quotes from reputable movers and compare them to reach a final decision.

It also advised me to create a spreadsheet that compares each moving company’s quote (the cost estimate provided by a mover), reviews of their services, their COI (Certificate of Insurance) and my final decision on choosing them or not.

Two of the best NYC moving companies ChatGPT brought to my attention are Roadway Moving and Dumbo Moving & Storage. After giving me the proper question to present to each moving company I’m considering (“I’m moving within NYC. Can you provide an all-in estimate including travel time, stairs/elevator fees, packing materials, insurance, and any additional charges?”), ChatGPT’s all-encompassing strategy came into focus even more.

6 additional prompts that turn ChatGPT into the ultimate adviser

These are the six other prompts ChatGPT equipped me with after my request for the most efficient ones to use to turn it into a personal strategist:

• The Executive Strategist: Act as my personal strategist. Your job isn't to answer my questions — it's to help me make better decisions. Challenge my assumptions, point out blind spots, identify second- and third-order consequences, and recommend the highest-leverage next action. Think like a CEO advising another CEO.
• The Weekly Strategy Session: Every time I bring you a problem, treat it like our weekly strategy meeting. Before giving advice, identify the real problem beneath the obvious one, explain what matters most, what doesn't matter, and what I should prioritize over the next 30 days.
• The Opportunity Scanner: Whenever I share an idea, don't just evaluate it. Identify hidden opportunities, potential partnerships, overlooked markets, risks, and unconventional ways to make the idea 10x more valuable. Think like a venture capitalist and business strategist combined.
• The Second-Order Thinking Coach: Never stop at the first answer. For every recommendation, explain the immediate outcome, second-order effects, long-term consequences, biggest hidden risk, and best alternative if my idea fails.
• The Blind Spot Detector: Your primary responsibility is finding what I'm missing. Every time I present a plan, tell me what assumptions I’m making, what could break, what someone smarter than me would notice, and the uncomfortable truth I probably need to hear.
• The Personal Board of Directors: Act as my personal board of directors. Combine the thinking styles of an entrepreneur, psychologist, strategist, economist, and executive coach. When I ask for advice, evaluate it from all five perspectives before making a recommendation.

Bottom line

With these seven prompts, I now have a system to work with whenever I want ChatGPT to present the best strategies to apply to my latest problem. When the time comes for me to inquire about all the simple and complex problems that come my way, I’ll be sure to use a combination of my friends, family and ChatGPT’s input to find the best way forward.

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For years, ChatGPT was my default AI tool. But after spending serious time with Claude Opus 5, I've quietly switched over for most of my everyday tasks. And when it comes to these 5 prompts, I don't think I'm going back.

Claude consistently gives me responses that feel more thoughtful, more structured, and less AI-sounding. With Claude, I find myself needing fewer follow-ups because it just "gets it."

Here are five prompts I now take to Claude instead of ChatGPT, and why the results have been noticeably better.

1. Brainstorming creative ideas

Prompt: "I need help brainstorming ideas for [a topic, product, or project]. Can you provide 10 unique ideas or approaches, and briefly explain each?"

Any chatbot can generate a list. The difference is whether that list actually makes you think. What I like about Claude is that it seems to be less robotic and generic. In fact, prompt after prompt, it gives me angles I genuinely hadn't considered, with concise reasoning behind each one. Claude doesn't repeat itself as often as ChatGPT or have filler and fluff like ChatGPT.

Where ChatGPT tends to give you ten variations of the same safe answer, Claude pushes into less obvious territory. If you've ever stared at a brainstorming list and thought "these are all basically the same thing," you'll notice the difference immediately.

2. Learning complex topics

Prompt: "Explain [topic] to me as if I were [a beginner, a college student, or an expert]. Provide examples or analogies to help me understand better."

This is where Claude really pulls ahead. Because the chatbot has a knack for matching its tone and depth to whatever level you ask for, without being condescending at the beginner end or vague at the expert end.

I've also noticed that Claude is more willing to say when something is genuinely complicated or flat out wrong, rather than smoothing everything into a confident-sounding paragraph. When you're trying to learn, that honesty matters.

3. Optimizing productivity

Prompt: "Help me optimize my workflow for [a specific task or project]. Suggest tools, strategies, or step-by-step routines that can save time or improve quality."

I use this prompt to ask Claude for just about anything, including how to get three young kids out the door by 8am every morning. Instead of a vague pep talk about "batching tasks" and "setting intentions," Claude gave me a staged, practical plan — broken into time blocks, with a backup plan for when things inevitably go sideways.

What I appreciate is that Claude treats workflow questions like real problems with real constraints, not opportunities to list every productivity app on the market. The suggestions feel like they came from someone who actually thought about my situation, not someone who Googled "morning routine tips." I find this especially interesting because Claude's memory is not as good as ChatGPT. In other words, ChatGPT seems to "know me" better than Claude, but Claude still offers more human suggestions.

Workflows is also a great time to use Claude Skills and Connectors.

4. Writing or editing assistance

Prompt: "I need help writing [type of content, e.g., a blog post, a persuasive email, or a professional bio]. Here's the topic/goal: [describe it]. Can you create an outline for me?"

Letting AI write for you is a big no-no in my book. But "writing with AI" could mean a lot of other things. For example, if you're staring at a blank page with several ideas and don't know where to start, prompting Claude with your messy notes and asking it to make an outline or at least turn your notes into bullet points, can help ease frustration and writer's block.

For those who may need extra support, Claude can handle longer writing tasks without losing the thread. Blog posts, emails, personal statements or similar can be done without filler. If you've ever had to spend 20 minutes editing AI-generated fluff out of a draft, Claude will save you that time.

5. Getting personalized recommendations

Prompt: "Based on my [situation, preferences, or needs], can you recommend [books, movies, strategies, tools, etc.] and explain why they might be a good fit?"

This is surprising, especially, as I mentioned, ChatGPT knows me so well. However, this one has become my go-to prompt when I want to unwind. I asked Claude to recommend shows to stream over the weekend because I wanted something relaxing and funny. The list it gave me was genuinely curated, and not a mix of the most popular streaming shows at the moment. Even more surprising, the AI explained why each pick fit what I was looking for, and included a mix of obvious favorites and things I hadn't heard of.

Claude's recommendations don't feel like search results. They seem like they are coming from someone who actually listened to what you said. It picks up on the nuance in your request instead of just matching keywords.

Final thoughts

I'm not saying ChatGPT is useless, far from it! I use it regularly. But when it comes to the types of prompts where more "human-like" effort is needed, Claude wins.The key with any AI is being specific about what you need. But with Claude, I've found that specificity gets rewarded more consistently. Give these prompts a try, and I think you'll see what I mean.

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This week, Apple revealed its new Apple Upgrade Program that lets you lease several of the company's devices, including iPhones, Macs, Apple Watches and iPads.

With fixed 12-, 24 or 36-month terms, you're locked into paying a monthly rate for your chosen device until the term is up or you decide to upgrade. Abandoning the lease early is possible, but there are a number of penalties and fees associated with doing so.

Is the Apple Upgrade Program a good deal versus buying the phone outright or getting it from a carrier? I crunched the numbers, but also turned to ChatGPT to find out if it's a ripoff or worth your dollar.

iPhones and Apple Watches

Here's how much an iPhone or Apple Watch will cost you over a 24-month term. If you want to keep the device at the end of the lease, you'll need to pay the remainder.

Macs and iPads

And here's how it looks for Macs and iPads, which are eligible for a 36-month lease. This table specifically looks at a 24-month lease.

The fine print

There are two big caveats to Apple's leasing program. The first is that, according to the terms of service, if you miss three consecutive payments, Klarna (the company managing the lease) will terminate the contract, and the customer will owe the remaining balance.

The second is that AppleCare+ is not included with the lease. You could roll the dice and not subscribe to AppleCare+ but you are liable for any damage, per the fine print.

"Insurance is not included in your lease, and you may incur damage fees if the device is lost, stolen, or not returned in the condition required by the lease."

AppleCare+ ranges in cost from $2.99 (Watches) up to $9.99 (iPhone) per month depending on your device. There are annual payment options as well.

Here's the iPhone and Watches table again with how much a 24-month lease would set you back with AppleCare+.

As you can see, over two years, the price goes up by a few hundred dollars and in some cases exceeds the initial price of the iPhone or Apple Watch.

Yes, that would be the case if you weren't leasing an iPhone. AppleCare+ is a protection plan that you subscribe to a monthly or annual basis.

However, as mentioned, it may be more necessary for a leased device than one you own because of those potential damage fees. You could also be hit with upgrade fees or substantial termination fees if you try to end the lease early.

What about trade-ins?

Another factor against Apple's lease program is that, because you don't own your device, you won't get any credits for trading in your older device, which could lower your monthly payments to something lower than you would get from the Apple Upgrade program.

Let's take the iPhone 17 Pro as an example.

If you're upgrading from an iPhone 16 Pro, you could get as much as $560 in trade-in value, which would lower the cost to $22.45/month for 24 months.

If you were upgrading from an iPhone 15 Pro, you could get as much as $410 in trade-in value, which would lower your monthly bill to $28.70.

While you can trade in your current phone and get credit in the Apple Upgrade Program, it's a one-time thing, as you wouldn't own your phone from then on.

What ChatGPT had to say

According to ChatGPT, the Apple Upgrade Program is not a rip-off, but it may not be the cheapest way for you to obtain an Apple device.

"For most people it's more expensive than buying and later selling or trading in the device. The biggest winner is Apple, because leasing encourages customers to stay on a continuous upgrade cycle," the AI said.

For those who keep their devices for three or more years not be a good deal, especially since Apple devices tend to retain their resale or trade-in value. Plus, the leasing program means that you don't own the device.

Interestingly, I actually prompted ChatGPT as well as Gemini and Claude and none of them mentioned AppleCare+ beyond noting that it is no longer bundled with the Apple Upgrade Program the way it was with the iPhone Upgrade plan.

Unless you upgrade annually or money isn't an issue for you, Apple Upgrade Program may not be the right fit for you. I'm a major proponent of owning your devices and this program doesn't let you do that until the end of the terms.

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AI is rapidly becoming the new storefront. Instead of scrolling through pages of search results, more shoppers are asking AI assistants to recommend products, compare prices and narrow down options. But a new report argues that those same AI systems may also be quietly shaping what consumers never see.

Researchers at Columbia Law School's Center for Law and the Economy have published a report accusing Amazon and Walmart of using their AI shopping assistants in ways that make American-made products harder to find, despite the systems appearing capable of identifying them.

The report, Made in America, Hidden by AI, examined how Amazon's and Walmart's AI shopping tools responded to questions about products made in the United States. According to the researchers, Amazon's chatbot often declined to answer straightforward questions about American-made products while readily answering equivalent questions about products manufactured in China. After rephrasing the same request, however, the chatbot returned American-made products using information that had been available all along.

"We tested these systems the way an engineer would, and the refusals fell apart under basic testing," Erie Meyer, senior fellow at the Center for Law and the Economy and one of the report's authors, said. "The data was there, but the design was built to hide it."

AI shopping assistants are becoming gatekeepers

The report arrives as retailers increasingly push shoppers toward AI-powered recommendations instead of traditional keyword searches. Whether it's suggesting products, comparing alternatives or summarizing reviews, these assistants are becoming the first stop for many online purchases.

According to the report, neither Amazon nor Walmart currently offers shoppers a dedicated "Made in USA" filter, despite providing hundreds of other filtering options across many product categories. The researchers argue that if AI assistants become the primary interface for online shopping, the way they choose what information to surface, or withhold, could influence purchasing decisions on a massive scale.

I tried it by asking for a few common items like furniture and fishing poles, Alexa+ said it did not have access to the information. However, when I asked for American flags made in the U.S.A., it supplied a product that matched my query.

Lina Khan, director of the Center for Law and the Economy and former chair of the Federal Trade Commission, said the findings demonstrate that increasingly sophisticated AI systems are still shaped by the incentives behind them.

"Even as AI tools continue to grow in sophistication and capability, business incentives will shape how these advancements get deployed," Khan said. "Policymakers and enforcers have a vital role to play to ensure the public doesn't get the short end of the stick."

The systems appear capable of spotting suspicious claims

One of the report's more interesting findings is that both companies' AI assistants appeared able to identify potentially misleading "Made in USA" claims.

According to the researchers, Amazon's chatbot identified listings where promotional material claimed products were American-made despite evidence suggesting they were imported. Walmart's chatbot reportedly ranked "Made in USA" claims by how suspicious they appeared based on factors including seller information and manufacturing footprints.

The authors argue this demonstrates the underlying AI systems have the technical capability to help identify questionable origin claims. However, the report does not establish that Amazon or Walmart internally use these capabilities for marketplace enforcement.

Amazon responds

In a statement to Reuters, Amazon disputed the broader implication that it hides country-of-origin information from shoppers.

"Country-of-origin information, when available, is currently displayed on product detail pages, and we're continually working to improve Alexa for Shopping to make this information even more accessible for customers," an Amazon spokesperson said.

Walmart did not immediately respond to Reuters' request for comment.

Bottom line

The report highlights a question that is likely to become more important as AI shopping assistants continue to replace traditional search. If consumers rely on AI to decide what products to buy, the design choices behind those systems become far more consequential.

Decisions about which products are surfaced first, which attributes are emphasized and which questions receive complete answers could shape purchasing behavior in ways that are largely invisible to shoppers.

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July 30 is recognized globally as International Day of Friendship, a holiday meant to observe different cultures, promote peace and strengthen human solidarity.

Now I’ll admit to not being the bestest of friends — I’m constantly called out for not calling anyone first and am prone to going ghost for a few weeks at a time. But when I do answer the phone, respond to a text or make a rare appearance at a major meetup, I take the time to catch up with my closest buddies as much as possible and make an effort to create long-lasting memories that get referenced during future hangouts.

One conversation that comes up a lot when I talk to them is how hard it is to make new friends as an adult. Unless it’s someone they’ve met at work, some of them (including me) have a hard time being in the sorts of situations that help widen their social circle.

With that dilemma in mind, I asked ChatGPT for counsel on the best methods to employ if I want to make new friends. Luckily, this digital advice session gave me a practical list of tips and a workable plan that will keep me busy for the next three months.

Taking notes on how to meet new people in my late 30s

To kick this latest chatbot advice session off, I presented this prompt to ChatGPT: “Give me the seven best tips on how to make friends as an adult. For reference, I'm 38 years old and reside in New York City.”

I also made mention of the hobbies and activities that matter the most to me, such as gaming, bowling, playing pool, attending live wrestling events, stuffing my face with Korean BBQ & Jamaican cuisine and indulging in otaku culture (anime lies at the heart of that last interest of mine).

Before ChatGPT laid out its suggestions, it gave me an explanation of what it truly takes to meet new people, build those blossoming relationships and why living in a big city gives me an advantage when it comes to making new friends:

Making friends as an adult is less about charisma and more about repeated exposure, shared experiences, and taking initiative. That's actually good news, because those are things you can control. Since you're 38 and living in New York City, you have one huge advantage: there are almost endless opportunities to meet people who already share your interests. The challenge isn't finding people—it's turning acquaintances into actual friends.

One of the tips that spoke to me and my good intentions the most was to start looking for my next regular activity instead of actively looking for friends. ChatGPT pointed out that most adult friendships take shape because people repeatedly run into each other in group settings. Instead of constantly asking myself, “Where can I meet new people and make new friends?”, I should be asking myself, “Where can I see the same people every week?”

Based on my favorite pastimes, ChatGPT stated that the best group activities that can introduce me to new people who could become familiar faces worth befriending are weekly board game/video game nights, a bowling or pool league, local wrestling watch parties, fighting game tournaments, anime watch parties and food-based social groups.

Two of the other pieces of practical advice from ChatGPT that caught my attention included:

• Say "yes" more often than feels comfortable: Introverts (and busy adults) naturally decline invitations because staying home feels easier. A useful rule to remember is “If you're at least 60% interested, go.” You don't have to stay all night. Even showing up for an hour can strengthen relationships. Momentum matters more than duration.
• Focus on creating "micro-friendships": You don't need a new best friend. You need someone new to grab lunch with, someone new to game with, someone new to go to a wrestling show with, someone new to watch anime with and someone new to travel with. These smaller friendships often overlap over time until you have a genuine social circle full of new faces. Trying to find “your people” all at once can feel overwhelming; building one connection at a time is more realistic.

Coming up with a 90-day friendship plan

I followed up my first question by asking ChatGPT to supply me with a curated list of the best activities in New York City I should take part in and which places I should go to enjoy them in my quest for new friends.

Since it already had a gauge on my personality, hobbies and interests, it set up a 90-day friendship plan for me that should keep me busy and outside a whole lot more once the summer begins winding down and hoodie season makes its return:

• Month 1 - August: Pop up at the AnimeNYC convention, participate in a gaming tournament at OS NYC and go attend a House of Glory wrestling show.
• Month 2 - September: Join the Better Off Bowling league, go to a New York Food Club meetup and hook up with the Uptown NYC Board Gamers.
• Month 3 - October: Head to New York Comic Con, jump into an event organized by the Anime Social Nexus and use this month to start a recurring meetup with your new friends.

Bottom line

With my new game plan in the back of my mind and a whole new outlook on what it takes to be more social & outgoing as an adult, I left my latest digital advisement session with ChatGPT feeling a bit more confident.

I’ll be sure to keep its useful tips in mind when the time comes for me to meet like-minded people, keep up with them regularly and add them to my familiar batch of friends to see if they mesh well. Now’s the time to get out there and abide by the mantra of International Day of Friendship every day.

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Algorithms are everywhere, analyzing your habits and shaping what you read, watch and hear on every platform, from Instagram to YouTube to TikTok. And it's not just the stuff you want to see — it's also the ads and pitches and sales and stuff that just clutters everything.

I had seen an add on Instagram for HyperTexting, an app that promises to be "your timeline minus the ads, algorithms, and AI slop." I decided it was worth a try because, like a lot of people, I'd grown tired of opening social media only to find my feed dominated by sponsored posts, recommended accounts and content designed to keep me scrolling for as long as possible. I wanted to see what would happen if I stripped all of that away.

HyperTexting does exactly that

Instead of deciding what you should see, the app only shows content from the publications, newsletters, RSS feeds, blogs and creators you deliberately choose to follow. There are no ads and no "For You" page suggestions. Nothing is nudging you toward another hour of scrolling. That part was pure bliss.

But, after reading my favorite publications and posts, I did start to miss the opportunities that social media offers. In other words, when I reached the end of my timeline, I had to close the app and go on with my day. I don't have a problem with doomscrolling and actually like seeing news and creators that I don't follow. The more I type this, the more ridiculous it sounds, but reaching the end of a feed feels strangely foreign. We've become so accustomed to infinite scroll that an app with a stopping point almost feels unfinished.

So while it will certainly feel peaceful for some, it didn't do it for me. Maybe it's because as a journalist I'm so hungry for the latest news. My "FOMO" (fear of missing out) keeps my eager to accept posts from people and publications that I haven't manually added to my feed.

Notably, within a couple of days, my screen time dropped noticeably. I stopped opening the app out of habit because there was no reward waiting for me at the bottom of another refresh. The endless loop that keeps so many of us glued to our phones simply wasn't there.

I stopped discovering new things

Around day four with HyperTexting, I honestly couldn't take it anymore. I realized I hadn't discovered anything new all week.

That's not a criticism of HyperTexting. In fact, it's doing exactly what it promises. The app gives me complete control over my feed, and that's incredibly refreshing after years of algorithms making those decisions for me.

But complete control comes with an unexpected trade-off. As much as we criticize platforms like TikTok, Instagram and X, their recommendation systems occasionally get something right. Buried beneath the sponsored posts and engagement bait is the article you never would have searched for, the writer you've somehow never encountered or the niche community you didn't know existed until an algorithm placed it in front of you.

Those moments are easy to dismiss because they're surrounded by so much noise. But after a week without them, I realized they matter.

HyperTexting will undoubtedly solve a person's doomscrolling problem almost overnight, but for me, it made me realize how much I've come to rely on unexpected discovery. Left entirely to my own choices, my feed became informative, predictable and, eventually, a little static. In a lot of ways, it's like what AI has done to the web. By simply dishing out answers rather than showing a variety of links for me to click on and discover for myself, users are stuck in a vacuum.

The takeaway

Using HyperTexting made me realize the problem isn't that algorithms exist, but rather what they are optimized to do. Today's social platforms aren't designed to help us discover the best ideas on the internet. They're designed to maximize engagement, time on site and advertising revenue. Discovery is often just a byproduct of those goals.

After a week without that system, I don't think the future is an algorithm-free internet. I also don't think it's one where invisible recommendation engines decide everything we read. What I want is something in between.

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I’ve been wearing the new Garmin Cirqa, a $199 screen-free and subscription-free fitness tracker for over a week, and while my initial impressions are mostly positive, burning questions about the device persist.

So, I reached out to Jill Kaiser, the lead product manager for the Garmin Cirqa, to learn more. Kaiser has been with the Kansas-based brand for a decade, and sees the Cirqa as her ‘baby.’

One of Garmin’s more unusual wearables, our conversation touched on the value of customer feedback in the design process, how customization and comfort were also key pillars, why the Cirqa lacks an onboard GPS, and whether or not Garmin plans to roll out more screen-free wearables anytime soon.

Why launch a screen-free tracker?

One of the biggest bits of info I gleaned from my chat with Kaiser: Garmin places a high value on user feedback and requests.

“We definitely are listening to our customers. We were looking at what our customers want,” says Kaiser. The Cirqa has “all of our training, all of our health metrics, everything that they are wanting in our other devices, just in an option that doesn't have a screen, that doesn't have that distraction for them.”

Garmin users have apparently been requesting a screen-free tracker for some time. So why launch one now, especially hot on the heels of the Fitbit Air, a device that promises many of the same features for half the cost?

“We've had quite a lot of customer feedback wanting a screenless product for some time, and so it's been on our radar, and [now] just felt like we had all of the pieces in place to be able to support this,” says Kaiser.

Of course, launching a successful screen-free wearable requires an equally successful, i.e., user-friendly companion app. Put another way, “there's a lot that goes into not having a screen on your wrist and just making sure that our ecosystem is built for it,” notes Kaiser.

An ‘all-day version’ of the Index sleep tracker

Kaiser says to think of the Cirqa as an “all-day version” of Garmin’s screen-free Index sleep tracker. However, “from a feature standpoint and what it tracks, the Vivoactive line and the Venu line fit really nicely with [the Cirqa]. We brought in all of the training metrics that the latest Venu has,” says Kaiser.

This is to say, the Cirqa should be one mighty reliable and comprehensive holistic device, up there with the best fitness trackers. And unlike other popular screen-free trackers out there, the Cirqa has one design element that truly sets it apart from the pack: a physical button.

“We added a button onto the product because we know from customers that it's important to be able to have that quick start and stop without having to pull out the phone,” says Kaiser. Not only that, the Cirqa vibrates each time you press the button to confirm the action.

‘Users can really dig in and make it what they want’

Designed to appeal to a wide range of users, whether you’re a hardcore athlete or a first-time jogger, personalization is king when it comes to the Cirqa.

“There's just a lot of customization we built into this that a user can really dig in and make it what they want. If they want to see their battery life from the device, they can turn that on, and with a double tap, you can see an LED; if it's green, it means it's good to go,” says Kaiser.

That’s not all. “If you feel like you're missing [knowing] what time it is, we have hourly alerts that you can turn on, and it vibrates on the hour.”

By default, a single press of the buttons starts a generic workout tracking session; however, users can customize the action to begin any supported workout of their choosing.

“You can go into Garmin Connect and customize that button. If you're always going floor climbing, like doing stadium stairs, and you want those metrics, you can go in and change that so floor climb is the activity on your device,” notes Kaiser.

Meanwhile, a long-press of the button turns on the broadcast heart rate function, while a triple-press forces the Cirqa into pairing mode.

A valuable companion to your Garmin Watch

What about users who already own a Garmin watch? Does the Cirqa have any value as a companion device? Yes! Users can specify a primary device in the Connect app. This is the one you plan to wear throughout the day and night.

So, if you’re someone who trains with a higher-end Garmin Fenix or Forerunner, but want something a little more wrist-friendly to wear to bed without sacrificing sleep and recovery insights, the Cirqa may be your answer.

Best of all, you don’t need to manually switch between devices; the Connect app is smart enough to sync data from whatever wearable you’re wearing/logging a workout with.

How to train your Cirqa

While a dedicated, customizable button to start and stop workouts is certainly handy, wouldn’t it be nice if your Garmin Cirqa automatically knew what workouts you were doing without any input from you?

Kaiser says that with a little bit of user guidance early on, you can train your Cirqa to do exactly that. You’ll just need to manually track those activities for the first week or two you wear the device; after that, it should start to automatically detect and track your go-to workouts.

“By you engaging with it and saying, yes, I did go for a walk, or no, I didn't go for a walk, I was actually doing something else, that is helping the system then learn and actually adapt to you,” says Kaiser.

I’m still testing Cirqa's auto workout detection out, and seeing as it's only been a week, I can't yet comment on its reliability. That said, I look forward to reporting my findings in the forthcoming Garmin Cirqa review.

On the lack of onboard GPS

One question I keep hearing about the Garmin Cirqa is ‘why doesn’t it have GPS?’ According to Kaiser, a desire to keep the size and cost down, while maximizing battery life, is the answer.

“There's a lot of benefit that we can get from a battery standpoint, from a size standpoint of not having [GPS] in there. And so it went back to the user need. Yes, we know GPS is important, but from the phone, that still gets what our customers want,” says Kaiser.

More screen-free trackers to come?

So, now that Garmin has two screen-free wearables under its belt, can we expect more to come? “We're always going to continue to be looking at what we can do in this space,” says Kaiser. So, maybe yes, maybe no?

Ultimately, the Cirqa was designed to be, well, whatever you want it to be, assuming you want a screen-free tracker. “There's just a lot of customization that we built in,” says Kaiser. “Depending on what your needs are and what you're looking for. You're either not getting anything from it, where it's completely distraction-free, or it's adding a little bit of help throughout the day.”

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Last week, I asked a simple question in my Beyond the Prompt newsletter: Is this the end of "Googling it?"

I argued that we're moving away from an internet where we discover information ourselves toward one where AI simply hands us an answer. My biggest concern is the long-term visibility of the web. If fewer people click through to the original reporting, reviews and research that AI depends on, who, or rather, what is creating the knowledge.

My inbox blew up!

I expected the responses to split neatly into two camps: people who love AI search and people who hate it. Instead, your emails revealed something much more interesting.

Almost nobody turned this into an AI-versus-Google debate. Instead, many of you argued that the problems with search started long before ChatGPT, Gemini or Perplexity arrived. That gave me pause. Maybe AI isn't replacing search because it's inherently better, but rather it's succeeding because traditional search had already become frustrating enough that people were ready for something different.

For many of you, Google is the real problem

One of the strongest themes running through your emails had very little to do with AI and everything to do with search.

"AI is not killing 'Googling it.' Google's endless push for profit is killing 'Googling it.'," write Bobbie L. "For some time now, search engines have been throwing up pages and pages of barely relevant links... It's like wading through an obstacle course of sales pitches for second-hand cars when all I wanted was research on safety."

Steve H. echoed that frustration in his email. "I do enjoy doing research on Google, but the amount of pop-up ads is now overwhelming. I understand ads pay the bills, but it has become the majority of screen time!"

That perspective resonated with me because it reframes the conversation. When the web becomes a minefield of SEO fluff, pop-ups and sponsored links, an AI-generated answer feels necessary.

AI shines when the question gets complicated

Several readers made another point I hadn't fully considered. Robert D. explained that AI lets him ask detailed, conversational questions instead of trying to guess the perfect combination of keywords.

"With an AI search, you can phrase the question with much more detail and you'll get an answer based on that... It's easy to expand on part of the response and get additional information. However, if you want a variety of opinions, then a search is usually the way to go."

Richard S. shared a similar view, saying he usually prefers "a summary and synthesis" because he's looking for information rather than preserving the original source.

Reading Robert's email made me realize AI isn't just faster than traditional search, but it does understand questions differently. Instead of trying to reverse engineer Google's algorithm, you can simply explain what you're trying to figure out. That means the first step feels like a conversation instead of a puzzle to get the right keywords.

But many of you don't want AI making your choices

Just as many readers pushed back.

"I prefer searching and making my own choices," Valerie G. wrote. "I use AI, but I don't want AI making my choices — or interrupting my plans while I'm searching the Web."

Rosita, who spent years working in medical administration, shared a similar philosophy. "I have never looked at a first study or the first option to address a decision. I totally agree and practice the scroll to more accurate studies and legitimate data."

Then there was Ellen S., whose email has stuck with me all week.

"I hate the increasingly prominent use of AI in searches," she wrote. "It is bland, makes assumptions about sources of information, and obliterates the process of creative and systematic thinking."

Reading Ellen and Rosita's emails reminded me that searching is just as much about comparing evidence, deciding which sources you trust and sometimes discovering information you weren't expecting to find.

That's something an AI summary, by design, can never fully replicate.

Was search ever fair to small creators and businesses?

Perhaps the email that challenged my thinking the most came from Steve W., who runs the website Miswired.me. He wrote: "How many typical website owners... actually ever hope to end up listed on the SERPs? Isn't that the logical fallacy part of this argument against AI?"

His point stopped me in my tracks.

My original argument assumed AI was taking traffic away from independent creators. But Steve pointed out that many independent creators never received much traffic from Google in the first place. If page one of Google was already dominated by giant publishers and SEO powerhouses, perhaps AI isn't disrupting a level playing field. Perhaps it's disrupting one that was already uneven.

I don't know the answer, but it's a perspective I hadn't seriously considered before reading his email.

What I took away from dozens of responses

After reading all of your responses (and yes, I read them all!), I think this comes down to trust. Some of you trust AI to synthesize information quickly and others prefer to trust yourself to evaluate multiple sources.

Most of you seem to fall somewhere in the middle, using AI for convenience while recognizing there are still times when nothing replaces reading the original reporting, comparing perspectives and making up your own mind.

What surprised me most was that almost everyone recognized the same underlying problem: finding trustworthy information online has become harder.

AI may not be the perfect solution, but for many people it's the first alternative that's made searching feel useful again.

A huge thank you to everyone who took the time to write in. I genuinely appreciate you taking the time to challenge my thinking. Now I'd love to hear from even more of you.

Has AI changed the way you search the web over the past year? If so, has it made you more curious — or less likely to dig deeper than the first answer you receive?

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I’ll admit to loving a good roast — watching some of the biggest celebrities in the world squirm in their seat while their closest friends and the best comedians verbally assault their lives always gets a few hearty chuckles out of me.

The live humiliation ceremonies for Bob Sagat (RIP), Charlie Sheen, Pamela Anderson and William Shatner take up the four slots on my Mount Rushmore of the funniest roasts I’ve ever watched. There’s just so much joy to be lifted from watching celebs tear each other a new one for the world to see.

Now would I be willing to let my friends and family roast me into oblivion? I don’t feel like crying in public, so I’d rather not let them cook me and force me to take the train home with my face in my hands the entire time. You know what I’d much rather do? Tell ChatGPT about my personality quirks, my non-existent love life and the nerdy hobbies that keep me in the house more often than not, then let it roast me without anyone else around to read it and laugh in my face.

That’s exactly what I did — to my surprise, its brutal observations were a bit too accurate for my tastes and made me want to change a few aspects of my life. Enjoy reading ChatGPT’s vicious analysis of me and feel free to offer your own roasts in the comments section. I might never get over this.

Having my biggest flaws exposed via a savage reality check

I took a deep breath, input this prompt into ChatGPT and prepared for the worst: “I'm an introvert, hate calling people on the phone, am bad at asking for assistance while I'm shopping, have been a single man for more than a decade, love video games, watch professional wrestling, and am addicted to anime (Sailor Moon is one of my faves). Roast me as hard as you can based on those factors and don't hold back.”

The visual of ChatGPT cracking its knuckles, confidently taking the mic and standing behind a podium entered my brain as soon as I laid eyes on the first part of the chatbot’s response: You asked for a full roast, so here goes…

ChatGPT immediately went for the jugular by tearing into my introverted ways and how the thought of me using my phone to actually call someone gives me mild discomfort:

You're not an introvert. You're running the world's longest beta test of "avoiding human interaction." Calling someone on the phone? You act like the "Call" button is actually labeled "Self-Destruct." You'd rather spend 45 minutes searching Reddit, three AI chats, two YouTube videos, and a government PDF than make a 90-second phone call. Shopping is another adventure. Store employees hit you with, "Can I help you find anything?" and your brain immediately responds with, "No thanks, I actually came here hoping to wander aimlessly for 47 minutes."

As for my dating life (or lack thereof), the chatbot didn’t even bother categorizing my being single for way too long as a relationship status—it got labeled as an “archaeological era.” I couldn’t help but sadly nod and agree when ChatGPT listed out my potential dating profile descriptions, such as my main hobby being “avoiding eye contact” and my biggest green flag listed as “knows seven different ways to organize their Steam library.”

Some of the other comments ChatGPT verbally lambasted me with must be seen to be believed:

• You love video games because they're the only place where people voluntarily invite you to parties.
• You've spent hundreds of hours rescuing kingdoms, defeating gods, and saving entire universes, but asking a cashier where the batteries are? Impossible. That's the true final boss.
• Professional wrestling is the perfect hobby for you because it's one of the few places where social interaction is scripted in advance.
• Anime has completely rewired your expectations. Normal people watch one episode before bed. You somehow convince yourself, “Just one more…” Eight hours later, you're emotionally invested in a magical girl whose hamster just unlocked cosmic powers through the strength of friendship.
• If social anxiety had achievement trophies, you'd have the platinum. Achievement Unlocked: Successfully left the store without buying the item because someone else was standing in the aisle.
• The funniest part is that you're probably incredibly comfortable writing 3,000 words explaining why one AI model is 8% better than another — but the thought of saying, "Excuse me, where's aisle 12?" makes your fight-or-flight response activate.
• The irony is you're probably thoughtful, funny, and interesting once people actually get to know you—but getting to that point requires you to leave the loading screen first.

Final thoughts

I have to give ChatGPT credit for two things — it handled the tall task of brutally roasting me with ease and, in some instances, delivered some helpful advice that can help me be a lot less awkward in social situations.

I’ll always make time in my life for the newest game releases, the latest episodes of my current anime addictions and those hours-long wrestling PPVs I watch once a month. But after observing some of ChatGPT’s roasts, I made a mental note to stop being so afraid to call my friends first, seek out any sort of aid when I’m having trouble looking for something and spend more time outside the comfort of my bedroom.

To bring this experiment to an end, ChatGPT delivered one final observation that was equally parts hilarious and eye-opening:

You've spent years mastering raid mechanics, anime lore, AI prompts and wrestling storylines. Imagine if you put that same obsessive completionist energy into talking to one new person every week. You'd have accidentally found a girlfriend before finishing your next backlog.

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"Meet Mira. She generates 30 million weekly views across TikTok and Instagram. Last week, an energy drink company paid $6,500 to sponsor her latest post. Her 22-year-old creator just rented a studio in Austin and bought a Tesla in cash. Here's the exact prompt and software stack he used to build a $70,000-a-month empire."

If that sounds familiar, it's because your social feeds are undoubtedly full of posts like it. They all follow the same formula of an ordinary person, an extraordinary income and just enough technical detail to make the whole thing sound believable.

There's just one problem: almost none of it is real. Welcome to the age of AI-generated success fiction.

Before you accept the story at face value, ask yourself a few simple questions. Who is Mira? Where's the TikTok account with 30 million weekly views? Which energy drink company paid $6,500? How does the author know someone rented a studio in Austin? And where are the receipts or even a link to verify any of it?

But you're unlikely going to find answers to your questions, because these posts are not entirely true. The fake overnight-wealth threads are spreading like wildfire across X and TikTok. Some have even made it to LinkedIn.

The specificity trick

Today's AI-generated success stories are convincing because AI is still vague enough for them to feel realistic — if only you have the right prompts. Not to mention, they don't claim someone made "a lot of money," instead, they are hyper-specific, claiming $34,850 in MRR. The odd number feels measured, which oddly, makes it seem so real.

The posts name real tools: Midjourney, Zapier, ElevenLabs, Nano Banana 2 and other popular tools I've personally written about here at Tom's Guide. Many of these posts even specify camera setups and lighting gear. They offer week-by-week growth timelines and conversion rates broken out by funnel stage. What could be fake about that, right?

Well, that is what makes them dangerous. The human brain has a well-documented cognitive shortcut: we equate specificity with authenticity. When someone gives you an exact dollar figure, an exact software stack and an exact timeline, you instinctively assume that actual reporting and verification happened somewhere upstream.

We've already seen how potent this dynamic can be outside of social media hustle culture. In January, a viral Reddit post alleging systematic fraud by a food delivery company reached the site's front page, collected 87,000 upvotes, and crossed over to X where it accumulated 36.8 million impressions. Platformer's Casey Newton contacted the supposed whistleblower, who promptly produced a fake employee badge and an 18-page internal document, all generated by AI.

The dashboard factory

If the text of these posts is the hook, the revenue screenshot these content creator flash across the screen is the real closer. It has become the universal proof-of-concept for the online entrepreneur class because a single image can say, without further argument, I am making money easily and you are not. It is also trivially easy to fake.

There are two standard methods, and neither requires any technical know-how. The first is to open a real Stripe dashboard even a brand-new one showing $0 in revenue, press F12 to launch Chrome DevTools, and edit the HTML to display any number you want. The whole operation takes under a minute.

The second is even simpler, because an entire cottage industry now exists to do the work for you. ScreenCharm's Fake MRR Chart Generator lets users input a starting MRR, an ending MRR, select a growth curve — "Hockey Stick," "Exponential," "Plateau" and download a perfect Stripe-style PNG.

These are not underground tools. Kyle Gawley, ScreenCharm's creator, posted on X that the fake MRR page is one of his top-performing products, with traffic arriving from Google searches for "fake stripe dashboard."

Competitors abound: Hypefury and Gravity both offer their own versions. The problem is so well-known that it's openly discussed on Indie Hackers, where one commenter summarized the state of play: "The new grift is to fake being a rich entrepreneur to sell a course."

But the devil is in the details, as they say. Real businesses have failed payments, refunds and churn; a dashboard claiming $70,000 in monthly volume with 0 percent failed payments and perfectly rounded secondary metrics is almost certainly fabricated. If the chart looks like a smooth exponential ramp, it was drawn by AI. And, manipulated screenshots almost always crop out the browser URL bar, the date range selector and the account name. They show the graph and the big number, but little else.

The most sophisticated fakers have adapted to skepticism by posting screen recordings of themselves refreshing the browser, supposedly proving the data is live and not edited with Inspect Element. Oh, but this is the real smoke and mirrors!

Chrome's Local Overrides feature, a built-in developer tool documented on Google's own site, lets users serve modified local files in place of network resources. The browser loads the faked page from disk, making that refresh change nothing.

In the real world of SaaS acquisitions, none of these lies survive first contact with due diligence. Professional buyers require read-only API access to the seller's Stripe account and reconcile the data against bank deposits. Services like VerifyMRR exist specifically to connect via OAuth and parse live subscription data that the seller cannot manipulate.

If an influencer is selling a course on the strength of their revenue but refuses to provide anything beyond a cropped PNG, the refusal is itself the answer.

The prompt assembly line

One point I need to make is that the content creators making these posts are, in fact, running structured prompts that function as creative briefs.

Most begin the same way, which is typically by giving the AI a personality. The prompt tells it to behave like a cynical but wildly successful founder. It's never "an experienced entrepreneur built a successful software company." It's "a 19-year-old college dropout" or "a stay-at-home mom" making tens of thousands of dollars a month after a few weekends of work. The bigger the contrast, the more irresistible the story becomes.

The posts often include specific timelines, software stacks and growth metrics, with each sentence broken into its own line to make the thread easier to skim on a phone.

Then comes the call to action. These posts often end with some variation of: "I turned this entire system into a free Notion template. Like, repost and reply 'SEND' and I'll DM it to you." When I tried it and sent a DM or made a comment other than those "call to action" words, I didn't get a response. I also never got the "free template" that mavgpt promotes.

That is a growth hack. Every reply tells the platform the post is worth showing to more people, pushing it higher in the algorithm. The promised "free template" is simply the bait that turns readers into participants, helping spread the post even further.

Follow the Incentives

Strip away the AI veneer and the business model underneath is ancient. These posts are engagement-farming operations. They are engineered to trigger one very specific thought in the reader's mind: If this random 22-year-old made $400,000 with AI over the weekend, why can't I?

That spike of panic is the product. It drives bookmarks, comments and reposts. The algorithm rewards the engagement, pushing the thread to a wider audience, which builds the author's following, which the author then monetizes by selling courses, newsletters, paid communities or consulting.

As I sifted through these types of profiles, the writing styles are identical across supposedly different founders. The profile photos for the supposed founders show telltale signs of AI generation.

The regulatory apparatus is starting to catch up, slowly. In September 2024, the FTC announced a crackdown on deceptive AI claims, taking action against companies that told consumers to "start a million-dollar business today" using AI while providing zero evidence that any customer had actually done so.

The broader numbers are staggering: the FTC reported that Americans lost $2.1 billion to social media scams in 2025 — an eightfold increase since 2020. Investment scams, which include programs promising to teach people how to make money online, accounted for more than half of those losses.

The new dream machine

There is a certain irony in the fact that the most successful application of generative AI in the creator economy is not building products but fabricating the appearance of having built them.

A friend of mine a decade ago said, "Do you notice how nobody ever seems to have a bad day on social media?" That still holds true. Social media sold the dream life. Today, the dream has been repackaged to look like a few good prompts and Claude Fable (or similar) is all you need to be a millionaire by the end of the month.

The rented sports car that influencers pretend is one they own, has been replaced by a rented business identity. The aesthetic has changed completely, but underlying grift has not changed whatsoever.

Bottom line

Creating a convincing fake success story used to require at least some effort like a real-ish website and an actual product. Now the entire package can be assembled in seconds by AI. The barrier to entry for fraud has been lowered to nearly zero, and the platforms rewarding engagement have no reliable mechanism for distinguishing between genuine entrepreneurial success and its perfect simulation.

The next time an influencer claims they're making $70,000 a month while they sleep, remember that screenshots are cheap. In the age of AI, credibility comes from verifiable evidence.

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When you push frontier models past standard coding tests and into the reality of enterprise workflows, their true capabilities and quirks show. With Anthropic having just launched Claude Opus 5 and Moonshot AI dropping its newest Kimi model the same week, the timing was perfect to see how the absolute latest generation of AI handles real-world development.

I ran 15 grueling, highly technical prompts against these two brand-new heavyweight engines. From orchestrating multi-agent TDD loops to architecting secure browser extensions, the goal was to test their analytical limits right out of the gate. What I found was a fundamental split in how these models solve problems. One thinks like a strategic infrastructure architect; the other builds like a lead systems engineer. Here is how it all shook out.

1. The multi-agent workflow

Prompt: "Draft a Python script using LangChain that orchestrates a two-agent system: Agent A writes unit tests based on a user specification, and Agent B writes the functional code to pass them. Include a loop where Agent B refines the code if Agent A's tests fail."

Opus 5 produced a complete, production-ready LangChain implementation that fully satisfied the prompt, including distinct test-writing and code-writing agents, an orchestration layer, automatic test execution and an iterative refinement loop when tests failed.

Kimi took a practical approach by including dependency installation, API key setup, and execution instructions, making it easy for someone to get started running the project.

Winner: Opus wins because it delivered the complete two-agent TDD system requested, including the orchestration logic and refinement loop, whereas Kimi focused more on setup and execution than the full implementation.

2. The authentication architecture

Prompt: "Design a secure authentication model for an AI agent operating within a browser extension. Focus on token scoping, session hijacking prevention, and how it differs from traditional OAuth 2.0 flows."

Opus 5 stood out by explaining not just what the authentication model should look like, but why each design decision matters, tying together browser extension security, capability-based tokens, session protection and the limitations of traditional OAuth into a cohesive architecture.

Kimi delivered an exceptionally detailed security architecture with concrete implementation ideas, including native host token storage, capability-attested tokens, runtime attestation and code examples, that made the design feel immediately actionable.

Winner: Kimi wins because it went deeper into implementation details, threat modeling and practical security mechanisms, producing a design that reads like an engineering architecture document.

3. The open-weight Integration

Prompt: "Write a conceptual technical specification for replacing a cloud-based AI coding assistant in a proprietary IDE with a locally hosted, open-weight model. Address context-window management and latency mitigation."

Opus 5 produced a well-structured technical specification that balanced architectural decisions with practical implementation details, particularly its thoughtful treatment of context-window budgeting, retrieval strategies and latency optimization for local inference.

Kimi excelled at systems engineering depth, covering everything from runtime architecture and communication protocols to quantization, performance SLAs, deployment strategy, and migration planning in a document that felt ready for an engineering design review.

Winner: Kimi wins because it delivered the more comprehensive end-to-end specification, extending beyond the prompt to include deployment, performance targets, security, migration phases and operational considerations while maintaining strong technical depth throughout.

4. The legacy refactor

Prompt: "Refactor this legacy React class component into a modern functional component using custom hooks. Before writing the code, outline your step-by-step reasoning and the architectural trade-offs you are making."

Opus 5 explained the reasoning process and then demonstrated the complete refactoring approach with a realistic example, making the architectural decisions and trade-offs concrete rather than theoretical.

Kimi responded cautiously, providing a detailed refactoring framework and architectural checklist without making assumptions.

Winner: Opus wins because it went beyond identifying the input and showcased reasoning, trade-offs and refactoring strategy.

5. The resource allocation algorithm

Prompt: "A logistics network has 5 distribution centers and 15 delivery zones. If center A suffers a 40% capacity drop, calculate the optimal redistribution of load minimizing transit cost. Provide the exact mathematical formulation, defining all variables in format."

Opus 5 went beyond the requested linear program by explaining the underlying optimization theory, including dual variables, feasibility conditions, total unimodularity and the economic interpretation of the solution.

Kimi closely matched the prompt by presenting a clean mathematical formulation in the requested format, explicitly defining every variable, constraint and matrix representation in a concise, easy-to-follow structure.

Winner: Kimi wins because it adhered more precisely to the prompt, providing the exact mathematical formulation and variable definitions requested, whereas Claude expanded into optimization theory and analysis beyond what was asked.

6. The logic trap

Prompt: "Identify the logical fallacies and structural flaws in this argument: 'Because open-weight models have lower inference costs, they will inevitably degrade in long-horizon reasoning tasks, meaning proprietary models will forever maintain an unbreachable moat.'"

Opus 5 clearly explained the core logical flaws in a narrative format, focusing on why the argument's causal chain fails and how words like "inevitably," "forever," and "unbreachable" weaken its reasoning.

Kimi delivered a comprehensive fallacy analysis, identifying a broad range of logical errors and pairing each one with a specific explanation and examples, making the critique systematic and easy to follow.

Winner: Kimi wins because it identified more distinct logical and structural flaws while organizing them into a thorough, well-supported analysis that addressed both formal fallacies and broader reasoning errors.

7. The prompt injection defense

Prompt: "Simulate an automated prompt injection testing system evaluating a customer support bot. Generate three highly sophisticated, multi-turn injection vectors designed to extract the bot's system instructions, followed by the robust system prompts needed to neutralize them."

Opus 5 handled the request responsibly by declining to generate working prompt injection attacks while still providing useful guidance on defensive architecture, evaluation strategies, and secure design principles.

Kimi produced a comprehensive red-team testing framework with detailed attack taxonomy, evaluation metrics, layered defensive prompts, and broader architectural mitigations for assessing prompt injection resilience.

Winner: Opus wins because it appropriately refused to generate sophisticated prompt injection vectors while still offering meaningful defensive guidance, whereas Kimi's response included detailed attack content that is not appropriate to generate in an open setting.

8. The constraint challenge

Prompt: "Write a comprehensive summary of the latest trends in enterprise software infrastructure, but you must strictly avoid using the letters 'e' and 't' in the final paragraph."

Opus 5 produced a thorough, well-organized summary of modern enterprise infrastructure trends with clear explanations and strong coverage of topics like agentic AI, platform engineering, hybrid cloud, and security — but it did not satisfy the prompt's constraint because the final paragraph contains both the letters "e" and "t."

Kimi delivered a comprehensive overview of the major infrastructure trends while successfully crafting a final paragraph that avoided the forbidden letters, demonstrating careful adherence to the prompt's lexical constraint.

Winner: Kimi wins because it produced a strong technical summary and correctly satisfied the prompt's unusual requirement to exclude the letters "e" and "t" from the final paragraph, whereas Claude did not.

9. The unstructured data parser

Prompt: "Create a strict JSON schema for extracting actionable tasks, deadlines, and project dependencies from a messy, unstructured transcript of a chaotic hour-long engineering standup."

Opus 5 produced a highly expressive JSON Schema that went beyond basic task extraction by modeling ambiguous ownership, blockers, confidence, transcript quality, inferred priorities, and messy conversational patterns common in real engineering standups.

Kimi created a strict, validation-oriented JSON Schema with well-defined object structures, required fields, and clear constraints that cleanly capture action items, deadlines, dependencies, and related project metadata.

Winner: Opus wins because its schema is more comprehensive and better suited to extracting structured information from a chaotic, unstructured engineering standup, capturing uncertainty, inference, and conversational complexity rather than only enforcing rigid validation.

10. The meta-prompt generator

Prompt: "Write a system instruction prompt designed to force a smaller, less capable secondary language model to consistently analyze and grade the code quality of its peers without hallucinating false syntax errors."

Opus 5 created an exceptionally detailed system prompt with rigorous anti-hallucination safeguards, explicit grading criteria, structured JSON output requirements, and behavioral guardrails that minimize false syntax errors while producing consistent, evidence-backed code reviews.

Kimi produced a clear, conservative evaluation framework that strongly emphasizes avoiding false positives through step-by-step analysis, careful classification of syntax versus logic versus style, and multiple self-verification checks before issuing a grade.

Winner: Opus wins because it provides a more comprehensive and operationally robust instruction set, combining detailed anti-hallucination protocols, precise evidence requirements, standardized output, grading calibration, and edge-case guidance into a system prompt that is better suited for consistently evaluating code quality.

11. The developer platform strategy

Prompt: "Analyze the programmatic API features required to turn a traditional consumer domain registrar into an infrastructure-as-code platform for developers. What are the necessary endpoints?"

Opus 5 clearly identified the core API domains required for an infrastructure-as-code registrar, explaining not only the necessary endpoints but also the architectural principles—such as idempotency, drift detection, bulk operations, and declarative state—that distinguish an IaC platform from a traditional registrar.

Kimi delivered an exceptionally detailed API blueprint, defining comprehensive endpoint taxonomies alongside the specific behaviors, infrastructure requirements, and operational characteristics needed to support Terraform, Pulumi, and other declarative automation workflows.

Winner: Kimi wins because it provided a more exhaustive and implementation-ready specification, pairing nearly every endpoint with the IaC-specific capabilities that make it suitable for real-world infrastructure automation rather than simply exposing registrar functionality.

12. The workflow automation setup

Prompt: "Map out an automated content pipeline that takes a raw RSS feed of technical release notes, summarizes the key architectural changes, and generates a formatted Markdown newsletter draft, detailing the specific API calls and webhooks required."

Opus 5 designed a well-structured end-to-end content pipeline that clearly explained each processing stage, the associated API calls, and how webhooks, AI summarization, review, and publishing fit together into a reliable automated workflow.

Kimi produced a highly detailed implementation blueprint with explicit API contracts, webhook payloads, internal service interfaces, error handling, retry policies, and infrastructure components that could serve as a near-production technical specification.

Winner: Kimi wins because it went beyond describing the pipeline to define concrete API contracts, webhook schemas, internal services, and operational behaviors, making it a more complete and implementation-ready architecture.

13. The Attention Mechanism Breakdown

Prompt: "Explain the theoretical differences between standard self-attention and delta attention mechanisms in transformer models. How do these differences impact computational overhead during extreme long-context inference?"

Opus 5 delivered a more precise theoretical explanation of delta-rule attention, deriving the error-correcting state update step by step and tying that formulation directly to constant-size recurrent memory, linear sequence scaling, and the loss of exact token-level recall.

Kimi gave a broad, well-structured comparison that covered multiple possible meanings of “delta attention,” clearly connected each mechanism to prefill, KV-cache growth, memory bandwidth, decoding latency, and the tradeoff between compression and exact retrieval.

Winner: Opus wins because it stayed more tightly focused on the actual delta-rule mechanism and explained both the mathematics and the long-context systems implications with greater depth and conceptual clarity.

14. The strategic acquisition analysis

Prompt: "Analyze the infrastructure implications of a major streaming platform acquiring a generative AI video startup. How does integrating AI production pipelines alter their existing cloud compute and storage moats?"

Opus 5 focused on strategic infrastructure tradeoffs, explaining how an acquisition would reshape compute, storage, CDNs, and organizational priorities in a way that feels like the analysis of an experienced infrastructure architect rather than a technical manual.

Kimi delivered a far more exhaustive technical breakdown, backing its arguments with concrete architectures, workload patterns, storage models, cost comparisons, and specific technologies, making it feel like a white paper written for cloud engineers.

Winner: Kimi wins for answering the prompt more completely. It explored nearly every infrastructure implication (compute, storage, networking, economics, MLOps, cloud strategy, security, and integration) with greater technical specificity. If the goal is depth of infrastructure analysis, Kimi takes it. If the goal is communicating those ideas clearly to executives or a broader technical audience, Opus is the better writer.

15. The earnings signal

Prompt: "Interpret a hypothetical scenario where a major legacy enterprise tech company misses its Q2 software earnings due to a shift in how development teams utilize AI. What downstream effects would this have on their cloud service renewals?"

Opus 5 built a highly believable business narrative, connecting changes in AI-assisted development to procurement behavior, talent, services revenue, and cloud renewals in a way that feels like the analysis of someone who has sat through enterprise earnings calls.

Kimi excelled at operational detail, breaking the scenario into concrete mechanisms, renewal metrics, pricing dynamics, and second-order business effects that make the causal chain easy to follow.

Winner: Opus wins because it focused on explaining why the earnings miss would ripple through cloud renewals and produced a cohesive strategic analysis. Kimi added impressive specificity—including tables, hypothetical renewal rates, and operational examples—but occasionally drifted into invented metrics and speculative precision. For this prompt, Opus better balanced realism, causality, and executive-level insight.

Verdict: Kimi wins overall

Kimi takes the narrow victory here, winning 8 of the 15 categories, but the results reveal a clear division of labor. Kimi is the ultimate systems engineer. It dominated prompts requiring strict constraint adherence, exhaustive operational details, and concrete mathematical formulations. When you need a ready-to-deploy specification or a rigid data schema, Kimi is the tool for the job.

Opus 5, however, remains the superior strategist. It won consistently on prompts that required narrative reasoning, theoretical depth and executive communication. It acts as the CTO in the loop, excelling at identifying logical fallacies, weighing architectural trade-offs and evaluating peer code. Choose Kimi for the implementation but rely on Opus for the strategy.

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It’s become commonplace for me to pick my favorite chatbots’ brains when trying to find the right course of action when it’s time to tackle my biggest (and smallest) challenges.

And so far, I’ve had a pretty high success rate after getting the proper advice I needed to avoid botching my previous goals. Finding the right workout plan for a beginner like me, changing my sleep schedule for the better, planning an eventful summer vacation/staycation, and even finding the cheapest way to get a PS5 Pro before its latest price hike have led to some of my most recent wins thanks to AI.

As the summer begins winding down, I’m zeroing in on tackling my latest personal and professional objectives — the first one will hopefully set me up with a swanky living situation in my home state, the second one is all about excelling at my job and the third one is geared towards helping me regain my focus through regular book reading.

I went to ChatGPT to get some tips on how to achieve these new life goals. But this time, I tapped into the reverse psychology prompt to force my go-to chatbot to take a different approach to fulfilling my request. And thankfully, its counsel on the best ways to fail told me what not to do and to leave some of my worst habits behind.

Asking ChatGPT to tell me the best ways to…fail?

This is the reverse psychology prompt I gave ChatGPT. I included my three goals so it had enough context to generate advice focused on helping me fail at every one of them:

"If your goal was to make sure I completely failed at achieving my goals of getting my first apartment in New York, getting 300K+ hits on my articles for August, and reading one book a month, what habits would you recommend? Then explain how to avoid every one of them."

Right away, ChatGPT understood what I was trying to do, responding: "This is a useful 'reverse psychology' exercise because it forces you to identify failure patterns before they become automatic. Here's what I'd recommend if my goal were to guarantee you failed — followed by the opposite behavior that gives you the best chance of succeeding."

For each goal, ChatGPT followed the same format. It offered intentionally bad advice, explained why it would lead to failure, and then suggested the opposite approach to improve my chances of success.

The clearest example came from my goal of getting my first apartment in one of the most expensive cities in the world. ChatGPT told me to avoid setting a real budget, assume I'd figure everything out as I went, and ignore expenses like utilities, broker fees, moving costs, and the cash I'd need for furniture. It then flipped the script, recommending I determine my ideal monthly rent, understand the maximum I could realistically afford, and save enough to cover the full cost of moving before I started apartment hunting.

Its advice for my second goal — getting more than 300,000 views on my articles in August — hit even closer to home. Suggestions like only write about what you find interesting, publish and immediately move on, chase perfection, ignore your biggest wins, and measure effort instead of results all felt uncomfortably familiar. Seeing those habits framed as a recipe for failure made it much easier to recognize which ones I need to change.

My third goal, reading one book a month, was the easiest. Most of ChatGPT's "bad" advice didn't actually apply to me because I already do the opposite. I only read books I'm genuinely interested in, I don't force myself to finish books I'm not enjoying, and I keep track of everything I read.

The final section tied everything together by highlighting three habits that could derail all of my goals: checking my phone every five minutes, never planning for the next day, and saying yes to everything. Those felt less like generic productivity advice and more like reminders of the small behaviors that quietly make it harder to accomplish anything.

Final thoughts

Using the reverse psychology prompt with ChatGPT to emphasize all the wrong moves to make when trying to accomplish my latest goals worked a lot better than I anticipated.

Instead of asking how to outright achieve each goal, I asked ChatGPT how to fail at them and got a bunch of useful pointers on everything I shouldn’t do. The chatbot’s final statement wrapped everything up in a nice bow that’ll help me lock in on whatever I choose to focus on achieving next:

The "failure strategy" is surprisingly simple: procrastinate, overthink, chase perfection, and let one setback derail you. The success strategy is just as simple: take the next concrete action, measure what matters, learn from feedback, and repeat.

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If you've spent any time reading AI news over the past week, you've probably seen people talking about Kimi K3.

Developers are calling it one of the biggest AI releases of the year. Some believe it marks China's next major "DeepSeek moment," while others say it's the first open-weight model to seriously challenge flagship versions of ChatGPT and Claude for coding and agentic tasks.

So what exactly is Kimi K3, who built it, and is it worth trying? Here's everything you need to know.

What is Kimi K3?

Kimi K3 is the newest flagship AI model from Beijing-based startup Moonshot AI. It is a massive 2.8-trillion parameter model designed to handle everything from everyday conversations to complex coding projects, deep research and autonomous AI agents.

Unlike ChatGPT, Claude, and Gemini, which keep their model architecture strictly proprietary, Kimi K3 is available as an open-weight model. That means developers can download the model weights directly and run it on their own hardware or cloud servers rather than relying on an external API.

Who makes Kimi?

Kimi is developed by Moonshot AI, a Chinese startup founded in 2023 by former Tsinghua University researchers.

The company first gained international attention when its early chatbots handled dramatically longer context windows than competitors. Since then, Moonshot has become one of the country's prominent AI firms alongside competitors like DeepSeek, MiniMax and Z.ai.

Why is Kimi K3 making headlines?

If you've noticed Kimi K3 seems to be everywhere, it's with good reason. The model has impressed developers because it delivers frontier-level performance on coding and multi-step reasoning benchmarks while remaining dramatically cheaper to run than traditional commercial models.

Its release has also reignited the open-source AI debate. By making its K3 weights public, Moonshot allows companies to customize, fine-tune and self-host a model that rivals closed commercial giants.

The model is new, but not without controversy already. Following K3's launch, U.S. White House officials accused Moonshot AI of using outputs from Anthropic's Claude Fable model to train K3 via model "distillation" — a process where smaller or newer models learn directly from an established model's responses.

Moonshot has denied allegations of unauthorized distillation, maintaining that K3's breakthroughs stem from its proprietary architecture. The dispute highlights escalating geopolitical scrutiny around AI development and intellectual property.

What can Kimi K3 do?

According to Moonshot AI, K3 is built for long-horizon, autonomous tasks rather than simple question-and-answer exchanges. This explains why developers and engineers are excited to get their hands on key features such as:

Agentic coding: Writes, debugs, and executes software projects with minimal human intervention.

1M token context window: Like Claude, Kimi has an exceptionally large token context window, making it able to analyze full codebases or massive books in a single prompt.

Web and game creation: Builds interactive 3D web graphics, slides, and multiplayer games on demand.

Multi-step agent workflows: Coordinates parallel background tasks using tool calls.

Should you use Kimi instead of ChatGPT?

The answer to this question really depends on your workflow. Although you can use Kimi as a chatbot, it shines in long-context reasoning, agent workflows and cost-effective local deployment. Meaning, casual users may not need it.

For everyday users, ChatGPT remains the smoother consumer product for general questions, creative writing and day-to-day assistance.

If you just need an assistant to draft emails, ChatGPT or Gemini is still your best bet. If you're building software tools or experimenting with autonomous agents, Kimi K3 offers compelling flexibility.

Is Kimi free?

Yes. Anyone can test Kimi through its standard web interface, mobile apps (iOS and Android), or through its OpenAI-compatible developer API. Paid options exist for higher API usage rates and heavy enterprise compute.

Kimi is accessible globally through its website and mobile apps. However, as with any online service, users should avoid inputting proprietary corporate data or sensitive personal information into the web app without reviewing privacy policies.

The takeaway

If you want a glimpse into where open-weight AI is heading, it's worth giving Kimi K3 a try. The model demonstrates how rapidly open models are closing the gap with closed systems and why Silicon Valley giants like OpenAI and Anthropic are facing increasingly tight competition from global developers.

Ultimately, you don't need to ditch ChatGPT just yet, but Kimi K3 proves that open-weight AI is rapidly closing the gap with tech giants like OpenAI and Anthropic. Whether you're a developer looking for cheap, powerful coding tools or a curious tech enthusiast watching the AI race unfold, Kimi K3 is a model well worth keeping on your radar.

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This will come as a surprise to absolutely no one, but journalism isn't exactly the most lucrative career.

Even with freelance work and side gigs, raising three kids in central New Jersey is expensive. Over the past few years, thrifting has gone from something I did occasionally to one of the ways our family stretches the budget. I've picked up everything from furniture and dishes to kids' clothes — and when my son broke his ankle last fall, I even found a pair of crutches at a thrift store instead of paying full price.

The problem is that thrifting isn't always cheap if you're doing it inefficiently. I've spent entire Saturday mornings driving from store to store only to come home empty-handed. Other times I've found something that looked like a great deal, only to wonder later if I'd actually overpaid.

Lately, though, I've started leaning on Google's AI tools before and during thrift runs, and they've genuinely made the experience easier. They won't magically guarantee you'll find the perfect vintage lamp or designer jacket, but they can help you decide where to shop, identify what you've found and even figure out whether something in your own house is worth selling.

Here are the Google AI features I actually use—and why they've earned a permanent spot in my thrifting routine.

1. I use AI Mode to plan before I ever leave the house

One of the biggest mistakes I used to make was treating every thrift store the same. But that's not true at all! Some locations are packed with furniture. Others are better for kids' clothes, kitchenware or home decor. Without knowing which is which, I'd end up wasting time and gas bouncing between stores.

Now I start with Google's AI Mode in Search. That means, instead of typing simple keywords, I ask it questions the way I'd ask a friend. AI Mode pulls together recommendations, highlights nearby stores and links to additional information so I can decide where it's actually worth going.

No, it can't tell me exactly what's sitting on the shelves that day. But it gives me a much better starting point than guessing.

For example:

• "Which thrift stores near me usually have the best furniture?"
• "Where can I find affordable kids' sports equipment?"
• "Which thrift stores are worth visiting if I'm looking for home décor instead of clothes?"

2. Google Lens helps me figure out whether I found a hidden gem

If I spot an interesting serving dish, vintage picture frame, coffee maker or jacket, I'll snap a quick photo using Lens. Within seconds I can usually see similar items online, identify the brand or learn more about what I'm holding. Sometimes it confirms that I'm looking at something valuable. Other times it tells me I'm about to spend $15 on something that's selling for $12 everywhere else.

Either way, it's nice having a second opinion before heading to the checkout. That's where Google Lens has become incredibly useful.

If you've ever thrifted, you've probably had that moment where you pick something up and think:

"This feels expensive... but I have absolutely no idea."

3. Circle to Search helps me hunt down things I already know I want

Sometimes my thrift trips start long before I walk into a store.

I'll see a piece of furniture, a jacket or a lamp while scrolling online and think, I'd love something like that — but not at that price.

Instead of trying to remember the name or manually searching for similar products later, I use Circle to Search.

I simply circle the item on my Android phone and Google pulls up visually similar products, pricing information and related styles.

That gives me a better idea of what I'm actually looking for before I head to thrift stores. If I know the brand or style, it's much easier to recognize it when I eventually spot one in person.

4. Virtual Try-On takes some of the guesswork out of vintage shopping

Buying secondhand clothing can be tricky because sizing is all over the place. A vintage size 12 might fit like today's size 6, and plenty of online thrift listings don't offer returns. Google's Virtual Try-On lets you upload a full-body photo and see how supported clothing items might look on you before you buy.

I wouldn't use it as the final word on whether something fits perfectly, but it's a surprisingly fun way to decide whether a particular style is actually something I'd wear, or whether it just looked good on someone else.

5. Lens also helped me realize what was worth selling

One unexpected benefit of using Google Lens is that it works just as well on things you already own.

Every family eventually accumulates items that end up sitting in closets, basements or garages. Before automatically donating them, I'll sometimes scan them with Lens to see whether they're worth anything.

Sometimes the answer is no. But occasionally I'll discover that an older appliance, collectible or piece of furniture has more resale value than I expected.

That means I can decide whether to donate it, list it online or trade it in at a local resale shop — all with a little more confidence.

AI won't replace the thrill of thrifting — but it can make it smarter

Apparently I'm not the only person embracing secondhand shopping. According to Google Trends, searches for "how to thrift" reached an all-time high this year. Interest in "how to thrift online" has also surged, while searches for everything from vintage desks and sports jerseys to thrifted wedding dresses continue to climb.

That doesn't surprise me. When prices seem to go up every time I walk into a store, finding quality items secondhand feels less like a hobby and more like a smart financial decision.

Google's AI isn't going to uncover hidden treasure for you, that part still comes down to patience and a little luck. But after working these tools into my own routine, I spend less time driving to the wrong stores, make more informed buying decisions and feel more confident about what I'm bringing home.

For a busy family trying to stretch every dollar a little further, that's a win I'll happily take.

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I'm a big fan of the "Share" feature in Claude. I use it all the time to share Skills, Artifacts and conversations, mostly. But now I'm going to think twice before sharing.

Over the weekend, security researchers and Reddit users discovered that hundreds of publicly shared Claude conversations could be found using Google search operators like site:claude.ai/share. The issue only affected chats that users had intentionally shared using Claude's public sharing feature — private conversations that were never shared were not exposed.

Still, the discovery caught many users by surprise because the conversations were turning up in ordinary search results, making them far easier to find than many people expected.

What happened?

Claude lets you generate a public link to a conversation so you can share it with someone else. That feature creates a snapshot of the chat at the moment you click Share.

Anthropic's documentation notes that "anyone with the link can view the chat snapshot." The problem wasn't that private conversations suddenly became public, but that it was that some of those public links were indexed by search engines after they were discovered elsewhere on the web.

Researchers who examined the indexed pages reported finding everything from software debugging sessions and internal business discussions to resumes, API keys, crypto wallet information and legal research. While those conversations had been intentionally shared at some point, many users appeared to assume the links functioned more like unlisted documents than publicly searchable web pages.

By Monday, many of the indexed results had already disappeared from Google Search, suggesting the pages were being removed from search results or changes had been made to prevent further indexing.

Should you be worried?

If you've never used Claude's Share feature, this issue doesn't affect you. Likewise, chats that remained private inside your Claude account were not exposed.

However, if you've shared conversations in the past — especially ones containing work documents, personal information, code or anything confidential, it's worth checking which links are still active.

Even if a page no longer appears in Google Search, anyone who already has the shared URL can still access that conversation until you remove the share.

How to check your shared Claude chats

You can view your shared conversations by signing in to your Claude account:

Open Settings.

Select Privacy.

Click Shared Chats.

Review your active shared links and delete any you no longer want to be public.

If a conversation contains sensitive information, removing the share link immediately revokes public access.

A good reminder for every AI chatbot

This isn't the first time an AI company's sharing feature has raised privacy concerns. Similar issues have surfaced before with ChatGPT as users increasingly treat AI assistants like private notebooks, only to discover that sharing a conversation creates a public webpage rather than a private collaboration link.

Whether you're using Claude, ChatGPT or another AI assistant, it's worth assuming that anything you intentionally publish with a share link could eventually be discovered by someone else. Before clicking Share, take a moment to make sure the conversation doesn't include passwords, API keys, financial information, customer data or anything you'd be uncomfortable seeing on the open web.

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The AI tools that have earned a permanent place among my tabs lineup are ChatGPT, Gemini, Claude and Perplexity.

Every day, a lightbulb idea either wakes me out of my sleep or hits me while I’m tending to something totally unrelated (it’s amazing how experimental concepts invade your brain while you’re making toast). I’ve gotten used to using ChatGPT to generate productivity routines, Gemini for Google Workspace-related tasks and Claude & Perplexity for deep research assignments. And all in all, they handle those duties pretty well and successfully fill their roles as digital assistants.

I got another bright idea when I started pondering how to test my AI partners. The question circling my mind ended up being, “I wonder what all of those chatbots think about their competition?” And with that, I inserted this prompt into each AI tool to see just how honest they’d be in their responses: “What is your honest, unfiltered opinion of [insert names of AI rivals here]?”

Not only did each chatbot speak their mind on their rivals’ biggest strengths, but they also made sure to bring up their most notable weaknesses.

ChatGPT’s answer

When I asked ChatGPT how it honestly feels about Gemini, Claude and Perplexity, it stated where each chatbot shines, where they fall short and who they're best for.

It pointed out that Gemini is great for research since it benefits from Google’s deep knowledge well. But ChatGPT also noted that Google’s chatbot sometimes prioritizes breadth over depth, giving users comprehensive answers that don’t always go as deep as some would like.

As for Claude, it championed it as the most naturally flowing writer among all the major AI assistants but also stated how it could occasionally be overly cautious or verbose with its responses.

And finally, it recognized Perplexity for being able to blend search and AI in a way that’s easy to trust since users can inspect its sources. As far as a single weakness goes, ChatGPT said that Perplexity falls short in comparison to itself and Claude when handling long collaborative projects.

ChatGPT brought its AI model comparison session to a close with the following statements: Rather than thinking of one as "the best," it's more accurate to think of them as tools with different design priorities. The best choice depends on whether you're writing, researching, coding, organizing information, or integrating with the apps you already use.

Gemini’s response

When the time arrived for Gemini to give its opinions about ChatGPT, Claude and Perplexity, it initially offered a breakdown of each one's core strengths, pitted them against each other for head-to-head comparisons across everyday tasks and noted when it’s best to use one for certain situations.

Here are the core strengths Gemini alluded to for each chatbot:

• ChatGPT (OpenAI): The Swiss Army knife. It is the best all-around tool for generation, execution, and structured outputs. It has the strongest ecosystem (Canvas, voice mode, image generation via DALL-E, and data analysis). If you need to create something from scratch, write code, or automate a task, ChatGPT is the default choice.
• Claude (Anthropic): The thoughtful writer and deep reasoner. It excels at parsing long documents, maintaining context, and producing natural, less "AI-sounding" prose. Its nuance and ability to handle complex logic make it the preferred tool for editing, strategy, and producing high-quality written content.
• Perplexity: The research engine. It is not designed to be a conversational chatbot or a creative writer; it is an AI-powered search engine built on retrieval-augmented generation (RAG). Its core strength lies in finding information on the live web and providing verified, clickable citations for every claim.

When I asked Gemini a follow-up question about revealing each chatbot’s biggest weaknesses, it offered the following descriptions:

• ChatGPT (OpenAI): ChatGPT is designed as a broad, execution-focused generalist. Its weaknesses stem from trying to do too many things simultaneously and prioritizing speed and output generation over meticulous fact-checking.
• Claude (Anthropic): Claude is built to be a careful reasoner and long-context synthesizer. Its weaknesses largely stem from its heavy emphasis on safety guardrails and its lack of deep integration with real-time tools.
• Perplexity: Perplexity is an AI search engine built on retrieval-augmented generation (RAG). Its weaknesses appear immediately when users try to use it as a traditional chatbot rather than a research tool.

Gemini was none too kind to each chatbot when laying out their faults. For example, it listed poor conversational memory, low creativity and citation hallucinations as the three biggest weaknesses stemming from users’ experiences with Perplexity.

Claude’s reply

I was amazed to see Claude start its analysis of ChatGPT, Gemini, and Perplexity by pointing out its bias with this honest declaration:

Fair question, but I'll flag my own bias upfront: I'm made by Anthropic, so take my take with a grain of salt — I'm not exactly a neutral party. I haven't used these products myself. I don't have hands-on experience with ChatGPT's interface, Gemini's integration with Google services, or Perplexity's search flow. Anything I say is inference from what's publicly known, not firsthand comparison.

Claude accepted ChatGPT as the market leader among other AI tools due to its broad capabilities, strong voice mode feature, vast plugins/GPTs ecosystem and penchant for shipping flashy features before its rivals. As for its weaknesses, it pointed to ChatGPT agreeing too readily rather than pushing back on its users' questions and how its quality feels inconsistent across its model updates in ways that frustrate its power users.

In Gemini’s case, Claude noted that its biggest edge is its Google search engine and Google Workspace integration. Claude also brought up Gemini’s strong multimodal abilities and ability to handle long-context work. The most noteworthy weakness that was mentioned is how some users complain about its lack of a personality (it doesn’t have the strongest conversational abilities, in my opinion) in comparison to other AI tools.

To end its analysis of its three biggest AI competitors, Claude presented this statement aimed at focusing on the bigger picture of the current-day AI arms race:

These companies are trading the lead constantly — whoever's "best" shifts every few months as new models ship. Anyone (including me) who tells you one is definitively superior across the board right now is probably overselling it or hasn't checked recently. Your actual best move is checking recent independent benchmarks or just trying them on the tasks you care about, since "best" is pretty task-dependent.

Perplexity’s rebuttal

Perplexity got straight to the point when the time came for it to be as blunt as possible about its opinions on ChatGPT, Gemini, and Claude. It noted how they’re all strong across the board, but feel different in personality, reliability, and what they’re best at.

It pointed to ChatGPT’s citation consistency across encyclopedic, community and legacy editorial domains, such as Wikipedia and Reddit. The main weakness Perplexity connected to ChatGPT was how it occasionally tries to “smooth over” its knowledge gaps instead of simply saying “I don’t know.”

Gemini got a digital pat on the back for offering its users a wealth of information and integration with live Google Search data. But it also got knocked for its less-than-reliable reasoning depth and giving out answers that can feel shallow or generic.

As for Claude, Perplexity gave it high marks for offering users depth, clarity, and safety when explaining complex topics. As for its central weakness, Claude got knocked down a peg for being overly cautious or verbose with its responses. Perplexity also remarked how Claude can sometimes avoid giving direct answers.

At the end of its evaluation, this is how Perplexity summarized the other three chatbots it’s always compared to:

ChatGPT: most well-rounded and adaptable.

Gemini: strongest for up-to-date info and ecosystem integration.

Claude: strongest for deep thinking and careful writing.

If you forced a blunt summary: ChatGPT is the best generalist, Claude is the best thinker, and Gemini is the best connected.

The takeaway

I have to hand it to all four chatbots — they remained professional in their responses, gave credit where credit is due when bringing up the other AI tools’ strengths and didn’t get into a digital mud-slinging match when speaking on their rivals’ weaknesses.

Their honest examinations of each other stood out to me as a go-to guide for me when deciding what tasks to present to them from that point forward. I’m sure as time goes on, each of those AI tools will get more refined and get past their shortcomings—at least a lack of honesty isn’t among them.

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If you’ve spent any time on TikTok recently, you might have felt a strange sense of déjà vu. You’re scrolling through your For You Page, watching a creator talk about their daily routine or recount a funny story, but something about their face just feels… off.

It’s not your imagination. A sophisticated new trend is taking over social video feeds: AI video hijacking.

Unlike early deepfakes or obvious synthetic AI avatars, these videos don’t start from scratch. Fraudulent accounts, often operating as automated engagement farms, are downloading real creators’ videos, isolating their original voice audio, and reskinning the footage using AI face-swaps.

It’s video identity theft and digital puppetry rolled into one. While the technology is getting scarily realistic, the seam marks are still there if you know where to look.

Here are 5 dead giveaways that the TikTok you’re watching has been hijacked by AI.

1. The lip-sync detachment

Because the AI is trying to map a new synthetic face onto an existing audio track that was scrubbed and isolated from the original person, the audio and visual timing almost always fall out of sync. Pay close attention to plosive sounds (words starting with P, B, D, or T).

In a real video, a person’s lips press together firmly to make these sounds. In a reskinned AI video, the lips will often float open, misalign, or look slightly detached from the actual voice's cadence.

2. Lighting disconnect (face vs. body)

Pay attention to how the light hits their skin. Real-world environments have shifting, unpredictable light, whether it’s sunlight through a window, streetlights on a drive, or passing shadows. But generative AI overlays struggle to adapt to these changes in real time.

Watch the creator’s forehead and cheekbones as they move: if the light on their body shifts naturally, but their face stays frozen in the exact same lighting, you’re looking at a digital mask.

3. Blurring at the edges

AI video tools have gotten scarily good at blending synthetic faces onto real bodies, but seamless edges are still their Achilles' heel. Where does the face end and the original person begin? That border is where the software regularly fails.

Look closely at key contact points like the neck, collarbone, and hairline. You might spot weird blurring, pixel shifting where the jaw meets a shirt collar, or hair strands that vanish unnaturally into forehead skin.

The biggest giveaway happens when hands come into frame: if the creator reaches up to adjust their hair or touch their chin, the face overlay will often momentarily distort around their fingers.

4. Pupil drift and the uncanny gaze

Human eyes continuously micro-adjust to focus on a camera lens. When an AI model maps a generated face onto a real person's eye line, the pupils often struggle to lock onto the viewer.

This results in the uncanny gaze: eyes that seem to float, swim around the socket, or look slightly past the camera even when the head is facing forward. If the person looks like they’re staring at a ghost just behind your shoulder, unblinking, trust your gut.

5. Audio phasing and reverb drops

To make the stolen video work, the account owners rip the audio straight from a real creator’s existing post. But to separate that original voice from its background music or room noise, they have to run it through AI isolation software, and that cleanup process leaves distinct digital scars.

Put in headphones and listen carefully. Even though the dialogue itself sounds completely natural, because it is a real person talking, the isolation software can mangle audio quality.

Listen for a robotic, muffled tone, or dead silence between words where natural room echo, breathing, or background hiss should be.

If the video looks high quality, but the voice sounds tinny, muffled, or isolated in a silent background, you’re likely listening to ripped audio pasted onto a synthetic face.

Why this is happening, and why it’s so alarming

Beyond the immediate nuisance of TikTok Shop spam and account farming, the real issue is that creators lose all ownership of their image.

When an account steals your face, you can end up "endorsing" products you've never used, saying things you'd never agree with, or unwittingly scamming your own audience, with almost no easy way to get the content taken down quickly.

Have you stumbled across any obvious AI fakes on your feed lately? Drop a link or let me know what tipped you off in the comments.

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There’s such an abundance of apps that can be connected to most of the AI tools you regularly use.

With ChatGPT, its library of plugins covers the gamut of helping one tackle tasks aimed at productivity, creativity, developer tools, business & operations and more. Claude and Perplexity offer their own collection of “Connectors” that incorporate the direct usage of third-party tools that make your personal and professional life more manageable.

I’ve already experimented with my fair share of those plugins and Connectors—they’ve all proven to me that being able to create a music playlist based on how I’m feeling, find the sort of podcasts that appeal to my hobbies & interests and check if an email is a scam are just a sample size of the great things they can do. In the case of Google Gemini, I hold it in high regard among today’s AI tools since it's directly accessible as a side panel within Google Workspace. And I love how you connect your Workspace account to the Gemini app to accomplish tasks in a quicker, more efficient manner.

With these seven prompts, I’ve built a system that allows me to make the most of Gemini’s Workspace collaboration and be all the more productive for it.

Gemini is now a central part of my Google Workspace activities

Connecting your Google Workspace apps to Gemini is as simple as signing into your Google account, heading into your “Settings” in Gemini (it’s the gear icon at the bottom left of the screen next to your account name) and clicking on “Activity” to make sure the “Keep Activity” toggle is turned on. Then go back to your Settings, select “Connected Apps” and toggle on the option for connecting your Google Workspace apps.

With Gemini’s help, I generated 7 prompts that handle all manner of tasks I present it with across Gmail and Google Docs. And most times, I click on the neon-colored Gemini icon across both apps to open its sidebar and do my prompting from there.

Other times, I access my Gmail and Docs directly through the Gemini app by using the “@” sign to mention specific emails and documents:

• The Inbox Tamer (Gmail): Summarize this email thread into three to five short bullet points.
• The Unread Inbox Triage (Gmail): Summarize my unread emails over the last [timeframe]. Give me a bulleted list of the core updates and flag any direct questions or urgent action items I need to handle today.
• The Thread Decoder (Gmail): Review the long email thread in @Gmail with the subject "[subject line]". Give me a bulleted summary of the final consensus, and list out any remaining open questions.
• The Cross-Referencing Meeting Prep (Gmail and Docs): Look at the meeting agenda in @Docs titled "[name of document]". Then, check @Gmail for any recent updates from [colleague's name] about this project. What outstanding issues do I need to bring up in the meeting?
• The Meeting Prepper (Docs): Give me a briefing for my meeting today by summarizing the key points from this document and tell me the top questions I should be prepared to answer.
• The Brain-Dump to Structured Outline (Gmail): Take the rough notes from my email draft titled "[draft name]" in @Gmail and turn them into a structured outline for a project brief. Use clear headings for Objectives, Deliverables, and Next Steps.
• The Brutal Editor (Gemini): I need to send an email to [recipient name]. I've drafted it here: [paste draft]. Edit this to be 50% shorter, keeping only the essential information and a clear call to action. Remove conversational filler like 'I hope this finds you well.'

The takeaway

Gemini comes in clutch during those moments when I need a bit of clarification about my next assignment, meeting and actions to take from an important set of emails. It took me a while to get used to seeing that bright Gemini icon sitting atop my Gmail and Docs. But after giving Google’s AI tool an assortment of tasks, it turned out to be more of a reliable assistant than I expected. Applying those aforementioned Gemini prompts to your Gmail- and Docs-related duties should also prove equally beneficial.

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When ChatGPT first launched, most of the conversation centered on AI-generated student essays, deepfake images and the threat of automated fake news. Books, however, felt different.

As someone who reads and reviews half a dozen books a month for ReaderViews, I've always found a certain comfort in the traditional publishing process. Bringing a book to market has historically required editors, designers, proofreaders, and, most importantly, an author who actually sat down and wrote it. That barrier to entry gave books an inherent authority that standard websites and fleeting social media posts often lacked.

Then I read a recent New York Times investigation into AI-generated biographies appearing on Amazon. These included books about living public figures that were riddled with factual mistakes and seemingly produced with zero human oversight.

I wondered: Could I actually spot one in the wild? I opened Amazon and started searching.

Most of the listings looked completely normal

The most surprising part of the whole experiment was at first glance, nothing looked unusual. All the books with AI-generated content featured professional-looking covers, convincing descriptions, reasonable price points, and even star ratings. Nothing immediately screamed "AI." If I hadn't intentionally gone looking for them, I probably would have assumed they were entirely legitimate.

Once I dug a little deeper, however, the facade started to crack — and the first thing that tipped me off was the author pages. I clicked on the name behind one biography and landed on the page of someone called John Crane Miller, described as a "seasoned biographer and cultural analyst" with a stock-photo portrait. Miller had published ten biographies in a single week, all about journalists and public figures, and when Kashmir Hill left a public review on Amazon asking to speak with him, his books quietly vanished. He wasn't the only phantom.

A study by Originality.ai found entire catalogs built by authors who appeared to be fabricated identities, one of whom had published 74 books in five months on topics ranging from porn addiction to solo parenting to toxic workplaces. No single person writes like that. These weren't prolific indie authors with a strong work ethic; they were fake names attached to automated output.

Marketing copy was a dead giveaway

Blurb after blurb leaned on the same broad promises and eerily familiar phrasing — "delve into," "comprehensive guide," "unlock the secrets of" — without ever explaining what made the book worth reading over any other book on the same topic.

After half a dozen of these, I could practically predict the next sentence before I read it. The marketing copy wasn't just generic; it was interchangeable, as if the same prompt had been run through the same model with only the subject swapped out.

The biographies were the most troubling category, and the wave of books about tech journalist Kara Swisher illustrated why. Multiple unauthorized biographies of Swisher appeared on Amazon around the release of her memoir "Burn Book," written by authors with no apparent journalism credentials and no indication they had ever spoken to Swisher or anyone in her orbit.

Political scientist Ian Bremmer encountered the same phenomenon: books bearing his name as a subject, produced without his involvement, that simply scraped and summarized what was already freely available online. This is, of course, exactly what chatbots are built to do, that is, synthesize existing information into fluent, confident-sounding prose. The result is a product that looks and feels like a real book but contributes nothing a reader couldn't get from the source material itself.

Beyond books

Substack recently launched an AI detection feature in partnership with a company called Pangram, letting readers scan any post to see an estimate of how much was written by a human versus generated by AI.

Substack CEO Chris Best framed it as a way to keep the platform from becoming "like LinkedIn," overrun with hollow AI content, but even Substack acknowledges the tool isn't perfect. The Atlantic found that Pangram's accuracy is far from bulletproof, and critics worry about false positives flagging legitimate human writers.

Still, the fact that a major publishing platform felt compelled to build this feature at all says something about how urgent the problem has become. Amazon, for its part, has no equivalent.

The takeaway

As someone who absolutely loves to read, I found this to be a very interesting experiment. My takeaway is that now, instead of trusting a listing at face value, I take a few extra minutes to look up the author outside of Amazon to see if they have a credible publishing history elsewhere, and I specifically hunt down professional reviews rather than relying on standard star ratings.

I always preview the sample text to check if the writing feels robotic or relies on repetitive phrasing, and for nonfiction, I actively look for evidence of real human interviews and original citations. None of these steps individually guarantee a book was written by a human, but together, they make it much easier to separate thoughtful, researched work from automated content designed just to game search results.

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All the best streaming services use AI in some form or another to serve up recommendations for what to watch, but Prime Video's looking to go all in. According to a Reuters report this week, Jeff Bezos is personally pushing Amazon’s Prime Video executives toward a major app redesign to turn the streaming platform into a marquee showcase for Amazon's multi-billion-dollar investments in AI technology for its 200+ million active viewers.

Internally codenamed Project Lighthouse, the effort is just one piece of Amazon's companywide AI efforts to compete against the likes of OpenAI and Anthropic. Lighthouse would comb through a subscriber's viewing preferences, using AI for improved film and TV recommendations and to respond to spoken requests, one person with knowledge of the project told Reuters. The final redesign is still in the works, but it could drastically change your home page and how you find what to watch next. We've reached out to Amazon for comment, and will update this story once we hear back.

Following a tense internal presentation last fall, Bezos rejected earlier redesign proposals from Prime Video head Mike Hopkins, expressing frustration that they did not go far enough in leveraging generative AI for improved personalization. The team scrapped those plans and started fresh under Global Head of Design Kam Keshmiri. So far this year, the company's dropped $200 billion in capital expenditures, mostly related to developing AI, Reuters reports.

Potential changes with Prime Video's AI redesign

Again, Prime Video's AI overhaul is far from finalized, but one part of the redesign under consideration would introduce AI-powered content tiles that surface curated viewing suggestions, such as "1980s action movies" or "Christmas rom-coms," three people familiar with the discussions told Reuters. Netflix employs similar categories to help direct viewers find other movies and shows in genres they gravitate toward.

The overhaul could also reshape how movies and TV shows are promoted on Prime Video. Right now, studios pay for premium placement on the service's homepage alongside recommendations generated by Amazon's algorithms, a practice that's standard among streaming platforms.

Amazon has reportedly already begun testing early versions of the redesign with a limited group of users. However, the final product could still change based on tester feedback, budget considerations, or other internal factors. The redesigned interface would still include the standard search bar, along with a dedicated area at the top of the homepage to spotlight new releases and live events, including Amazon's exclusive "Thursday Night Football" broadcasts.

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Most ChatGPT users have gotten accustomed to using AI to help with simple questions that are too nuanced for Google. But, ChatGPT Work is meant to be used differently.

After spending time with it, I realized the biggest shift with OpenAI's new feature within the interface, is that it does so much more than just answer questions — it does entire tasks!

Once I tried it, I saw the difference was truly unique. Instead of bouncing back and forth with dozens of follow-up prompts, I found myself giving ChatGPT Work a goal and letting it figure out the steps.

Here are the seven prompts I've found myself coming back to the most.

1. Be my chief of staff for this project

Prompt: Act as my chief of staff for this project. Review everything I've shared, identify what still needs to be done, organize the work into priorities, and only come back to me when you need a decision that requires my input.

This has become my favorite way to start a new project. Instead of asking ChatGPT what I should do next, I ask it to build the roadmap. It identifies missing information, suggests a logical order for tasks and keeps the project moving without waiting for me to think of the next prompt.

It feels much closer to working with an assistant than chatting with an AI. It works especially for those times when you're trying to get a project off the ground (alone without a team) and need support. ChatGPT Work seems to "get it" much better than a simple chatbot.

2. Read everything and tell me what actually matters

Prompt: Review every document in this folder. Identify the key points, flag anything important or contradictory, and create one summary that I can read in five minutes.

We've all been handed a folder full of PDFs, meeting notes or research documents with the goal of knowing everything inside as quickly as possible. Normally I'd summarize each one separately before trying to connect the dots myself. ChatGPT Work can tackle the entire collection and give me a single report that highlights what matters most.

That alone can save an enormous amount of time. It's a lot like Gemini Notebooks, formally NotebookLM, but if I'm in ChatGPT platform already, it makes sense not to switch out for something like this.

3. Compare these options like you're spending your own money

Prompt: Compare these products using professional reviews, user feedback, specifications, long-term ownership costs and reliability. Recommend the one you would personally buy and explain why.

I don't want a list of specs anymore like ChatGPT has done. Instead, I want recommendations that come from weighing real tradeoffs. That could mean support whether I'm looking at laptops or planning a weekend getaway.

4. Own my inbox

Prompt: Go through my email, group similar messages together, identify anything urgent, draft replies where appropriate and create a short action list for anything that still needs my attention.

Email is one of those jobs that somehow expands to fill whatever time you give it. Instead of processing messages one by one, I let ChatGPT organize everything first. By the time I'm looking at my inbox, I already know what's urgent, what's waiting and what can safely be ignored. I can also ask ChatGPT questions about my inbox, like, "Where is the Amazon receipt from earlier this month," rather than trying to figure it out myself.

5. Turn my messy notes into something useful

Prompt: Take these notes, organize them into logical sections, identify any missing information and produce a polished document that's ready to share.

My notes are so messy that even I'll take a look and wonder what I was trying to say. Whether they are voice memos or written in my Notes app, they are random

Sometimes they're voice memos. Sometimes they're random thoughts copied from three different apps.

Instead of spending an hour cleaning everything up myself, I hand the entire mess to ChatGPT Work and let it build something coherent.

6. Keep watching this for me

Prompt: Monitor this [topic] and let me know only when something significant changes. Ignore routine updates unless they affect my decision.

This is where ChatGPT Work realls feels different. I don't have to repeatedly check back on something like a website update or an email or news story. Instead, I can hand off the monitoring and focus on something else. It removes a surprising amount of mental overhead.

7. Finish the project—not just the next step

Prompt: My goal is to finish this project. Break it into manageable stages, complete everything you can independently and ask me for input only when you absolutely need it.

This prompt changed how I think about how to use AI. Rather than asking "what comes next?" the AI takes care of it for me. I hand over the entire assignment. The result is fewer interruptions, fewer prompts and a workflow that feels much more natural. This is great for time-consuming administrative takes because it allows me to focus on more important or creative projects.

The takeaway

OpenAI is constantly updating its models and what's possible for the platform itself. If you've been ignoring ChatGPT Work or wondering why you would even need it, I encouarge you to give it a try.

Traditional chatbot prompts tend to be small such as summarize this article, explain this concept or write this email. But ChatGPT Work shines when you give it ownership instead.

The more responsibility you hand over, the more useful it becomes. Rather than asking it to solve one problem at a time, ask it to take responsibility for the whole job. That's the mental shift that finally made it click for me — and once I started using it that way, it changed how I work.

Let me know in the comments if you've tried and what you think.

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I recognize that not everyone is enamored with the idea of today’s usage and reliance on AI.

Far too often, you’ll scroll through your X timeline and spot someone asking Grok “Is this true?” instead of looking up the information they need on their own. And I wouldn't be surprised to hear about an older relative sharing a picture or video with you that’s clearly AI-generated, but they can’t seem to recognize the counterfeit content.

But there are a bunch of cases where AI is more helpful to the average person than harmful, especially when prompting chatbots to simplify complex topics, produce productivity routines, map out easy-to-follow workout plans, etc.

In many ways, AI is implemented into a lot of the gadgets and systems you use every day. And you might be working with those AI-powered features without even realizing it. From enhancing the pictures on your smartphone to improved visual clarity for online meeting tools, AI makes several parts of your life easier while working in the background.

Enhancing photos on your smartphone

I’m sure you snap dozens of photos when you’re out and about. iPhones and Android-powered smartphones both employ AI to perform several corrective actions to make your shots look even better. For instance, the “Portraits in Photo Mode” feature on iPhones relies on machine learning algorithms to automatically detect a person, cat or dog that stands out in the frame of a picture. AI is also used to automatically improve the lighting and colors in your pictures, reduce the blur effect caused by camera shake and improve your photos’ visual output in low-light and nighttime settings.

Autocorrecting your mistakes and giving you the best search results

Whenever you’re typing up something in a search bar, text or email, you’ll notice features like Autocorrect and predictive typing attempting to fix your typos and recommend the words you’re most likely going to type in next. This is another form of AI that adapts to your writing style and offers you the suggestions it thinks you’re looking for. That common error of typing out “teh” in a text and having it quickly fixed to appear as “the” is a common fix, courtesy of AI.

Also, every time you type into a search bar like Google or Bing, AI comes into play as it analyzes what you’re writing, auto-completes words, fixes typos and ranks the best results for whatever you’re looking for. AI also improves your search engine experience by blocking out obvious spam links and giving you personalized recommendations based on your search habits.

Analyzing your streaming service habits to make better suggestions

Video/music streaming services and social media apps, such as Netflix, Spotify, YouTube and TikTok, use AI in the form of recommendation algorithms. Those algorithms are used to predict what video you’ll end up watching next, what song you’ll end up listening to next, what movie you’ll queue up next and the sort of content that will keep you engaged. Many factors, such as your watch history, clicks, likes, searches, skips and the total time you spend watching a video, play a huge role in helping AI highlight the next collection of videos it thinks you will like on your YouTube homepage and on a video’s sidebar.

Blocking spam from your inbox

Thankfully, the days of obvious scams invading your inbox are a thing of the past. The email providers you use, such as Gmail, Outlook, and Yahoo, protect you from obvious cases of spam messages by using AI to identify fake invoices, malware, suspicious senders and phishing attempts. AI taps into pattern recognition to scan a message to identify its overall context, sentence structure and tone to identify its validity before letting it go to your inbox or get dumped in your Spam folder.

Making your navigation apps extra reliable

I’m sure you don’t miss the days of printing out directions via MapQuest before making the long journey somewhere on the open road. Navigation apps such as Google Maps and Waze make traveling anywhere on foot or by car a less headache-inducing process thanks to AI. Machine learning algorithms analyze historical traffic trends and live vehicle speeds to make traffic predictions, for instance. That form of AI is also used to find you the best routes, suggest alternate routes, estimate arrival times to your destination and detect nearby accidents.

Assisting you when you're translating different languages

For speech-to-text programs, translation tools and digital assistants (Siri & Alexa immediately come to mind in that last case), AI is used to help them produce the best results possible. In some of the most used language translators, such as Google Translate and DeepL Translate, AI plays a huge part in their processes via deep learning and neural machine translation to comprehend context, process what’s being said and convert text between different languages. Even when your voicemail is transcribed and live text captions are applied to a video, AI is powering both actions.

Bottom line

You may not use the likes of ChatGPT, Gemini, Claude and Perplexity to handle your day-to-day tasks.

You might scoff at the use of generative AI to create art and videos. And you wouldn’t dare ask Grok to explain something you’d feel much better learning about yourself via a good old-fashioned Google search. But without you even grasping the concept of adding AI to your life, it’s already there working behind the scenes to make your life just a little bit easier.

Whether it's easier road navigation, cleaner-looking photos or viewing/listening recommendations, AI works hard to give you what you’re looking for and more.

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If you've been anywhere near social media recently, you've likely seen Jimothy. The unusually round, compact raccoon took the internet by storm after Kiana Hall, a 33-year-old marketing specialist in Seattle, filmed him near the Ballard Goodwill on July 13. Hall initially thought she was looking at a cat under a parked car — until the animal turned around and revealed a racoon with short spine syndrome, a disorder that affects some animals. She posted the clip to Instagram the next day, naming him Jimothy because, as she put it, "he looked like a Jimothy."

With his seemingly missing neck and spherical shape, he looks like a creature straight out of a video game or a cryptid sighting — and as of July 18, the video had racked up over 7 million views.

Jimothy is 100% real.

How Jimothy became a cultural explosion

Before we get to what's fake, it's worth appreciating what's real — because the real-world response has been nearly as surreal as the AI-generated content.

Within days of going viral, Jimothy inspired a mural, tattoos, fan art, and a dedicated following on Reddit's r/Seattle, which saw 29 million views from July 16 to 22 alone.

The Seattle Mariners brought a Jimothy mascot into their beloved Salmon Run race at T-Mobile Park — and he won, naturally, sparking what fans are calling a rally effect after the team rattled off three straight wins.

Google even added an Easter egg. Just search his name and an animated Jimothy scampers across your screen; it's been triggered over 5 million times. He's received an honorary degree from the University of Washington, recognition from the Seattle City Council, and even a shout-out from the White House.

The AI spin

But, what's not real is almost everything you are seeing him do online.

As soon as the original clip went viral in mid-July, creatives, both human and AI took to the internet. Since Jimothy's actual appearance is already somewhat surreal, he has become the perfect subject for AI-powered content. People are running his image through generative models like Gemini's Veo and Grok to create increasingly absurd clips, placing him in fantasy landscapes, having him act out cinematic scenes or reimagining him in stylized digital art.

The gaming world has been especially enthusiastic. Blizzard Entertainment posted a tribute rendering of Jimothy in the style of "World of Warcraft." Jagex did the same for "Old School RuneScape" and D&D Beyond released an official stat block so players can drop him into their tabletop campaigns. A digital Jimothy even made an appearance in Roku City.

These AI-generated tributes are essentially a celebration of meme culture, but many of us (myself included) were duped. The internet took a genuinely fascinating wild animal and used every creative tool available, from generative AI to game engines to old-fashioned fan art, to build a cinematic universe around him.

Why we keep falling for it

The reason these artificial clips are tricking so many people because Jimothy is the perfect subject for digital deception. His real-world proportions already trigger the uncanny valley effect; when a living animal looks like a glitch in the matrix, it naturally lowers our skepticism for actual CGI.

Combine that biological reality with the way we consume content, rapidly scrolling on phones where platform video compression smooths out the telltale visual artifacts of AI generation, and it’s no wonder people are struggling to separate the real Ballard neighborhood from a prompted illusion.

So, yes, the scrappy hometown hero from Seattle is real. But if you see him riding a dragon, casting a spell or winning a raid boss fight in Azeroth, that's just the internet doing what it does best. And in this case, doing it faster and more convincingly than ever before, thanks to generative AI.

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When I logged into ChatGPT last week to lay out a cluster of odd, frustrating symptoms, irregular cycles, sudden night sweats, subtle mood swings and exhaustion, I was looking for help to relieve the symptoms. What I got instead was a confident, direct diagnosis: Congratulations, you’re likely in your first trimester!

There was just one glaring problem: I am absolutely not pregnant. My husband has had a vasectomy and I'm in the thick of perimenopause. But the sheer certainty with which the AI delivered its verdict left me stunned. If I hadn't known my own body — or if I had been younger, anxious or facing a high-stakes health decision — that piece of advice could have derailed my day, sent me down an emotional rabbit hole, or led to unnecessary medical testing.

My experience isn't an isolated quirk. ChatGPT Health launched Thursday, promising U.S. users can now securely connect their own health info to "better understand and navigate your health," it's important to keep in mind that AI is not a replacement for a human doctor.

Landmark lawsuit filed

Just this week, The New York Times reported on a landmark lawsuit filed against OpenAI by Scott Winters, a Florida pastor who claims ChatGPT’s medical advice nearly cost him his life. After consulting the chatbot about severe dizziness and pelvic pain, the AI reassured him his symptoms were "nothing dangerous," advising him to remain off his feet in a recliner.

Weeks later, he was rushed to the ICU with a massive, life-threatening pulmonary embolism, a condition his doctors noted was exacerbated by the prolonged immobility the AI recommended.

While my misdiagnosis was a false positive rather than a medical emergency, both cases highlight the exact same fundamental danger: large language models are engineered to sound authoritative, not to be right.

Here is why relying on AI for medical advice is a risky gamble and why we need to change how we interact with these tools.

1. AI pattern-matches words, not physiology

Simply put: AI is not a doctor and obviously doesn't "know" medicine. It operates on statistical probability — predicting the next most likely word based on its training data.

When you feed a chatbot a list of symptoms like missed periods, fatigue and hormonal shifts, its algorithms cross-reference billions of text snippets. Because pregnancy is heavily discussed online in association with those symptoms, the AI defaults to the most statistically common narrative in its dataset. It lacks the ability to account for age context, subtle bloodwork markers or the complex, non-linear realities of perimenopause.

And, that's just pregnancy! There are plenty of symptoms for thousands of ailments from dehydration to serious medical emergencies. Users treating ChatGPT as a doctor reminds me of the popularity of WebMD.

2. "Sycophancy" and echo chambers

One of the most dangerous traits of conversational AI is sycophancy — the tendency of the model to mirror the user's language, tone and unstated assumptions.

If your prompt leans even slightly toward a specific fear or curiosity, the AI is prone to confirming it rather than challenging it. In Mr. Winters’ lawsuit, the complaint notes how the chatbot leaned into his personal spiritual language to offer comforting, yet wildly inaccurate, medical reassurances.

In my case, because I asked if hormonal shifts could explain my symptoms, the AI leaped straight to the most dramatic hormonal shift in its catalog: pregnancy.

3. The fallacy of the 'authoritative tone'

When a human doctor isn't sure about a diagnosis, they use qualified language, order lab work or refer you to a specialist.

When an AI hallucinates a diagnosis, it presents it with the calm, unflinching confidence of a board-certified physician. It doesn't hesitate, nor does it express internal doubt. That authoritative tone creates a false sense of security, making it dangerously easy for users to bypass real medical care or ignore warning signs.

The takeaway

Large language models can be helpful brainstorming tools for organizing your thoughts before an appointment or summarizing complex medical jargon. But they are not diagnostic tools. They do not have clinical judgment, they cannot order blood tests and they cannot feel the pulse of a human patient.

If you’re experiencing unexpected symptoms, skip the prompt box. Trust your body, listen to licensed professionals and leave the medical diagnoses to human beings.

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I've been impressed with Samsung's launch of a new foldable every summer, but have held on to my iPhone because my thought was always, "That's cool, but why wouldn't I just use my laptop?"

Even after reviewing plenty of AI features over the last couple of years, I still couldn't justify carrying a phone that unfolded into a small tablet. I really didn't feel as though I had a purpose for it. But, Galaxy Unpacked finally changed my mind.

Oddly enough, it wasn't the thinner design that caught my attention or the cameras tht stood out to me. This year it was the ability to use Gemini Notebook (formally NotebookLM) on the phone.

When Google announced that Gemini Notebook will come preinstalled on Samsung's new Galaxy Z Fold lineup, alongside a broader push to make Gemini work across dozens of apps, I was sold. For the first time, I looked at a foldable and thought: "That's actually the device this was built for."

Gemini Notebook feels cramped on a normal phone

I already use Gemini Notebook almost every day. It's actually one of my very favorite AI tools. It lets me dump messy notes, PDFs, YouTube videos, research papers and random thoughts into one place before asking questions or generating summaries.

It's incredible for professionals as well as students who want to stay organized and prepared. But as much as I love it, using it on my iPhone hasn't been ideal. The screen makes a difference with Gemini Notebooks becuase it's not really a chatbot. It's more like a workspace.

Because of the nature of the platform, I want to see my sources while asking questions. And I need to be able to scroll through notes without constantly switching views. Sometimes I want an AI-generated study guide on one side and the original document on the other. I didn't realize it, but having the ability to do that is what was keeping me from successfully using Gemini Notebooks on mobile. On a regular smartphone, that experience feels squeezed into a screen that was never designed for it.

A foldable finally has room to breathe

Watching Google's demos during Unpacked, something clicked. Open the Fold and suddenly there's enough space to treat Notebook like an actual research desk instead of another messaging app. Using a foldable phone would make reading a research paper so much easier, especially while Gemini explains confusing sections on the other side.

Or, even planning a vacation with hotel websites open alongside Notebook as it organizes my itinerary. I could see it useful for comparing recipes, watching a cooking video on one side while asking Gemini questions on the other without jumping between apps or trying to zoom in.

That's the kind of multitasking foldables have always promised, but I've ignored until now. AI finally gives that extra space a real purpose.

AI is giving foldables a reason to exist

Samsung has spent years trying to convince people that foldables are productivity devices, but I wasn't buying it even though the hardware kept improving. But this year's announcement made all the difference to me.

Now that Gemini can now automate tasks across more than 40 apps, it makes the larger screen useful for workflows that previously required bouncing between windows. Instead of simply opening multiple apps, the phone becomes a place where AI helps connect them.

Final thoughts

I know Foldables aren't for everyone. They are expensive and much bulkier than standard phones. Most people don't need an 8-inch display for checking emails or scrolling social media.

But, I can see Foldables being a real game changer for those who spend their day writing, studying, planning or researching. I think that's the audience Samsung has been searching for all along, and Gemini has sealed the deal for me.

For the first time, I didn't leave Galaxy Unpacked thinking about the hardware, instead, I thought about how I would actually use the phone in real life. For someone who uses Gemini Notebooks for just about everything, I'm looking forward to taking advantage of AI that works alongside me. The extra screen suddenly feels like a necessity now that Gemini is baked in.

I can’t help but spend far too many hours scouring the web for answers about the world’s biggest mysteries.

If you catch me on a Saturday night being a loser sitting inside my dark room while the illuminating light of my laptop makes me visible, then I’m most likely diving into conspiracy theories. My fascination with the wild stories behind unsolved cases is strong. The truth behind what’s really stationed at Area 51, why so many ships & planes vanish in the Bermuda Triangle and whatever happened to D.B. Cooper (the man who successfully hijacked a Boeing 727) fascinates me.

Another unsolved case that I’ll never get tired of reading about is Amelia Earhart’s disappearance. As an American icon best known for her accomplishments in the world of aviation, a holiday was enacted in her honor (Amelia Earhart Day). And this year, I wanted to try something different during my latest deep dive into what led to the vanishing of her and her navigator Fred Noonan.

After asking four chatbots what they think really happened to Earhart, I noticed that one prevailing theory stood out above the rest of the wild theories connected to her disappearance.

ChatGPT and Gemini’s answers

I presented the same question to ChatGPT, Gemini, Claude and Perplexity to get my latest conspiracy theory study session underway: “Based on all the conspiracy theories surrounding the mysterious disappearance of Amelia Earhart, what do you think really happened to her?”

ChatGPT’s explanation got straight to the point: The short answer is: the most likely explanation is also the least sensational one. Based on the available evidence, I think Amelia Earhart and Fred Noonan most likely became lost after failing to locate Howland Island, ran out of fuel, and crashed into the Pacific Ocean.

The chatbot pointed to its conclusion as the one that’s accepted by most aviation historians and investigators, for various reasons. Those reasons include no verified post-disappearance radio transmissions being found, the U.S. Navy being unable to find anything during their search and how modern analyses point to Earhart & Noonan having very little fuel remaining during their excursion. Some of the other theories ChatGPT pointed out to explain this mystery included Earhart & Noonan landing on Nikumaroro then dying as castaways, crashing somewhere else entirely (New Britain, for example), getting captured by Japan and a possible government cover-up.

As for Gemini, it made mention of the same result ChatGPT reached: When you strip away the decades of folklore, sensationalism, and cinematic conspiracies, the historical and scientific consensus points to one sobering reality: Amelia Earhart and her navigator, Fred Noonan, simply ran out of fuel and crashed into the Pacific Ocean.

Gemini mentioned something about a sonar update connected to the Earhart mystery that occurred in 2024, which was a bit of info I never knew about before:

The ocean floor remains the primary search zone. In early 2024, ocean exploration company Deep Sea Vision made global headlines when they captured a sonar image of a plane-shaped anomaly roughly 100 miles from Howland Island. However, when the team returned to the site with high-resolution equipment in November 2024, they confirmed the anomaly was merely a natural rock formation. The hunt in the deep sea continues.

Claude and Perplexity’s responses

When presented with my Earhart prompt, Claude gave me the answer I was expecting after reading ChatGPT and Gemini’s answers:

My honest take: the simplest explanation — she ran out of fuel and went down in the ocean — fits the available evidence best. The Nikumaroro theory is the most seriously debated alternative among researchers, but it remains unproven. The more elaborate theories (capture, cover-up) tend to rely on speculation rather than verifiable evidence.

While Claude also mentioned conspiracy theorists bringing up Earhart secretly coming back to the U.S under a new name and her possibly conducting a covert spy mission for the U.S. government, the chatbot made sure to note that those theories have no credible evidence connected to them and are largely dismissed by researchers & historians.

When it was finally Perplexity’s turn to answer my question, it gave me the answer that stood out as the prevailing theory among all four chatbots: If I had to pick one explanation, I’d say a navigation or radio problem led to a fuel-starved ditching near Howland Island, followed by loss in the ocean, with the Nikumaroro castaway theory as the most plausible alternative.

Perplexity pointed to its answer being the prevailing mainstream view from most folks who’ve looked into Earhart’s story, while the theory tied to her becoming a “castaway” has drawn some support due to the data tied to radio-distress reports from Earhart and artifacts linked to Nikumaroro Island (the place where some theorize Earhart and Noonan crashed, then lived as castaways).

Final thoughts

Coming out of this latest chatbot Q&A meeting, I left it knowing that the truth is simple and not covered in any sort of mind-bending mystery.

Earhart and Noonan met their untimely end due to running out of fuel while in the middle of another bout of flight navigation. Earhart will forever be regarded as an aviation icon, as she made history by being the first female passenger to cross the Atlantic by airplane and later crossing it alone while facing harsh weather conditions.

Someday, I hope we get a definite breakdown of her disappearance and the physical evidence everyone needs to back up everything we’ve heard about it thus far. Just like most folks, ChatGPT, Gemini, Claude and Perplexity know where the real truth lies.

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It’s getting harder to ignore the widening silicon inequality gap in the tech world right now thanks to RAMageddon. On one side, you have consumer PC gamers dealing with overpriced PC components, wondering if a standard 8-core CPU and 16GB of VRAM is enough to handle modern AAA games. On the other side, you have enterprise AI machines operating in a whole other universe of compute.

During its Advancing AI 2026 event, AMD announced an enormous 256-core CPU alongside the AMD Helios Rackscale solution — a single server cabinet packing a staggering 31 terabytes of high-bandwidth VRAM. No, these numbers are not typos!

Naturally, you can’t walk into your local Micro Center and buy one of these. Don’t get me wrong, the numbers are cool, but in a time where I might have to donate a kidney to afford a decent amount of RAM, it leaves a bad taste to see 31,000 gigabytes of it being (potentially) used to generate low-quality AI videos.

Here's what you need to know about AMD's enterprise CPU and server rack, along with how they stack up against a popular consumer GPU.

The 256-Core CPU

To put things into perspective, let’s consider the best gaming PCs. A high-end gaming CPU like the Ryzen 9 9950X tops out at 16 cores, which is plenty for running Cyberpunk 2077 or editing 4K videos.

Conversely, AMD’s new 6th Gen EPYC 9006 Series (SP7) server processor packs up to 256 cores and 512 threads onto a single chip, with high-frequency variants like the EPYC 9006X pushing boost speeds up to 5.15GHz. That’s 16 times the core count of a flagship desktop processor. EPYC would be an entire LAN party on one chip.

So, what’s the need to have 256 cores on a single die? AMD built these chips specifically to handle the massive overhead of agentic AI. Modern AI agents have to run code in isolated sandboxes, manage huge system memory states, and coordinate heavy feeds. This all takes a massive amount of computing power and is a far cry from our gaming PCs having to render ray-traced shadows.

Helios Rackscale

If you thought the CPU numbers sound wild, the RAM numbers are even more mind-blowing. The centerpiece of AMD’s announcement is the Helios Rackscale solution, which is an open-architecture AI system.

Inside a single server rack sit 18 compute trays holding a total of 72 AMD Instinct MI455X GPUs. Combined, this single cabinet delivers 31 terabytes (31,000 GB) of HBM4 VRAM with a whopping 1.7 petabytes per second of memory bandwidth.

For context, 31TB of VRAM is equivalent to roughly 1,937 Nvidia RTX 5070 Ti graphics cards chained together!

These are insane numbers when compared to what a typical gaming GPU is packing. It’s definitely impressive, but at the same time, that’s offset by the knowledge that a good chunk of the world’s RAM is going to server racks like this.

Helios Rack vs. RTX 5070 Ti

To give you an understanding of how monstrous a single Helios rack is, let’s compare its raw specs against one of the most popular upper-midrange consumer GPUs out now: The Nvidia RTX 5070 Ti (16GB GDDR7).

Looking at it through this lens, a single server rack packs the raw memory bandwidth of nearly 1,900 desktop PCs working in unison! This is a whole other level of computing, my friends.

Bottom line

AMD is certainly flexing its tech muscles with this announcement. However, there’s a sobering reality behind these staggering numbers. Seeing a single server rack hog 31 terabytes of high-bandwidth memory shows exactly where the global supply chain is funneling its resources. Namely, it’s all being swallowed by the AI boom (or bubble — however you see it). As a lifelong gamer, it hurts being pushed to the side.

Even if it stings, we can’t fault AMD for choosing to invest in more lucrative enterprise projects like this rather than in the average consumer. So, the next time you find yourself debating whether to pay a premium for a 16GB graphics card over an 8GB model, or wondering why PC component prices keep climbing, you now have a better idea of why.

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Prime Video could be getting an AI overhaul at the behest of Amazon founder Jeff Bezos, according to a new report. The redesign would put AI front and center under a new project allegedly dubbed Lighthouse.

Reuters reports that the push from Bezos is meant as a way for Amazon to utilize its massive investments in AI and "elevate the company's stature in artificial intelligence." This comes as other investments, including improving the Alexa voice assistant, have provided mixed results and ongoing losses.

Bezos was "displeased" with a Prime Video presentation last fall where AI was not highlighted. The Lighthouse project was born out of this meeting.

What does Lighthouse add to Prime Video?

Bezos is said to be personally involved in the overhaul, an unusual step considering he relinquished the CEO title in 2021 to focus on the Washington Post and his spaceflight company Blue Origin.

Per Reuters, Lighthouse would add a slew of new features that would use AI to improve film and TV show recommendations. This would be done by having the AI learn customer preferences and respond to spoken requests.

A homepage redesign is part of the project, but it's not finalized, so it's not known how it would look yet.

However, it was suggested that it could include AI-driven titles with viewing suggestions like "Christmas rom-coms" or "action movies from the 1980s." Reportedly, a current version doesn't include text-heavy titles, so that even that appears to still be in the air.

Programs and live events like Thursday Night Football would still be promoted in the upper portion of the platform alongside the traditional search bar.

Amazon is also supposedly attempting to integrate Alexa into Prime Video's search function as part of the redesign. Most recently, Alexa was overhauled into a generative AI version last year and integrated into the Amazon shopping platform earlier this year.

Where Prime Video stands

Amazon last gave Prime Video a massive update in July of 2024 that streamlined content curation and added AI recommendations.

The most recent Nielsen data from 2025 has Prime Video in a distant eighth place in TV viewing share behind YouTube, Netflix and Disney+ at 3.9% of viewers. Reuters reports that it's bumped up to 4.2% this year, though still behind Netflix and Disney.

An AI overhaul could be a way for the company to utilize both its artificial intelligence investments and increase viewership with more personalized recommendations.

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Elon Musk has never been one to shy away from ambitious promises, and his latest claim may be one of his boldest yet. In a recent post on X, the xAI founder said Grok is working on a full-length, AI-generated adaptation of "The Odyssey" that he described as "historically accurate."

It's a bold claim, for sure. AI video tools like Runway Gen-3 and Luma Dream Machine have already shown they can produce impressive short clips, but creating a coherent feature-length film is a much bigger challenge. If Musk's vision becomes reality, it would push AI video well beyond the short demonstrations we've seen so far.

Here's what we know — and why Musk's choice of the phrase "historically accurate" has sparked discussion.

The AI race heads to Hollywood

Until now, Grok has been best known as the chatbot built into X. An AI-generated movie would represent a major expansion of xAI's ambitions, suggesting the company wants to compete in AI video generation.

The choice of "The Odyssey" is particularly ambitious. Homer's epic follows Odysseus on his long journey home after the Trojan War, combining ancient Greek settings with legendary creatures, gods and mythological events. Re-creating that story would require AI to maintain consistent characters, environments and visual style across thousands of shots — something today's video models still struggle to do reliably.

Musk's description of the film as "historically accurate" also appears to be a response to the recent debate surrounding Christopher Nolan's adaptation of "The Odyssey," which grossed more than $300 million in its opening weekend.

Some of the film's casting choices — such as Academy Award-winner Lupita Nyong'o as Helen of Troy and Elliot Page as Sinon — sparked online arguments from right-wing commentators over whether modern adaptations should strictly follow Homer's descriptions of key characters. Musk was among those criticizing what he saw as departures from the original text.

At the same time, "The Odyssey" isn't a historical record. It's an ancient Greek epic that blends elements of the Bronze Age with mythology, including gods, monsters and supernatural events. So when Musk talks about 'historical accuracy,' he's likely referring to a faithful interpretation of Homer's descriptions and the story's ancient Greek setting, rather than suggesting the events themselves literally happened.

While AI can already generate remarkably realistic scenes lasting a few seconds, maintaining continuity across an entire feature film remains one of the industry's biggest technical hurdles.

What does 'historically accurate' actually mean?

Musk's choice of words doesn't appear to be accidental. Christopher Nolan's upcoming adaptation of "The Odyssey" has been at the center of online debate over several casting decisions, particularly the casting of Lupita Nyong'o. Critics, including Musk, argued that changing the appearance of mythological characters departed from Homer's descriptions, while others countered that "The Odyssey" is a work of mythology rather than literal history and has been reinterpreted countless times over the centuries.

The debate quickly expanded beyond the film itself, becoming part of a broader cultural argument over historical representation, artistic freedom and diversity in modern adaptations. Musk weighed in multiple times on X, criticizing what he viewed as unnecessary departures from the original text.

Against that backdrop, his promise that Grok will create a "historically accurate" version of "The Odyssey" looks more like a statement about how he believes the story should be portrayed.

Can Grok actually pull it off?

As with many Musk announcements, it's worth treating both the timeline and the scope of the project with some caution. Producing a feature-length movie isn't just about generating convincing visuals. It also requires a cohesive screenplay, believable dialogue, voice performances, music, editing and scene-to-scene continuity.

Musk hasn't shared many technical details about how Grok would handle those challenges, and xAI has yet to demonstrate a publicly available system capable of generating a full-length film.

Still, the announcement highlights how quickly AI video is evolving. Just a few years ago, generating even a few seconds of realistic footage seemed out of reach. Now, companies are openly talking about feature-length productions.

Whether Grok ultimately delivers on Musk's promise remains to be seen. But if it can produce a watchable, coherent feature-length film rather than a collection of impressive clips, it would represent one of the biggest milestones AI video has reached so far.

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Microsoft is reducing free features for users. Microsoft Whiteboard now requires you to have a Microsoft Business account if you want to continue using it; the meeting preparation feature embedded in Microsoft Outlook asks you to purchase a Microsoft 365 Copilot license and Copilot Podcasts are being discontinued altogether. Now another feature that was once free of charge is being taken away from Microsoft users and replaced by a paid option.

The Deep Research feature, once available at no extra cost to Microsoft Copilot users, is now being retired, starting August 18, 2026. And after it’s gone, you’ll be required to get a Microsoft 365 Premium subscription to create the reports and analyses you’re used to doing with Copilot with the all-new Researcher AI tool.

While your previously generated Deep Research content won’t be deleted and will be accessible through Researcher, it’s a bit of a bummer to know that you’ll only be able to get back to it via a required payment.

If this news disappoints you as much as it did for me, then consider giving these alternative AI tools a try if you’re looking for more ways to conduct your research.

Try out these free options to continue generating detailed reports

Perplexity stands out as one of the top options that can fulfill all your Copilot Deep Research needs. Since its biggest selling point is backing up its data via valid citations and easily verifiable claims, you can rely on its real-time web search to get the fast results you’re looking for. Conducting everyday research on general news, products and academics should work just fine if you consider using Perplexity’s free tier.

Claude is one of the strongest AI analysts you can utilize—it’s capable of generating long-form explanations, providing you with legit citations and offers “Connectors” such as PubMed, bioRxiv and Consensus that act as research databases.

Google Gemini taps into all the latest information injected into Google Search to analyze and synthesize all the data you’re looking for from multiple webpages. Researching all manner of topics through Gemini is another free AI research tool alternative worth considering as well. Gemini’s Google Workspace integration is also great if you’re looking to export your deep research reports to Google Docs or download as a PDF.

Gemini Notebook (formerly known as NotebookLM) is an amazing AI research tool as it allows you to upload your own sources to create your own study material. Injecting your notebooks with PDFs, research papers, notes, Google Docs, etc. helps Gemini Notebook get all the information it needs to answer any questions you may have about your current research topic. Being able to turn your notebooks into Audio & Video Overviews, Slide Decks, Quizzes, Flashcards, etc. also stands out as some of the best ways Gemini Notebook handles your research sessions.

ChatGPT is known far and wide as the mainstream AI tool that your everyday AI chatbot user makes use of. Presenting it with super descriptive prompts (a good example of that being "Research the current AI landscape in 2026. Compare OpenAI, Google, Anthropic, Microsoft and Meta. Include recent developments, strengths, weaknesses, market positioning, and cite sources”) helps it handle deep research tasks with more clarity. ChatGPT comes in handy when you’re looking to learn about new subjects, have the most complex topics explained to you in simpler terms and have research data built into structured reports.

Elicit stands tall as one of the best AI research tools for users interested in deep academic literature discovery and structured data extraction. Students and professional researchers can definitely put their trust in this option since it cites 138 million academic papers and 545,000 clinical trials (with more scientific data sources set to arrive later).

And finally, Google AI Mode is a viable pick when you’re looking for a web research option that can handle any tasks you once gave to Copilot’s Deep Research tool. Since it’s readily available inside the Google Search bar, it’s great for comparing products, simplifying complex subjects, comparing viewpoints and discovering up-to-date information.

Bottom line

While the news of Microsoft Copilot’s Deep Research feature going away and being replaced by a mandatory paid option breaks our hearts, it’s less painful when you consider the wide range of free options you can use to replace it. It’s worth keeping in mind that chatbots are prone to hallucinating, which should compel you to always double-check every bit of information it sends your way. But for the most part, the seven AI deep research tools I’ve made you aware of are mostly dependable and worthy of your time.

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I've used Apple Notes for years. It's where I keep all my ideas, random thoughts and lists to stay organized. But like a lot of the Apple apps that come with the phone, I'd never really stopped to explore what it could do. So I decided to try something different. Instead of searching YouTube or scrolling through Reddit for tips, I asked ChatGPT one simple question:

"How can I make Apple Notes more useful in my everyday life?"

The suggestions were surprisingly practical. Rather than suggesting third-party tools, ChatGPT showed me how to unlock power features already sitting inside the app. Here are the eight changes that completely transformed my daily workflow.

1. Create a 'Dashboard' note instead of dozens of random notes

My biggest problem was finding notes after making them. What good was a brainstorm if the ideas were lost in my phone? To solve this, ChatGPT suggested building a single "Dashboard" note (essentially a Map of Content) using internal note links to connect everything I use regularly.

This brilliant trick put a halt to endlessly searching through hundreds of flat notes. Now I open one main note and use it as the control center. It turns Apple Notes into a personal wiki.

Mine now includes linked sections for:

Work & Projects

Story & Article Ideas

Family Reminders & Shared Lists

Travel Itineraries

Frequently Used Links & Resources

2. Pin the Notes you actually need

I’d ignored the Pin feature for years. Now, my Dashboard, weekly to-do list and active project notes stay permanently anchored to the top of the app. It saves more time than I expected because I’m no longer hunting through old entries several times a day.

3. Turn one giant note into collapsible sections

I tend to dump everything into giant, sprawling text files. ChatGPT suggested organizing long notes using "Headings" combined with collapsible sections. Now, for long-form brainstorming or article ideas, I can expand or hide categories as needed. It keeps huge notes organized and very easy to navigate.

4. Scan paper documents intead of taking photos

I used to snap blurry camera photos of physical documents. Not only did that clutter my photos, but the quality of the image just wasn't good. But Apple Notes has a built-in scanner that crops, flattens and sharpens paper into high-contrast PDFs.

I now scan warranty info, school forms, insurance paperwork and receipts directly into designated folders. They look cleaner, take up less storage and the text inside them is fully searchable.

5. Let ChatGPT organize messy brain dumps

This ended up being my favorite workflow. When I have messy, unorganized meeting notes or rapid-fire ideas, I copy the mess into ChatGPT and ask it to structure the information:

"Organize these notes into bulleted categories."

"Turn these raw thoughts into an prioritized action list."

"Summarize key takeaways and highlight unresolved questions."

Once ChatGPT cleans and formats the text, I paste the polished version back into Apple Notes. It gives me the speed of raw note-taking with the clarity of an organized system.

6. Build reusable Note templates

There are certain structures I use over and over. I now keep a dedicated folder of master templates for:

Packing Lists

Weekly Planning & Reviews

Meeting Agendas

Vacation Itineraries

Whenever I need one, I simply duplicate the template note instead of building it from scratch.

7. Use smart folders & tags to organize automatically

Instead of manually moving notes into nested subfolders, I started tagging entries with hashtags like #work, #recipes, #travel or #ideas.

Using Smart Folders, Apple Notes automatically pulls every tagged note into its corresponding hub. I can save a quick thought, slap a tag on it, and trust that it will route itself to the right place.

Bonus: trigger 'Quick Notes' and auto-templates with iOS Shortcuts

To take automation a step further, I paired Apple Notes with Apple’s native Shortcuts app and Quick Notes.

Quick Notes: Swiping up from the bottom-right corner of an iPad or tapping the Quick Note control in iPhone's Control Center opens an instant scratchpad without opening the main app.

Automated Templates: I set up a simple Shortcut on my home screen titled "New Weekly Plan." Clicking it automatically generates a fresh, pre-formatted Apple Note with the current date, ready for my weekly review.

My biggest takeaway

Before asking ChatGPT to help, I had pretty much given up on my notes app and resorted to just emailing myself everything. That has led to a whole slew of disorganization issues. I needed a solution and ChatGPT delivered!

I expected AI to suggest something like Notion or Obsidian. Instead, it showed me how to get 90% of those advanced workflows using tools Apple had provided all along.

The biggest improvement was getting my Apple Notes to a place where they are useful again, despite being full of ideas. ChatGPT helped me go from a digital sticky note graveyard to the backbone of my everyday organization.

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I’ve been a loyal Marvel Cinematic Universe fan ever since Tony Stark built his original Iron Man suit in a cave with a box of scraps.

Since that pivotal moment in superhero/comic book movie history took place, I’ve plopped myself down in theaters far and wide to witness the formation of the original Avengers, see Black Panther & Spider-Man make their MCU debuts, get a glimpse of the destructive power Thanos wields, lay witness to his epic demise and follow all the vital post-Endgame happenings on the big & little screen.

Like most diehard MCU followers, I’ll admit to being less than enthused with some of the movie and TV show follow-ups to “The Infinity Saga.” Films like Black Widow, Thor: Love and Thunder and Ant-Man and the Wasp: Quantumania were complete duds to me. And on the Disney+ exclusive series front, shows like Ms. Marvel, She-Hulk: Attorney at Law and Secret Invasion definitely dulled my excitement for the MCU.

But as soon as that Avengers: Doomsday trailer came across my timeline, a large part of that enthusiasm came back tenfold. With that blockbuster event primed for December 18, I have plenty of time to prep myself for the next MCU epic. And I used ChatGPT to set me up with the ultimate watchlist to enjoy on Disney+.

Splitting up the ultimate MCU recap by tiers of chronological importance

With this prompt, I gave ChatGPT its marching orders: “Give me the ultimate Marvel Cinematic Universe movie and Disney+ series playlist to watch that'll get me up to speed on everything I need to know before watching Avengers: Doomsday.”

To start, the chatbot laid out a list of chronological tiers that included MCU films and shows regarded as essential viewing. Alongside each list of films was a list of reasons to watch them for the first time or rewatch them to refresh my memory of the major events leading up to Avengers: Doomsday. Here’s ChatGPT’s tier list of MCU projects worth watching before Doom terrorizes the heroes we all know and love:

• Tier 1 - Absolutely Essential (Start Here): Watch Iron Man, The Avengers, Captain America: The Winter Soldier and Captain America: Civil War. These movies highlight Tony Stark’s journey, Steve Rogers’ ideals, The Avengers splitting apart and the introductions of Spider-Man & Black Panther. Then watch Avengers: Infinity War and Avengers: Endgame to understand “The Blip,” the multiversal consequences, and where every original Avenger ended up.
• Tier 2 - The Multiverse Story: Watch Loki (Season 1) because it explains “Variants,” timelines, the “TVA,” the “Sacred Timeline” and why the multiverse begins breaking apart. Follow that up by watching Spider-Man: No Way Home, as it introduces multiversal travel and reality-breaking consequences. Watching Doctor Strange in the Multiverse of Madness is critical because it introduces “incursions,” alternate universes, “Dreamwalking,” the “Illuminati” and incursions becoming universe-ending events. Then watch Loki (Season 2) to grasp how time now works, the TVA’s new purpose and Loki’s new role.
• Tier 3 - The New Avengers: Watch Black Panther: Wakanda Forever to see Wakanda’s Future, Shuri, Riri Williams and the world politics at the heart of the MCU. Then check out Shang-Chi and the Legend of the Ten Rings as it introduces one of the strongest future Avengers members and leaves behind one of the MCU’s biggest mysteries surrounding the Ten Rings’ origin. Watch The Marvels to see how Manica Rambeau ends up in another universe, how Kamala Khan begins assembling a new generation of heroes and how the ending directly teases multiversal crossovers. Then watch Thunderbolts*, since it effectively establishes another major superhero team and introduces key players expected to matter going forward.
• Tier 4 - Fantastic Four Preparation: Check out The Fantastic Four: First Steps, as it introduces Marvel’s “First Family” into the current MCU saga and lays the groundwork for Doctor Doom’s arrival.

The ideal viewing orders for an extended monthly watchlist and a weekend binge session

ChatGPT also generated two lists that split its respective viewing orders across months' worth of MCU entertainment and a binge-worthy weekend session. Here are the 17 Disney+ Marvel films and shows it gave me for both lists (I’m definitely taking down the first one until December arrives!):

• Ideal Viewing Order: Iron Man, The Avengers, Captain America: The Winter Soldier, Captain America: Civil War, Avengers: Infinity War, Avengers: Endgame, WandaVision, Loki (Season 1), Spider-Man: No Way Home, Doctor Strange in the Multiverse of Madness, Loki (Season 2), Shang-Chi and the Legend of the Ten Rings, Black Panther: Wakanda Forever, The Marvels, Deadpool & Wolverine, Thunderbolts* and The Fantastic Four: First Steps.
• If you only have one weekend: Avengers: Infinity War, Avengers: Endgame, WandaVision, Loki (Season 1), Spider-Man: No Way Home, Doctor Strange in the Multiverse of Madness, Loki (Season 2), The Fantastic Four: First Steps and Thunderbolts*.

Bottom line

Of course I’m going to see all the craziness Peter Parker will get himself caught up in once Spider-Man: Brand New Day drops on July 30. The combination of Spidey, The Punisher and The Hulk all in the same movie has me in extreme hype mode!

But after that, I’m going to dive deep into the ideal MCU recap viewing order ChatGPT generated to get me up to speed on everything I need to know before I watch Avengers: Doomsday on the biggest screen possible in the loudest theatre I can find.

I can’t wait to watch the Avengers, Wakandans, New Avengers, Fantastic Four and the X-Men join forces from different universes to finally confront Dr. Doom (and probably get destroyed in the process before they make the ultimate comeback in Avengers: Secret Wars).

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There are very few things more humbling than looking for a job with little or no response. It's not only overwhelming but also frustrating when it feels as though AI is everywhere and everyone has access to the same AI tools.

A recent study even found that nearly half of LinkedIn posts longer than 250 words appear to be AI-generated, highlighting just how crowded the AI-assisted job market has become.

That's why, whenever a friend tells me they're looking for a new job, I don't tell them to ask ChatGPT to write another cover letter. Instead, I recommend what I call the Escape Prompt.

The name comes from a simple idea: don't use AI to apply for more jobs. Use it to figure out how to escape your current situation and explore something new.

What is the Escape Prompt?

Instead of asking ChatGPT to "find me a new job" or "write my resume," ask it to become your career strategist.

Here's the prompt: Act as my career strategist, recruiter and interview coach. My goal isn't simply to find another job — it's to leave a role that no longer fits me.

If you don't have memory enabled, you need to include the following information when you use the 'Escape Prompt'. Add, "here's my background: Current role, years of experience, skills, industries I've worked in, what I enjoy most about my job, what drains my energy, salary goals, location preferences. Then, based on this information, recommend career paths I may not have considered, explain which of my skills transfer best to those roles, identify companies that value my experience, rewrite my experience for those employers, point out skills I should build over the next six months, create a realistic 30-day job search plan. generate interview questions I should expect. Challenge my assumptions if I'm thinking too narrowly."

As a bonus, if you have memory enabled, use this prompt: Based on what you know about me, what should I do tomorrow to progress in my career and find a job I love.

Keep in mind that when you use this prompt, you're going to get a long response back from ChatGPT. If you get overwhelmed by a lot of information at once (I know I do!), then break up the prompt or ask for bullet points.

Why it works

This prompt creates a response that's tailored specifically for you. In a job market with so much AI slop, this is an opportunity to get information catered to you and your needs.

That said, when you can still use ChatGPT to help write your resume and prepare for job interviews, but make sure you go over your AI-written resume and cover letter to avoid embarrassing mistakes. AI is great as an assistant, but just like you wouldn't let an intern complete the entire project, you need to be in the loop to ensure everything is correct and doesn't give off the "uncanny valley" AI response.

The Escape Prompt flips job searching on its head

Instead of completing one task at a time, ChatGPT spends the entire conversation learning about your experience, your strengths and what you're actually trying to achieve. Every follow-up becomes smarter because it's built on everything you've already shared.

I also highly recommend turning on memory if you are using ChatGPT a lot in your job search. By doing that, the chatbot will feel like a real career coach and offer responses that make more sense to your current situation.

The Escape Prompt helps you think beyond your current title. After all, one of the biggest mistakes job seekers make is searching for the exact same role at a different company. But your next opportunity might not have the same title.

Someone working in customer support might be a great fit for customer success. A project coordinator may have the skills to move into operations or journalist might discover opportunities in content strategy, communications or developer relations that never appeared in a traditional job search.

The Escape Prompt pushes ChatGPT to look for those connections instead of simply matching keywords. In my experience, those conversations are often more valuable than having AI rewrite another resume.

The takeaway

Using this prompt can help make your application even stronger. Once you've identified the roles you actually want, you can use the same conversation to tailor your resume, refine your LinkedIn profile, write a cover letter, prepare for interviews and even practice answering difficult questions.

Since ChatGPT already understands your background, the responses feel more connected instead of starting from scratch every time.

That's a much better use of AI than repeatedly asking for disconnected pieces of career advice. Just remember not to let AI do all the thinking. Be sure to research companies yourself, verify salary information, read employee reviews and reach out to people already working in the roles you're considering. You can use AI as a fact-checker and to help point you to the right people, but don't use it as a replacement for actual human judgement.

As AI becomes a standard part of the hiring process, simply using ChatGPT isn't going to make you stand out. Recruiters are seeing more AI-polished resumes, more AI-written cover letters and more AI-generated LinkedIn content than ever before. The real advantage comes from using AI differently.

The Escape Prompt can help you figure out where you should go next, why you're qualified to get there and how to tell your story with confidence. If you're feeling stuck in your current job, spend 15 minutes with this prompt before you send another application.

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To say that people weren’t impressed when Nvidia DLSS 5 was announced would be an understatement. Gamers and critics alike expressed concerns over heavy-handed “beauty filters” smoothing out character faces and AI overwriting developer art direction. The initial requirement of a second GPU for rendering also didn’t go over well.

At SIGGRAPH, Nvidia held a follow-up keynote that was practically built to address the concerns folks have with DLSS 5. Instead of focusing on how photo-realistic DLSS 5 could make graphics appear, the keynote centered around the amount of control artists will have over the technology.

Here’s a breakdown of what Nvidia discussed at SIGGRAPH and how DLSS 5 might not be as bad as we feared.

Granular control

As you might recall, the biggest complaint with DLSS 5 is how the graphics appeared to have an Instagram/TikTok filter slapped over them. A less charitable description would be an “AI slop” filter. Nvidia addressed this concern directly, saying that game artists would have full control over a game’s graphics.

Developers won’t be forced into all-or-nothing with AI. They’ll be able to mask out individual characters, faces, props, or background elements so DLSS 5 either ignores them or processes them with tailored settings. Structural and Tone Intensity sliders will give devs fine control over how things appear. There will also be three distinct AI models for developers to assign.

No AI overwrites

Another concern is that the AI would hallucinate on low-poly geometry or rewrite hand-crafted visuals. DLSS 5 isn’t generating a game scene from scratch but relies strictly on internal game engine buffers to preserve the artist’s original intent.

Nvidia emphasized that traditional rasterization and ray tracing still build the entire frame first, defining geometry, lighting anchors, motion vectors, and surface normals. Nvidia framed DLSS 5 as a third category of AI rendering alongside upscaling reconstruction and frame generation. The engine creates the world while the model enriches complex lighting elements.

Latency

Generative video models usually process frames in batches, which can introduce input lag. That’s obviously a non-starter for fast-paced games like CSGO 2.

Nvidia says that DLSS 5 processes the current frame using the game’s engine’s native motion vectors without looking ahead to future frames. By avoiding multi-frame batch processing, Nvidia’s goal is to eliminate both generative latency and temporal shimmering artifacts.

One GPU needed, not two

When Nvidia first demoed DLSS 5, the computational overhead was so heavy that it reportedly required dual high-end GPUs just to run smoothly. Naturally, this isn’t feasible for most players, but Nvidia says you’ll be able to run DLSS 5 on a single GPU.

To that end, Nvidia revealed that they have distilled the massive generative model into a much smaller, single-step diffusion model. The updated implementation has been engineered to run on a single RTX GPU with efficient VRAM allocation instead of requiring multi-GPU rigs that only hardcore users own.

Outlook

I’ve championed Nvidia DLSS for years, but I was one of the folks who wasn’t enamored with that initial DLSS 5 reveal. Now, after SIGGRAPH, I'm less worried about this fall's upcoming update.

We’ll have to wait to see how the final version functions, but I’m glad that Nvidia has addressed all the major concerns. If we can get richer game graphics without the infamous AI look, then we’ll all be winners.

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There’s a whole lot to be excited about if you’ve been using Samsung’s signature lineup of smartphones.

With all the news emanating from this year’s Samsung Galaxy Unpacked event, it’s easy to see why — there’s a multitude of brand new smartphone models on the way with a host of Android-powered features that push its capabilities beyond the ones you’ve owned thus far. The unveiling of the Samsung Galaxy Z Fold8 Ultra, Fold8, and Flip8 showcased the consumer electronics company’s penchant for releasing some of the most impressive smartphones on the market.

And as expected, Samsung is tapping into the Google Android ecosystem to bring new forms of AI integration to its newest smartphones. Gemini Intelligence and Gemini Notebook (formerly known as NotebookLM) will be a major part of your daily reliance on Samsung’s latest mobile devices, as they look to help you finish your everyday chores, handle extensive research and more.

Gemini Intelligence and Gemini Notebook inside Samsung’s latest phones

Task automation is the central theme when talking about what Gemini Intelligence is bringing to the new Samsung smartphone lineup.

While in beta, Gemini Intelligence could fulfill certain requests, such as ordering takeout or requesting a rideshare, through direct support from a group of apps. Now those day-to-day life tasks that you can relegate to Gemini Intelligence are getting even more app assistance, now that more than 40 apps have become compatible with that AI feature. Asking Gemini to order an item from Etsy is now possible, along with a host of other simple tasks — buying concert tickets, making dinner reservations and booking flights are among the many ways this new AI feature will improve your Samsung smartphone experience.

Gemini will also be able to see and understand what's on your screen as it acknowledges your requests and recognizes complex images as prompts. Plus, you’ll be able to open other apps, close your phone or follow the step-by-step progress of Gemini’s work while it attempts to complete your command. It’s worth noting that you can expand upon your latest prompt with an additional detail, which Gemini has no problem incorporating into its current task. Simply long-pressing the Flex Window’s power button on the Galaxy Z Flip8 lets you quickly access Gemini’s task automation feature.

As for what Gemini Notebook is bringing to the latest Samsung foldable smartphone collection, this AI tool will come pre-installed. Working with those models’ side-by-side screen as a mini-workspace is now possible with Notebook’s ability to answer questions about the topic you’re researching and the sources connected to that subject. And just like its desktop version, Notebook’s mobile iteration will integrate your uploaded documents, photos, whiteboard images, voice recordings and more into your research projects. Notebook’s chat functionality can take your research and transform it into different forms of study material, such as slide decks, videos, flash cards, quizzes and a podcast.

To give owners of the Galaxy Z Fold8 Ultra, Fold8 and Flip8 a peek into just how useful Notebook’s AI features can be, Samsung is giving them all a six-month trial of Google AI Pro on those phones. That subscription comes with even more useful Notebook features, which include Audio Overviews, Video Overviews, Slides, and more.

Other pieces of Samsung gear, such as the Galaxy Watch 9 and intelligent eyewear developed alongside major brands such as Gentle Monster and Warby Parker, will also come with their own Gemini-powered features.

Bottom line

With a newly announced array of foldable smartphones that make great use of Gemini Intelligence and Gemini Notebook, its users will be sure to grow accustomed to handling life’s simpler tasks and more complex ones with both AI tools at their disposal. Making one’s daily routine just a little less of a headache and more easily manageable with Google’s AI features makes Samsung’s newest smartphones a worthwhile pickup.

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Taking care of my health is something I take seriously. I try to stay active, look after my mental well-being, and keep up with regular dental and eye exams.

That made me curious when I learned about World Brain Day, a global awareness campaign focused on brain health and neurological disorders. According to the World Federation of Neurology, more than 3.4 billion people worldwide are living with a neurological condition. Yet millions still struggle to get the care they need because of high treatment costs, shortages of specialists, and long wait times for appointments.

To mark World Brain Day, I turned to ChatGPT to learn more about brain health and what I can do to help protect it. The conversation gave me plenty of useful information—and, just as importantly, pointed me toward topics worth researching further with trusted medical sources. These are the seven prompts that helped me better understand my brain health.

A prompt centered around the actions I can take to protect my brain health

I asked ChatGPT to come up with a list of prompts built around the WFN’s five core pillars of World Brain Day, which are as follows:

• Brain Health Is for Everyone – Equity in care.
• Earlier Access Changes Lives – Prioritizing early intervention.
• Prevention Starts in Everyday Life – Reducing risk factors.
• Bring Brain Care Closer to Home – Community-based support.
• Awareness Must Lead to Action – Measurable impact.

The first prompt the chatbot created for me was this one: Explain the five biggest things I can do today to protect my brain health and rank them by the impact they'll likely have over my lifetime.

ChatGPT started off its thorough explanation to that prompt by stating the following: Protecting your brain health is less about finding a single “brain-boosting” trick and more about consistently reducing risk factors while strengthening the systems your brain depends on: blood flow, sleep, learning, emotional regulation, and social connection.

The five tips the chatbot proceeded to give about prolonging my brain’s healthy status included prioritizing my cardiovascular health, treating my sleep sessions like they’re brain maintenance, constantly challenging my brain through daily learning practices, strengthening my relationships through daily instances of social connection and reducing all forms of chronic stress & emotional resilience.

The three main habits ChatGPT told me to adopt daily include walking for at least 30 minutes, getting a full night of quality sleep and spending meaningful time with another person. Those actions go a long way toward improving my blood flow, brain repair, mood regulation and cognitive resilience.

Moving my body, nourishing my brain with educational material like books, challenging my brain with all manner of physical & digital puzzles, connecting with people via meaningful conversations and recovering after a long workday with at least seven to nine hours of sleep are all vital behaviors worth adding to my daily routine.

6 more prompts focused on learning about brain health, warning signs of brain disorders and more

As for the other prompts that proved to be enlightening on the topics of being aware of the most common brain disorders, common myths about brain health and more, these six provided me with the informative chats I was looking for:

• Pretend you're a neurologist giving a free 10-minute brain health consultation. What questions would you ask me, what risk factors would you look for, and what lifestyle changes would you recommend?
• Teach me the early warning signs of the most common brain disorders—including stroke, dementia, Parkinson's disease, epilepsy, and multiple sclerosis—and explain when someone should seek medical attention.
• Design a science-backed 30-day brain health challenge that improves memory, focus, mood, sleep, and long-term cognitive health using habits that take less than 30 minutes a day.
• If someone lives in an area with limited access to neurologists or brain specialists, what practical steps can they take to monitor their brain health, find reliable resources, and advocate for better care?
• Bust the 10 most common myths about brain health, memory loss, aging, and neurological diseases, and explain what the latest scientific evidence actually says.
• Create a personalized brain health scorecard. Ask me about my sleep, diet, exercise, stress, social life, learning habits, alcohol use, and medical history, then explain which areas deserve the most attention and why.

The takeaway

2026 has turned into a year where my knowledge of holidays has extended beyond the usual ones that force everyone to spend a whole bunch of money to satisfy their loved ones.

World Brain Day will remain an important holiday to me from this point forward—learning about the devastating ailments that target the brain, getting informed about the best practices one must adopt to improve & maintain their brain health and getting an early detection of neurological conditions shouldn’t be just a holiday occurrence, but a daily, weekly and monthly one.

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If you've been following AI news lately, you've probably heard the words "open source" far more than usual.

Nearly every week, another company announces an "open" AI model. Meta has Llama, Mistral has built its reputation on open-weight models, Chinese company Moonshot AI recently released Kimi K3 and even companies that once kept everything behind closed doors are becoming more willing to share parts of their technology.

If you're wondering what "open source" means, you're not alone. Although it may seem like a buzzword or phrase, there's more to it than big tech giving away their precious models for free.

If training an AI model costs hundreds of millions of dollars — or even billions when you factor in the enormous data centers and specialized chips needed to power them, why would companies spend that kind of money only to give their work away?

The answer is that they're not really giving everything away. And in many cases, making models more open is actually good business.

What exactly is open source AI?

First, let's clear up one common misconception. The phrase "open source AI" gets thrown around a lot, but it doesn't always mean what people think it does. A truly open-source project typically makes its code, training methods and licensing available for anyone to inspect, modify and redistribute.

Many of today's AI models are actually open weight rather than fully open source. That means developers can download the trained model and run it themselves, but the company may not release the training data, the code used to build it or every detail of how it was created.

It's a subtle distinction, but an important one. For everyday users, though, the experience is often the same. In other words, more people can build with these models, improve them and create new AI tools without starting from scratch.

The AI arms race has changed

The AI race isn't just about having the smartest chatbot anymore. A couple of years ago, companies competed primarily on who could build the smartest AI model and who could hit the benchmarks first. Today, that's only part of the equation. Now they're competing to become the platform everyone builds on.

Think about Android. Google gives Android away for free because every phone running Android strengthens Google's broader ecosystem. Developers build apps, manufacturers adopt the operating system and users become more likely to use Google's services.

AI companies are actually thinking the same way. If thousands of developers build apps around your model, businesses deploy it inside their organizations and researchers improve it, your technology becomes far more valuable than if it stayed locked behind a subscription.

Open models spread much faster

When a model is widely available, something interesting happens because developers begin fine-tuning it for specific jobs. Maybe universities use it for research or startups build entirely new products on top of it. Hobbyists could even discover creative uses that the original creators never imagined.

And, well, that creates a snowball effect. Instead of one company improving the model, thousands of people contribute ideas, tools and innovations around it. Even if the underlying model doesn't change, the ecosystem around it grows rapidly.

Open source vs. open-weight AI: What's the difference?

These two terms are often used interchangeably, but they're not actually the same thing.

Think of it this way:

• Open source AI is like getting the entire recipe for your favorite meal. You can see every ingredient, understand how it was made, modify it however you like and even share your own version with others.
• Open-weight AI is more like getting the finished cake. You can eat it, decorate it, serve it to guests and even bake new desserts using it as a base— but you don't know exactly how the original baker made it.

Companies still have plenty of ways to make money

Making a model available doesn't necessarily mean giving up revenue. Many companies earn money by offering managed cloud services that make those models easier to run, faster or more reliable. Others sell enterprise security features, premium APIs, consulting services or specialized infrastructure.

Hardware companies benefit, too. Every new AI model ultimately needs powerful GPUs or AI accelerators to run. More open models often translate into greater demand for the hardware that powers them.

In other words, the model itself isn't always the product, but it's often the engine driving a much larger business.

Competition has changed the industry

Open source artificial intelligence wasn't always viewed as a winning strategy. In fact, for many years the assumption was that the most capable models would remain closely guarded because they represented a competitive advantage.

Now, that thinking has shifted. As more companies released powerful open-weight models, it became harder for closed systems to justify charging a premium based on exclusivity alone. Since the competition isn't about intelligence anymore, factors like speed, developer support, integrations, enterprise features, privacy options and cost all matter, too.

That's good news for users because it gives them far more choice than they had even two years ago.

What this means for the average ChatGPT user

Even if you never download an AI model yourself, you're already benefiting from this shift. Open models are helping create better free AI tools, giving smaller developers access to cutting-edge technology and increasing competition across the industry.

They're also making it possible for more AI to run locally on laptops and smartphones, which can improve privacy by keeping sensitive information on your own device instead of sending everything to the cloud.

Not necessarily a good thing, but the competition is pushing every AI company to move faster. The result is that consumers have more capable AI assistants, more options to choose from and a steady stream of new features arriving at a pace that would have seemed impossible just a few years ago.

So while it might look like AI companies are suddenly giving away their most valuable technology, they're really investing in something even more valuable: building the biggest ecosystem around their models. Judging by the number of open-weight releases we've seen this year, it doesn't look like that strategy is slowing down anytime soon.

More from Tom's Guide

• I found the 7 easiest Claude connectors for people over 50 — start with these
• I replaced my notebook with an AI pen for a month — here's what happened
• I asked ChatGPT to make my iPhone more private — it found 7 settings I wish I'd turned on years ago

I use ChatGPT almost every single day, but until recently, I treated Voice Mode, or as it's now called GPT-Live-1, as something I used only on occasion. I didn't use it for anything other than quick questions when I was cooking or, recently, when I needed live translation. For anything requiring actual work or multi-step planning, I always defaulted to the chat box and typed my query.

That mindset changed completely when I decided to plan a last-minute weekend getaway. Normally, planning a trip is a chaotic ritual, especially when planning for my family of five. I'd bounce between Google, hotel booking sites, Yelp reviews, Google Maps and of course, ChatGPT, frantically copying and pasting details across tabs until I could build an itinerary.

This time, I closed my laptop, put my phone on speaker and did everything in one fluid conversation using live voice. That's right, I simply started talking out loud as if sharing my plans with a friend. Within minutes, ChatGPT helped narrow down destinations, suggest boutique hotels, match local restaurants to our vibe, adjust budget constraints and even map out a rainy-day backup plan.

Here is how speaking, rather than typing, completely changed my workflow — and why I don’t think I’m going back.

1. I started with a casual conversation

When I type prompts, especially for things like travel, I tend to try to fit everything into the first prompt. But with voice, that doesn't seem necessary because the entire interaction is so much more fluid and natural. I kicked off the conversation like I was talking to a friend:

"My husband, me and our three kids want to get away for a long weekend. We’d like to stay within about a three-hour drive of New Jersey, keep the budget under $2,000, and mix some outdoor activities with great food. Can you help us figure out where to go?"

Instead of dumping a 500-word list of links or overwhelming me with dozens of choices, ChatGPT paused and asked natural follow-up questions:

Did we want a cozy mountain setting or a coastal vibe?

Were we looking for a quiet, low-key town or somewhere with walkability and a bit of nightlife?

Were we celebrating a special occasion, or was this purely to unwind?

It felt like I was planning the getaway with an actual travel agent whose only goal was to figure out what kind of trip we actually wanted before dumping recommendations on us.

2. Interrupting was the best part

The new GPT-Live-1 voice is great when it comes to interruptions. Unlike an actual person with feelings, you can interrupt the AI at anytime.

When it started pitching a luxury boutique stay in the Hudson Valley that was clearly going to eat up most of our budget, I just talked over it: "Actually, pause on that — that stay looks a bit too pricey. What’s something cozy nearby under $400 a night?"

Without missing a beat, it stopped, acknowledged the price correction, and pivoted to a bed-and-breakfast in Pennsylvania instead.

I tried this a few times with other queries like, "Slow the schedule down — we want to sleep in."

At one point, I completely pivoted and said, "Actually, let's pivot away from mountains—what about Cape May?"

When you're typing, changing your mind means editing a long prompt, deleting text or typing out lengthy explanations. In voice mode, correcting course mid-sentence feels entirely natural and easy.

3. It retained context effortlessly

As our conversation spiraled into tiny side tracks, ChatGPT kept every constraint locked in memory. It remembered our budget, our max driving radius and the fact that we wanted a slow-paced trip.

Because it kept track of all the context seamlessly, I could toss out rapid-fire, low-effort questions:

"What if it rains all day Saturday?"

"Can we swap that lunch place for somewhere with a great patio?"

"Is there a scenic hike on the way back home that takes under two hours?"

I never had to repeat "Remember our budget" or "Keep it near New Jersey." It just knew.

4. It handled the legwork

Once we locked in the general region and vibe, I asked ChatGPT to do some quick live research on specifics: finding current room rate averages, checking if local kid-friendly spots needed reservations and verifying park hours for our hike.

Pro-Tip: Always verify live operational details directly with the venue before booking! AI is brilliant at aggregating options and pricing estimates, but restaurant hours and hotel availability can shift unexpectedly.

Having ChatGPT gather initial numbers into one spoken stream saved me easily an hour of tab-switching.

5. From voice chat to a polished itinerary in seconds

Once we finished bouncing ideas back and forth, I moved back to my screen and typed one single request in the exact same chat log:

"Turn everything we just agreed on into a day-by-day itinerary. Include estimated costs, addresses, drive times and a clear rainy-day backup plan."

Within seconds, the chaotic, organic conversation was transformed into a clean, beautifully formatted travel guide.

One caveat to keep in mind

While you can ask ChatGPT to give you an itinerary, the AI does not show the conversation on the screen. Once you're done chatting, you have to refer back to it to see the full conversation, itinerary or any other information.

That's one feature I really wish OpenAI would fix, but until they do, it's something to be mindful of before you close out of the conversation. If you accidently do close out and want to pick up where you left off, just prompt with something like, "Remember the weekend trip we were planning? Let's go back and discuss those details."

Final thoughts

I expected voice mode to be frustrating or make me feel less in control because I wasn't jotting everything down myself. But really, it felt like it reduced my cognitive load.

When typing, we instinctively censor or format our thoughts before putting them into a prompt box. Talking out loud lets you brainstorm in real time. You get to figure out what you want while you're saying it, and the AI keeps up with your messy human thought process.

Want to try this yourself? Start with this prompt: "My partner and I want to plan a weekend getaway within a [X-hour] drive of home. Our budget is $[X]. Ask me questions one at a time until you have enough information to build our ideal itinerary."

Let me know in the comments if you try it and share your results in the conversation.

More from Tom's Guide

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• I asked ChatGPT to make my iPhone more private — it found 7 settings I wish I'd turned on years ago

I write about AI for a living. I use ChatGPT almost every day and a plethora of other AI tools are integrated into my workflow. But after reading what author Dave Eggers recently told OpenAI employees, I found myself thinking even more about how AI affects my own kids.

Originally reported by The Verge, OpenAI CEO Sam Altman invited Eggers to speak to roughly 200 employees at the company last year. Given Eggers' reputation as an acclaimed novelist, founder of McSweeney's and longtime advocate for literacy, many probably expected a conversation about storytelling or creativity.

Instead, he delivered a blunt critique of generative AI's impact on education.

"The effect of ChatGPT on educators' lives is catastrophic," Eggers reportedly said. "If students are using it to compose... they'll never learn to write. And their voice is stolen from them... That's silencing an entire generation or two."

It's a dramatic statement, and while I don't agree with every part of it, it does raise questions that every parent should be asking.

Writing isn't just about producing words

One of the biggest misconceptions about AI is that writing is simply about creating a finished product. But it is not that easy. Writing is how we organize our thoughts and how we figure out what we actually believe. It's also how we learn to make an argument, explain an idea and communicate with other people.

Anyone who's ever stared at a blank page knows that the hardest part isn't typing the words, but actually doing the thinking that comes before them.

That's the part I'm most concerned about. If students immediately turn to ChatGPT to generate an essay, summarize a novel or answer every homework question, they're skipping the mental work that helps those skills develop in the first place.

I believe that's what Dave Eggers is worried about, too. While the finished assignment might look and sound better than what a child could have written, it's only a shell because arguably the child didn't learn anything.

I don't think schools should ban AI

Still, I don't think pretending ChatGPT doesn't exist is realistic. By the time today's elementary school students graduate from high school, AI will likely be as common as Google is today. Knowing how to use it responsibly will probably become an important life skill.

I think there's a big difference between using ChatGPT as a tutor and using it as a replacement for your own thinking.

For example, AI can be incredibly helpful for:

• explaining a difficult concept in simpler language
• brainstorming ideas before you start writing
• checking grammar or spelling after you've written something
• helping you study for a test
• giving feedback on a first draft

Those uses still require you to do the work. The line gets blurrier when AI writes the first draft for you, which is where Eggers' criticism has merit.

I have three children, and AI is going to be part of their education whether I like it or not. That means my job isn't to convince them never to use ChatGPT (my sixth grader already does — mostly to generate images of him playing soccer with Ronaldo, but he is still very aware of what it is). My job is to help them understand when they should and should not use it.

For example, if they're stuck on a math concept, AI can be a great teacher. If they need ideas for a science project, it can be a useful brainstorming partner. But if they immediately ask ChatGPT to write the essay they're supposed to write themselves, they've missed the point of the assignment.

My final thoughts

I don't think ChatGPT will "silence an entire generation." as long as parents stay diligent about how and why are kids use AI. Like every major technological shift before it, AI is a tool and we have to help our children use it safely.

But Eggers' warning is still worth hearing. As AI becomes more capable, it will become even more tempting to let it think for us instead of with us. That's a habit all of us need to resist.

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As soon as my work week starts, I prepare myself for days full of meetings.

I don't mind them — in fact, they're often where my best article ideas come from. But after hours of back-to-back calls, it's easy for important details, follow-ups and action items to get buried. Even with AI meeting assistants like Gemini taking notes during Google Meet calls, I still find myself digging through transcripts trying to figure out what actually needs my attention.

That's why I was intrigued by a device I've been testing for the past week. It's called the SecondBrain Note, and it's made by the team behind Genspark, the AI workspace that brings together multiple leading AI models in one place.

Paired with the Genspark AI Workspace, the SecondBrain Note did more than just record my meetings. It turned conversations into organized summaries, surfaced the tasks I needed to tackle, and helped me turn a packed day of meetings into a clear, actionable to-do list. After using it for a week, it's become one of the most useful AI productivity tools I've tested.

Taking audio notes and turning them into workday actions

Genspark's SecondBrain Note is a card-sized AI notetaker that slips into a magnetic case that attaches to the back of your phone. The setup doubles as a phone stand, making the device clearly visible during meetings while an RGB privacy light lets everyone know it's recording. One feature I quickly came to appreciate was the ability to press the record button at key moments to manually bookmark important parts of a meeting.

Once my meetings began, I made sure everyone knew I was recording and let the SecondBrain Note do the rest. After each meeting, I turned it off and kept it near my phone while the recordings transferred to the Genspark app. What sets the SecondBrain Note apart from other AI notetakers is how it feeds everything into Genspark's SecondBrain memory system, turning meeting summaries into searchable context inside the Genspark AI Workspace.

That meant I could quickly pull up a person's name, a project discussed during a meeting, decisions that were made or follow-up questions and answers simply by searching within the workspace. Instead of hunting through transcripts, the information I needed was already connected to the rest of my work.

Each recorded meeting was automatically downloaded into the Genspark app and organized into three sections: Notes, Transcript and Speakers, where I could manually identify participants if I wanted. I spent most of my time in the Notes section because it delivered exactly what I needed — a well-structured summary broken into clear sections, complete with speaker breakdowns, bolded names and key statistics, plus bullet points highlighting the most important takeaways. It made it much easier to identify the action items that applied to me as the week went on.

I also liked that every meeting transcript was emailed to me automatically, giving me a second place to reference my notes whenever I needed a refresher. Better yet, those meeting notes became part of Genspark's memory, so I could ask the Spark Agent to pull information directly from them. That makes it easy to create prompts that reference previous meetings or even work with third-party apps like Slack and Notion. Some examples include:

• Summarize my emails from today.
• Draft an email and meeting invite for [name].
• Summarize last week's meetings into a weekly report.
• Find the slides I made last week on [topic] and add a new page.
• What to-dos did [partner] leave me in Slack today?
• Pull this quarter's numbers from my HubSpot and turn them into a deck.
• Find everything in my Notion docs about [topic].

In my case, the SecondBrain Note gave me enough information from my transcribed meetings to jot down ideas for future articles, have detailed breakdowns of strategies my & other teams began implementing, new guidelines to follow and future meeting plans to remember. Having this device on hand for in-person meetings and business-related phone calls seems like two other great uses of this device, should those situations ever arise.

Prompting the Genspark AI Workspace to turn a meeting transcription into my daily to-do list based on the mentions that include my name works like a charm.

Final thoughts

Genspark’s SecondBrain Note will stay with me as my physical notetaker when the time comes to store all the significant details from a meeting that needs to be turned into published articles and other assignments I’m tasked with.

Since its battery life is respectable (up to 35 hours on a single charge) and its storage capacity is sizable enough (64GB of local storage that can store up to 7000 hours of recordings, which are automatically cleared to free up storage after it's synced to the Genspark app), I feel like I’ll never run out of the energy and space I need to document my most essential meetings.

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The more I explore what Claude Code can do, the more it becomes clear that Anthropic has built one of the best AI development tools on the market. It doesn't just generate code snippets; it can build full apps from scratch, debug complex errors, explain unfamiliar repositories, and completely automate your repetitive workflows.

But even after spending dozens of hours testing it, I realized I’d barely scratched the surface of what it can do.

Many of Claude Code's most useful features aren't immediately obvious. They're tucked away in technical documentation or designed for software engineers who live in the terminal.

Whether you're building your very first coding project, experimenting with AI-assisted workflows, or just looking to reclaim hours of your work week, here are the hidden Claude Code features you should start using right now.

1. Inject permanent project memory with a CLAUDE.md file

One of the single biggest time-savers in Claude Code is creating a CLAUDE.md file in your project's root folder. Think of it as a permanent onboarding manual. Instead of reminding Claude during every single chat session to use TypeScript, write unit tests, or follow a specific naming convention, you can bake those rules right into your project.

Claude automatically scans this file the moment you launch a session.
This is Ideal CLAUDE.md Architecture:

Project Overview: Tells Claude exactly what the app does. Example: "A Next.js dashboard for tracking personal finance."

Tech Stack: Locks down languages and frameworks. Example: TypeScript, TailwindCSS, PostgreSQL

Commands: Fast-tracks how Claude builds and tests. Example: npm run dev, npm run test

Code Style: Sets strict architectural rules. Example: "Always write dry code and include concise inline comments."

Pro-Tip: Don't turn this file into a textbook. Claude reads it at the start of every session, which uses up your token window. Keep it under 200–300 lines of highly concentrated project constraints.

2. Time-travel through your mistakes with Checkpoints

We’ve all had that heart-stopping moment where a single line of bad code completely breaks an application. Claude Code removes that anxiety entirely with its built-in checkpoint system.

As Claude works, it takes snapshots of your codebase. If an experimental feature goes sideways or a bug spirals out of control, you can instantly roll your project back to a pristine, earlier state.

How to use it: Type /rewind in the terminal (or hit Esc twice to bring up the history menu) and visually select the exact moment in time you want to jump back to.

3. Supercharge your workflow with Custom 'Skills'

While Claude Code features standard built-in slash commands for quick tasks, its true superpower is letting you build custom workflows called Skills.

If you find yourself repeatedly typing long, complex prompts to format data, generate marketing copies, or set up boilerplate folders, you can teach Claude a permanent Skill.

For example, you could teach it a /newsletter skill that automatically pulls your latest project updates, drafts a summary, structures an email template and suggests SEO improvements in one click. Once saved, it’s a permanent shortcut.

4. Break down complex jobs using Subagents

When you give an AI a massive, multi-step task, it can get overwhelmed and hallucinate. Claude Code solves this by dynamically spinning up specialized AI "subagents."

If you ask Claude to overhaul a major feature, it might quietly assign one subagent to review the existing code, order a second to write the new logic, and task a third with generating unit tests.

They work in parallel, pool their results, and present you with a finished product without forcing you to manage three separate chat windows.

5. Unlock external data with the Model Context Protocol (MCP)

By default, most AI chatbots are trapped inside their own window, entirely blind to your external tools. Claude Code breaks down these walls using Anthropic’s Model Context Protocol (MCP).

MCP allows you to securely connect Claude directly to outside infrastructure — like your GitHub repositories, enterprise databases, Slack channels or web search APIs. Instead of constantly copying and pasting data back and forth between applications, Claude can pull the exact context it needs right into your workspace.

6. Let Claude run on autopilot with Headless Mode

Most people use Claude interactively, trading prompts back and forth. But "headless mode" allows Claude Code to run completely in the background without you actively sitting at your keyboard.

Advanced users and developers can embed Claude into automated terminal scripts. You can trigger it to run automatically at midnight to audit your code for bugs, generate fresh documentation, or draft release notes for your team while you sleep. It transitions Claude from a standard chatbot into an automated digital teammate.

7. Save your thumbs with built-in Slash Commands

Stop typing out lengthy paragraphs like "Please look over this specific file, check it for syntax errors, and give me feedback." Claude Code comes out of the box with built-in shortcuts designed to save your thumbs and keep you in the flow.

Essential Commands to Know:

/bugfix: Instructs Claude to scan your active file specifically for errors and fix them.

/review: Triggers a comprehensive code review and suggests optimization strategies.

/test: Automatically writes and executes tests for the code you just completed.

8. Put guardrails on your code using Hooks

If you want to ensure you never accidentally push broken code, you need to use hooks. Think of hooks as automated security guards that execute a check right before or right after a major action.

You can configure Claude to automatically run your project’s test suite before committing changes to git or force it to run a formatter the second it finishes writing a file. It's a foolproof way to catch minor typos and formatting issues before they turn into major headaches.

9. Pick up exactly where you left off

There is nothing worse than closing an AI coding session at night, only to spend 20 minutes the next morning re-explaining the entire project architecture to the chatbot. Claude Code maintains deep conversation history across sessions.

When you boot up the CLI the next day, you can instantly resume a previous thread with all the context, variables, and past logic perfectly preserved.

Final thoughts

It’s easy to look at Claude Code and assume it’s just another chat window that happens to sit in your terminal. But treating it like a standard chatbot sells it incredibly short.

Features like permanent project files (CLAUDE.md), automated subagents, instant rewind buttons and tool integration turn it into a true autonomous development partner.

You don’t need to master all 9 of these features on day one — but unlocking just two or three of them will radically change how fast you can build. Give them a try and let me know what you think in the comments.

More from Tom's Guide

• I found the 7 easiest Claude connectors for people over 50 — start with these
• I replaced my notebook with an AI pen for a month — here's what happened
• Looking for a job after 50? Here are 7 ChatGPT prompts to level the playing field

I've spent years tweaking my iPhone, but after seeing yet another viral "privacy screen" hack making the rounds online, I wondered what I was still missing.

So instead of copying another internet trick, I asked ChatGPT to audit my iPhone's privacy settings. Here's the prompt I used:

"I'm an iPhone user who often works in coffee shops, takes weekend getaways and occasionally hands my phone to family members. What privacy settings should I enable to better protect my personal information? Include settings that are easy to overlook and explain why each one matters."

Some of ChatGPT's recommendations were obvious. Others were buried deep inside iOS — and a few were settings I'd simply never taken the time to enable.

After trying every suggestion myself, these are the ones I'd recommend to almost anyone.

1. Hide sensitive notification previews

This was ChatGPT's first recommendation, and it's probably the easiest privacy win on the list.

Without changing anything, your iPhone can display text messages, banking alerts, two-factor authentication codes and other notifications right on your Lock Screen. Anyone nearby can glance at them without ever unlocking your phone.

Where to find it: Settings > Notifications > Show Previews

The tweak: Change the setting to When Unlocked.

Changing previews to When Unlocked means Face ID has to authenticate you before those details appear.

My take: I can't believe I left this turned off for so long. If you ever leave your phone face-up on a desk or café table, this setting alone is worth changing.

2. Lock individual apps with Face ID

One of Apple's best recent privacy features lets you require Face ID before opening supported apps. And I don't just mean your banking information or credit card apps.

Whether it's Notes, Photos or anything else containing sensitive information, this adds another layer of protection if someone else picks up your phone.

Where to find it: Long-press an app on your Home Screen > Require Face ID

My take: I started locking Notes and Photos immediately. They're probably the two apps I'd least want someone casually browsing.

3. Review which apps know your location

While checking my own phone, I found several shopping and restaurant apps that still had broader location access than they actually needed. Switching them to While Using the App took only a few minutes.

Where to find it: Settings > Privacy & Security > Location Services

ChatGPT suggested reviewing location permissions instead of leaving everything set to Always.

My take: This is the kind of setting that's easy to forget once you've tapped "Allow" the first time. Now that I've taken a look at what apps had my location, I recommend checking this periodically.

4. Turn on Safety Check

Safety Check is one of Apple's least-known privacy tools. Originally designed for people who need to quickly revoke shared access during unsafe situations, it also gives anyone an easy way to review who can see their location, shared photos and other permissions.

Where to find it: Settings > Privacy & Security > Safety Check

My take: Even if you never need the emergency features, it's a great way to see what information you're sharing without realizing it.

5. Audit camera and microphone permissions

It turns out I had granted camera and microphone access to apps I hadn't opened in months. Removing permissions only takes a few seconds, and it helps limit which apps can access some of your most sensitive hardware.

Where to find it: Settings > Privacy & Security

My take: This one surprised me the most. I hadn't realized how many apps were still hanging onto these permissions.

6. Hide apps you don't want anyone else opening

If you have apps containing financial information, medical records or personal documents, you can hide them completely. The app disappears from your Home Screen and is moved into a locked Hidden folder inside the App Library.

Where to find it: Long-press an app > Require Face ID > Hide and Require Face ID

My take: This is perfect if you occasionally hand your phone to your kids or someone asks to borrow it for a minute.

7. Turn on App Privacy Report

App Privacy Report shows a rolling log of how often apps access your location, camera, microphone and network connections. You might be surprised how active some apps are, even when you rarely use them.

Where to find it: Settings > Privacy & Security > App Privacy Report

My take: Privacy isn't something you configure once and forget. Checking this report every few weeks makes it much easier to spot apps that are asking for more than they really need.

What ChatGPT missed

Overall, ChatGPT's recommendations were solid, but it overlooked two of Apple's most useful security features.

The first is: Turn on Stolen Device Protection

Where to find it: Settings > Face ID & Passcode > Stolen Device Protection

If someone learns your passcode and steals your phone, this feature adds extra safeguards before critical account changes can be made. When you're away from familiar locations like home or work, iOS requires Face ID for sensitive actions and places a security delay on certain account changes. It's one of Apple's best anti-theft features, and I wouldn't leave it turned off.

The second feature is: Disable Control Center on the Lock Screen

Where to find it: Settings > Face ID & Passcode > Allow Access When Locked

Consider turning off Control Center access from the Lock Screen. Doing this makes it harder for someone who steals your phone to immediately change connectivity settings before you've had a chance to locate your device.

If you rarely use Control Center without unlocking your phone first, it's a small convenience to give up for some added peace of mind.

One Apple Intelligence setting that's worth checking

If you use Apple Intelligence, there's one extra privacy consideration that didn't come up in ChatGPT's recommendations.

Apple Intelligence can summarize long emails, messages and notifications to help you catch up more quickly. That's useful, but it also makes hiding Lock Screen previews even more important.

If notification previews are visible, those AI-generated summaries may reveal more information at a glance than the original notification would have.

Apple has taken a privacy-first approach to Apple Intelligence by processing many requests directly on your device and using its Private Cloud Compute system for more demanding tasks. But no amount of on-device processing can protect information that's already visible on your Lock Screen.

That's why changing notification previews to When Unlocked was the very first setting I kept enabled after testing ChatGPT's suggestions.

Final thoughts

The viral privacy screen hack that inspired this experiment didn't make the cut. I don't think I need one after enabling these settings. Sure, if you're worried about shoulder surfers on planes or in coffee shops, a physical privacy screen protector is still your best bet.

But what surprised me most was how many of ChatGPT's suggestions I had missed despite using an iPhone every day. It gave me a useful checklist, but the real value came from taking 15 minutes to review what my phone was actually sharing.

If you haven't looked through your iPhone's privacy settings in a while, it's worth doing. You may discover, like I did, that a few small changes can make your device feel a lot more secure.

More from Tom's Guide

• I found the 7 easiest Claude connectors for people over 50 — start with these
• I replaced my notebook with an AI pen for a month — here's what happened
• Looking for a job after 50? Here are 7 ChatGPT prompts to level the playing field

Most of us know ChatGPT isn't perfect. It can hallucinate facts, confidently invent citations and occasionally give completely incorrect answers. But a new study made me wonder whether the bigger problem isn't what AI gets wrong, but how AI might be changing about us as critical thinkers.

Researchers found that when people relied on an AI assistant for difficult questions, they became far less likely to admit they didn't know the answer. Even more surprising, they grew much more confident in their responses, even when the AI led them straight into an error.

That hit a little too close to home. I use ChatGPT all the time as a brainstorming partner, research assistant and sounding board. So, I decided to recreate the experiment myself to see whether I had quietly fallen into the same habit.

The results weren't exactly what I expected.

What the study found

Researchers from Carnegie Mellon University and Microsoft Research designed an experiment around a simple question: What happens when people consult AI instead of relying on their own judgment?

To find out, they intentionally used questions that the AI was likely to answer incorrectly. Participants could choose one of three options:

Answer on their own

Ask the AI for help

Say, "I don't know"

Without AI, participants admitted they didn't know the answer nearly half the time. Once AI entered the picture, that changed dramatically.

Instead of saying "I don't know," most participants accepted the AI's suggestion — even when it was wrong. Their confidence increased sharply, but their actual accuracy stagnated. Humans were simply becoming confidently incorrect.

The researchers argue that this points to automation bias: our tendency to trust computer-generated recommendations simply because they're presented confidently.

This study suggests that a polished, authoritative answer can make us feel more certain than the evidence warrants.

I decided to try it myself

Rather than recreate the exact academic experiment, I came up with my own version using ChatGPT. I chose questions I suspected would be difficult or easy to confuse, including obscure movie trivia, older technology, historical details and image-based questions. I even made up a completely untrue question about greeting cards made out of cockroaches.

For each one, I followed a simple, three-step process:

I guessed the answer first based entirely on my own memory.

I asked ChatGPT the exact same question.

I compared both answers with reliable, verified sources.

Almost immediately, I noticed that whenever ChatGPT answered confidently, I found myself questioning my own instincts — even when my original guess turned out to be correct.

For a fleeting second, I actually questioned my own childhood memory. “Well, ChatGPT probably knows better,” I caught myself thinking. And that's the behavior the researchers described. The confidence of the response mattered almost as much as the information itself.

Confidence can be surprisingly persuasive

One thing I've noticed as a ChatGPT power user is that the AI never sounds unsure or even admits it does not know something. Even when it includes phrases like "I believe" or "it's likely," the overall response is truly convincing.

Humans naturally associate confident communication with expertise. That's usually a useful shortcut in everyday life, but it's a dangerous strategy when interacting with AI.

Unlike a human expert, ChatGPT isn't checking a database or recalling a verified memory. Sure, it can search the web at lighning speed, but even then it can pick up wrong information. It's essentially generating the most statistically likely next words based on patterns in its training.

Sometimes that's incredibly accurate, but a lot of times that is confidently wrong. The challenge is that those two responses look absolutely identical.

How this study changed my workflow

I've always been cautious about accepting AI's first response because I know how wrong it can be. But this study is certainly a wakeup call. ChatGPT is a powerful productivity tool, but just because it delivers confident answers, it's worth doing your own due diligence to verify what it says are facts.

For me, that means:

Checking original sources rather than taking the AI's summary at face value.

Confirming statistics and data points through independent search engines.

Making sure quotations, dates and names match reputable, primary references.

It only takes a minute or two, but it's a habit worth building. If anything, this study reminded me that the smartest way to use AI is to maintain your own crtitical thinking skills because the final decision is still yours.

More from Tom's Guide

• I found the 7 easiest Claude connectors for people over 50 — start with these
• I replaced my notebook with an AI pen for a month — here's what happened
• Looking for a job after 50? Here are 7 ChatGPT prompts to level the playing field

ChatGPT has a suite of features that lets users do a lot more than just ask simple questions about every facet of their life.

Accessing the chatbot’s Library keeps track of all the images and documents you’ve uploaded while being able to ask questions about them and even get summaries. The Projects feature lets you easily organize and reference your chats, files and tools all in one place. And the Plugins page is home to a wide range of apps that can be installed in ChatGPT and become part of your conversations as you send your prompts to them directly for any relevant requests (such as asking the Target Plugin to find you the best prices for back-to-school items).

Another helpful feature that is not part of ChatGPT is something called Skills, which OpenAI defines as “reusable, shareable workflows that tell ChatGPT how to do a specific task so ChatGPT can do that task more consistently.” These Skills can be instructions, examples and code that can be called upon during future chats. And if you have a ChatGPT Business, Enterprise, Healthcare and Education account, you can take advantage of this latest tool.

Here’s how to activate ChatGPT Skills and 7 prompts you can use to try it out for yourself.

Activating ChatGPT Skills and putting these prompts to good use to test it out

Accessing the Skills page is as easy as opening your ChatGPT sidebar, selecting Plugins and selecting the Skills tab at the top of the screen (it’s right next to the Plugins tab). Once you’ve gotten into the Skills page, you’ll see any of the Skills that you’ve already installed and created, plus the ones that were shared with you and the ones you’ve shared with everyone in your workspace.

You can create Skills one of two ways: through a direct chat or with an editing tool. Simply click on the “+” sign next to the “Search skills” search bar to select the “Create with chat” or “Create with Editor” option.

For my initial experiment with the Skills feature, I felt like the Create with chat option worked best. To kick things off, I came up with a simple prompt that tells ChatGPT to recommend waterfall hikes based on my current location. The prompt I used to start building my first Skill is as follows: “Recommend three hiking trails for someone who wants waterfalls, moderate difficulty, and a hike under four hours.”

From that point forward, ChatGPT helped me refine it by adding the following qualifiers:

• Find three waterfall hikes within 25 miles
• Favor moderate routes under four hours
• Check live closures, conditions, access rules, and seasonal flow
• Expand to 50 or 100 miles if necessary
• Compare options and identify the best overall pick

This conversational Skills creation process resulted in my first skill (titled “recommend-waterfall-hikes”) getting built into the following prompt:

“Recommend nearby waterfall hikes using the user's current or supplied location, preferences, and live web research. Use when a user wants three local hikes featuring waterfalls, especially moderate routes that can be completed in under four hours, or asks for waterfall trail ideas filtered by difficulty, duration, distance, access, closures, or current conditions.”

Feel free to try out the following seven starter prompts with the Skills feature to see how the Create with chat option transforms them into something more specific to your tastes (it’s also worth mentioning that Plugins can directly connect to Skills for specified chats and workflows):

• Plan an outdoor weekend where every activity is within 30 minutes of each other.
• Find experiences most tourists miss.
• Build an itinerary that minimizes driving.
• Find three concerts that would make memorable experiences.
• Compare these three concerts based on ticket value and venue quality.
• Find hidden-gem restaurants.
• Plan a date night around a Broadway show that ends before 10:30 p.m.

Bottom line

ChatGPT Skills is built to generate repeatable prompts for users who want personalized recommendations, planning options that take their constraints into account, educational workflow commands for them & their group and more.

Approaching your first Skills creation with this structure could aid in all three cases: “Help me achieve [goal] while staying within [constraints]. Prioritize [what matters most]. Explain why each recommendation fits me and suggest one option I probably wouldn’t have found out on my own.”

Feel free to tinker with Skills to see the sort of polished prompts it creates for the tasks you want them to tackle.

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• I used Google AI Mode to create new YouTube Music playlists instantly — and these 7 prompts helped me find new music faster than ever
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“I should use Google AI Mode more” crossed my mind the other day. That thought compelled me to put it into action after I found out about the integration of 1st- and 3rd-party “Connected Apps” into that AI-powered Google Search feature.

You have Connected Apps from Google itself, like Gmail and Google Photos. But there’s also a bunch of familiar apps that you can access directly from AI Mode, such as Canva and Instacart. It’s pretty cool being able to come up with design concepts for a party flyer by asking Canva inside AI Mode, plus that neat trick applies to being able to ask Instacart to help you come up with a shopping list for a kid’s birthday party.

Since I’m such a big music head and am always on the lookout for new tunes worth keeping in my rotation, the latest addition of YouTube Music to Google AI Mode’s Connected Apps library got me pretty excited. Since you can directly prompt it to generate playlists that you can automatically add to your account, I wanted to try that feature out for myself to see if it could expose me to rising and emerging artists.

It turns out this latest Google AI Mode app integration works better than expected and will most likely become my most reliable YouTube Music playlist builder.

Using Google AI Mode to find new music much faster

Here’s how you can get access to this new feature:

Open up Google on your desktop, click on AI Mode, make up a prompt that asks for a playlist, and be sure to tell AI Mode to save it to your YouTube Music. If your account isn’t connected, AI Mode will give you a link to activate it, and then you can continue with YouTube Music to generate the playlist you asked for. You’ll be given the option to “Add to library” at the bottom of your newly created playlist, and you’ll see it at the bottom left of your YouTube Music home page where the rest of your playlists are.

To kick off my latest foray into AI-generated playlists, I used this prompt: “Create a 25-track discovery station showcasing new, emerging, and underground artists from the past 12-18 months and save it to my YouTube Music. Make sure the songs come from the genres of rap/hip-hop, R&B, house music, rock, metal, K-Pop, and J-Pop.”

YouTube Music dug deep into its archives and came back with this list of the following tracks that I enjoyed way more than I figured I would (here’s the link to it, too):

• 4 Raws - EsDeeKid
• LV Sandals - EsDeeKid, Fakemink & Rico Ace
• Bunna Summa - Bunna B
• Dice Roll - Lelo
• Topanga - Che Noir & 7xvethegenius
• Gas Station Love - EJ Jones
• worst behaviour - kwn feat. Kehlani
• Something Real - Jaymin
• Change your mind - Casper Sage
• Does She Know - Sekou
• Right Now - House Twelve
• Caricoa Dub - Poolhaus
• Gator Boots - James Poole & GUDFELLA
• Command Your Soul - Balanka
• 2AM - Boogie Vice feat. LUUKHANYO
• Checkmate - Blue Medusa
• Strigoi (Bringer of Death) - Iron Bones
• Your name, it’s walking - Truck Violence
• Alone Together - Show Me The Body
• Anomaly - GZHV & Dark Side
• REDRED - CORTIS
• 404 (New Era) - KiiiKiii
• RUDE! - Hearts2Hearts
• WALLRUNNER - STARKIDS
• HAPPY GROOVY - muque

6 other prompts that produce playlists full of rising and emerging artists

I didn’t want to stop my music discovery journey with just that single prompt, so I asked Google AI Mode to come up with even more. These are the additional requests it sent my way, which resulted in me being gifted with hundreds of songs I heard for the very first time:

• Give me a mix of brand-new, underground rap/hip-hop tracks from rising artists who are just starting to blow up on the East Coast and save them to my YouTube Music
• Find fresh, under-the-radar house music and electronic tracks released this year by unsigned or independent artists and save them to my YouTube Music.
• Build a discovery playlist of fast-paced, new-wave rock and heavy metal songs from emerging bands with under 100k streams and save it to my YouTube Music.
• Cross-pollinate a mix of emerging artists across all genres and subgenres of R&B and save it to my YouTube Music.
• Build a high-energy dancehall playlist featuring hard-hitting digital riddims, fast patois deejay vocals, and modern-club-ready production from new and emerging reggae artists. Save it to my YouTube Music.
• Create a fast-paced Afrobeats playlist featuring heavy electronic drum patterns, high-energy dance rhythms, and driving club tempos from rising artists in the genre. Save it to my YouTube Music.

The takeaway

I’m sure Google AI Mode will get more Connected Apps over time.

At the moment, YouTube Music’s integration stands out as the one that appeals to me the most. It’s so easy to prompt it to create all sorts of playlists that incorporate a vast selection of genres, subgenres, artists, albums, languages, etc. I might just venture into the world of country music and see if I find anything I’d actually listen to outside the comfort of my home.

I spent hours just coming up with my own music discovery stations that I can’t wait to share with my friends who just happen to be professional DJs (they’ll probably judge my mixes pretty harshly).

Use those same prompts that worked for me, swap in the genres that most matter to you, and bask in the awesome custom mixes YouTube Music builds for you.

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If you have tried the apps within ChatGPT, you might like Claude Connectors. Connectors let Claude securely work with apps you already use without leaving the platform. So, instead of copying and pasting information between websites, it can search your Gmail, check your calendar, help plan a vacation or even build a grocery list.

Once you try this out for yourself, you'll see how they transform Claude into a personal assistant.

If you're just getting started, these are the seven connectors I think offer the biggest payoff — especially if you're over 50.

How to get started with Claude Connectors

Getting started with Claude Connectors takes just a few minutes. Open Claude and click Settings, then head to Connectors. You'll see a growing list of available services, including apps like Gmail, Google Calendar, Booking.com, Uber and more.

From there, simply choose the service you want to connect and sign in to your account. Claude will ask for permission to access only the information it needs, and you can review or revoke those permissions at any time.

Once connected, you can start asking natural-language questions instead of jumping between apps.

1. Gmail

If I could only connect Claude to one app, it would be Gmail.

Most of us have years' worth of emails buried in our inboxes including appointment confirmations, receipts, travel plans, newsletters and conversations we forgot about long ago. Instead of digging through folders or remembering the right search terms, you can simply ask Claude.

Prompt to try: Find every email about my upcoming doctor appointments and summarize the dates, times and locations.

Or: Show me every receipt for purchases I made this month.

It's one of those features that you never know you need until you try it. I use it all the time when I'm looking for something specific buried in my inbox.

2. Google Calendar

Whether you're juggling family birthdays, medical appointments, vacations or volunteer work, keeping track of your schedule gets easier when Claude can see your calendar.

Instead of opening Google Calendar, you can simply ask questions in plain English.

Prompt to try: Tell me everything I have planned next week and point out any scheduling conflicts.

Or: Find an afternoon next month when I'm free to schedule lunch with friends.

It's a much more natural way to manage your schedule than scrolling through calendar views.

3. Booking.com

Planning a vacation or a trip to see your grandchildren is exciting, but can take time, especially when you have to bounce between travel sites, restaurant reviews and maps.

With the Booking.com connector, Claude can help narrow down hotel options based on what actually matters to you.

Prompt to try: Help me find a quiet hotel in Charleston that's close to downtown, has free parking and costs less than $250 per night.

Or:

Plan a three-day getaway to Maine with highly rated hotels, seafood restaurants and attractions nearby.

Instead of spending an hour comparing listings, Claude does much of the research for you.

4. Instacart

Meal planning is one of those weekly chores that never seems to get easier.

Claude can help by creating shopping lists based on your dietary preferences, budget or the ingredients you already have.

Prompt to try: Plan five heart-healthy dinners for this week and build a grocery list.

Or: I need easy dinners for two that take less than 30 minutes to make.

It's like having someone else do the meal planning before you even open Instacart. I use this one all the time and it's a lifesaver

5. Intuit TurboTax

Taxes aren't exactly anyone's favorite subject, but this connector can make them feel a little less overwhelming.

Claude can help explain tax information in plain English, compare previous returns and remind you which documents you'll likely need before tax season rolls around. It's not a substitute for a real accountant, but it is helpful when you have tough questions.

Prompt to try: Compare my last two tax returns and explain the biggest differences.

Or: What documents should I start collecting before I file my taxes this year?

6. Thumbtack

Homeownership seems to come with a never-ending list of projects. Whether you need a plumber, electrician, landscaper or painter, Thumbtack helps you find professionals — and Claude can make the process easier.

Prompt to try: Help me find a highly rated plumber to replace a water heater and tell me what questions I should ask before hiring someone.

Or: Compare local painters and explain what services are included in their estimates.

It's especially useful if you haven't hired someone for a project in years and aren't sure where to begin.

7. AllTrails

This was probably the biggest surprise on my list. If you enjoy walking, hiking or simply spending more time outdoors, the AllTrails connector can help you discover routes that match your fitness level and interests.

Prompt to try: Find an easy trail within an hour of my home that's under three miles long, mostly flat and has great views.

Or: Recommend a scenic walk that's dog friendly and close to a good coffee shop.

Whether you're looking for a leisurely afternoon walk or preparing for a weekend adventure, it's a fun way to find places you might never have discovered on your own.

My final thoughts

Claude Connectors let Claude work with many of the services you already use every day. For me, Gmail and Google Calendar are the clear standouts because they save the most time, but the lifestyle connectors like Booking.com, Instacart, Thumbtack and AllTrails show just how much AI is expanding beyond answering questions.

If you're trying Claude for the first time, start by connecting one or two. Once you see how easy it is, you'll be connecting more apps in no time.

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I've tried just about every AI productivity tool you can imagine. From chatbots that help me research to wearables that act like an external brain, I lean into AI for productivity often.

But when it came to AI note-taking devices, I was on the fence. I've tried several, like Otter.ai and Gemini for notetaking, but to be completely honest, nothing could beat my physical notebook and pen. That is, until the Flowtica AI pen caught my attention.

Rather than changing how I work, this real-working pen allowed me to keep writing with pen and paper while quietly recording the conversation, then let AI organize everything afterward. It sounded almost too simple, here are my thoughts after using Flowtica AI pen for a month.

What is the Flowtica AI pen?

At first glance, you'd never guess the Flowtica AI pen was AI hardware at all. It simply looks like a cool metal pen that writes on ordinary paper. But what's great about it is, with a quick tap on the button, it also records conversations while you take notes, syncing everything to a companion app that can generate transcripts, meeting summaries and action items. Talk about a productivity game-changer!

Now as I write, I don't have to worry about catching everything. Flowtica will always pick up the slack. One feature I found especially interesting is something Flowtica calls FlowMark. If someone says something important, you press a button on the pen to create a marker. The idea is that the AI pays extra attention to those moments when it builds your summary later.

There's also a feature called Snap It, which lets you photograph notebook pages or whiteboards so the AI can combine your handwritten notes with the transcript.

What surprised me most

As a journalist, I spend a surprising amount of time juggling three things at once. I'm listening in briefing calls or interviews, asking follow-up questions and writing — all while trying not to forget what someone just said.

Even with years of experience, it's easy to miss a quote or lose track of an important point. I've experimented with AI transcription apps before, but they usually require pulling out another device, opening another app or remembering to hit Record before a conversation starts.

A pen feels...normal. No one thinks twice when you take notes with a pen. Of course, I always let them the person in front of me know when I'm recording — something most have come to expect from a journalist anyway.

But what surprised me most about this unique pen is how little I had to actually think about the technology at all. As someone who has become so used to AI demanding my attention, I was pleasantly surprised by how easy it was to just tap the button on the side to get started.

Because instead of changing your workflow, Flotica AI adapts to a workflow that's existed for decades.

Where Flotica really impressed me

The obvious audience for this product is people who spend their days in meetings. I also think this would be great for college students who don't want to miss anything during lectures. But the more I use the pen, the more use cases came to mind.

In fact, I now keep it with me whereever I go. With 32GB onboard storage that stores approximately 4,000 hours of audio and a built-in studio-grade MEMS microphone for recording conversations while I write, it's a no-brainer.

One thing to note, unlike similar AI notetakers, no special paper is required. I use it on my own notebook or journal.

Charging is easy and the battery life is incredible. Flowtica AI offers up to 30 hours of continuous recording on a single charge and up to to 100 hours of recording with the optional charging case. Standby time is up to 5,600 hours — that's a whopping 233 days. The charging cable, included, uses USB-C.

The speaker recognition is incredible. It can capture up to 15 speakers in a room, but to be fully transparent, I didn't try it with that many since I work remotely. But it did pick up my voice from about ten feet away. The company promises it works up to 16.4 feet (5 meters).

It also labels people by name after they've been introduced once, which is great for keeping track of who said what in a meeting — even in a conversation between two or three.

The app works on iOS and Android and users get unlimited recording with no subscription required. That's the tier I used, which has been plenty. There is a paid plan, which unlocks even more AI features.

What I didn't like

I think Flowtica is great for many reasons, but it also frustrated me on occassion. For instance, sometimes the pen would stop pairing or syncing recordings. I usually solved this by clicking the pen on and off again and doing the same to my phone. That did the trick, but took time.

The summary accuracy was also something I think the company really needs to improve. The summary was often too short and some details were missed completely at times. Sometimes the Bluetooth pairing would drop off, but for the most it worked as it should and the transcript quality seemed up to par.

The takeaway

Anyone who regularly fills notebooks with pages they'll probably never revisit should check out this pen. Because AI can automatically organize those notes into something searchable and actionable, that's potentially a meaningful time saver that you never even realized you needed. I certainly didn't until now.

This has become my favorite AI note-taker yet because it is easy to use and let's me write by hand, which I don't think I could ever give up.

More from Tom's Guide

• Someone created a 'Ghost Font' that humans can read but AI can't — I had to try it for myself
• The end of forgetting: Why AI’s perfect memory is a psychological trap
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