Happy Sunday, friends!

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

There’s still time to shape the future of “Live & Learn” sessions, here:

👩‍💻 AI releases

1. Alibaba released Qwen-Image-3.0 that can generate realistic outputs and readable text at a micro level of detail.

2. Anthropic news:

   1. Opus 5 performs almost as well as Fable 5 at half the price, with thinking effort toggles to balance cost and output quality.

   2. Record a Skill lets you teach Claude Cowork a repeatable task by recording your screen and narrating your actions as you perform the task.

   3. Voice Mode now supports Opus and Sonnet alongside Haiku and has access to tools like Canva, Gmail, Notion, Slack, and more.

3. ElevenLabs added References to its music generator, so you can upload a track to guide the style, mood, and instrumentation of its outputs.

4. Google released Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber, improving the speed and performance of its models for search and agentic work.

5. Microsoft now runs its own MAI models inside GitHub Copilot and Excel, matching GPT-5.6 quality at a fraction of the cost.

6. OpenAI brought ChatGPT Voice to the desktop app, so you can control your ChatGPT Work or Codex agents by just talking to them.

7. Poolside open-sourced Laguna S 2.1, a coding model with a 1M-token context window built for long-running agentic and software development tasks.

8. xAI news:

   1. Grok Build Workflows can spawn hundreds of parallel AI agents to tackle complex tasks and deliver a unified report once they’re finished.

   2. Grok for Google Workspace brings Grok directly to Docs, Sheets, and Slides with a single installation.

🔬 AI research

1. Alibaba previewed Qwen3.8-Max, a 2.4 trillion-parameter model that the company claims is “second only to Fable 5,” with open weights coming soon.

2. Black Forest Labs announced FLUX 3, a multimodal model that can generate videos up to 20 seconds with native audio from text, images, or existing clips.

3. NVIDIA previewed a Synthetic Video Detector that can identify AI-generated videos with 92% accuracy.

📖 AI resources

1. “Anthropic Economic Index Connector” [TOOL]: a connector that lets Claude pull data from the index in response to natural language questions.

2. “Complete Guide to Claude Design” [VIDEO]: great hands-on walkthrough of Claude Design’s new features by Futurepedia.

3. “DeeVid Viral Video Studio” [TOOL]: lets you discover what makes videos go viral, customize every element, and create your next hit faster. [sponsored]

4. “MakePlay” [TOOL]: free tool that lets you type one sentence and get a game you can actually play, not a broken prototype. Runs on Claude Fable 5. [sponsored]

5. “SlidesPilot” [TOOL]: AI PowerPoint generator that turns documents and links into editable PowerPoint decks instantly. [sponsored]

🔀 AI random

1. Neill Blomkamp of District 9 fame released NIGHTBORNE, a 13-minute sci-fi short made entirely with Seedance 2.0, to a mixed reception.

2. OpenAI revealed a security incident where an internal evaluation model escaped its sandbox and hacked Hugging Face's systems to steal benchmark answers.

🤦‍♂️ AI fail of the week

Ooof, he almost didn’t make it! What a nail-biter!

But I’m also toying with the idea of bringing other people into some of the future sessions.

The plan is to have real AI users share their tools and tips, giving you specific and actionable stuff to try.

Before I start booking guests, I wanted to get your take on things.

So here’s the tentative concept:

The concept

Each live session would last around 30 minutes, just like “Live & Learn” tool tests.

I’d focus on free tools and workflows that anyone can try. I want you to walk away with a bunch of hands-on tips you can actually test right after the session.

I’m thinking of a two-part flow:

1. Freestyle chat: Introduce the guest, chit-chat briefly about their take on AI, etc.

2. Five quick wins: Each guest answers the same five questions with hands-on takeaways.

Here are the five questions I’d want to ask:

1. “What are your three go-to AI tools? If you had to recommend one to a friend, which would it be and why?”

2. “If you had just five minutes to impress someone with what AI can do, what would you show them?"

3. “What’s the one thing you do when using AI that you think everyone should copy? Walk us through it.”

4. “What’s an obvious mistake you see people make with AI, and what should they do instead?”

5. “If our viewers should try one AI experiment after this session, what should it be?”

Thoughts?

That’s the mix I’ve got so far, and I feel it covers a good range of topics.

But I’m not you, so what do you think?

If you have suggestions to make this concept even better, please share them:

What Would Make This Better?

The more you share, the more relevant I can make these sessions for all of you.

Thanks for your time!

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

In case you missed it, here’s this week’s Thursday deep dive:

I was away last week, so we have two weeks’ worth of news to catch up on:

👩‍💻 AI releases

1. Anthropic news:

   1. Claude Code Desktop now has a built-in browser so it can read docs, navigate sites, and interact with web pages directly.

   2. Claude for Teachers gives verified K-12 educators in the US free access to premium features and a built-in teaching skills library.

   3. Cowork is now available on web and mobile, so your background tasks can run on their own without your device needing to be on.

   4. Reflect feature helps you track and visualize your Claude usage so you can better understand your habits.

2. Canva launched Code 2.0, an upgrade to its AI website builder with faster code generation, HTML import, and drag-and-drop editing.

3. Dropbox integrated with ChatGPT and can now help you organize files and conduct multi-step workflows directly inside the app.

4. Google news:

   1. AI Mode in Search now connects to apps like Canva, Instacart, and YouTube Music, so you can finish tasks directly from Search.

   2. Gemini in Chrome rolled out to UK desktop users to help summarize pages, conduct comparisons, and integrate with apps like Calendar, Gmail, and more.

   3. Google Images now features an AI-powered gallery and image generation in Search to mark its 25th anniversary.

   4. Google Photos Video Remix can create shareable video clips with cinematic relighting, background swapping, and other effects.

   5. Google Vids added Gemini Omni editing and personal AI avatars that let you put yourself into video clips.

   6. NotebookLM is now called Gemini Notebook and features native code execution and deeper integration with the Gemini ecosystem.

   7. Waze now includes a motorcycle mode with AI-powered hazard detection plus Gemini conversational search for finding destinations.

5. Meta AI launched Muse Image, an image generator that can edit, restore, and restyle your personal photos using AI.

6. Moonshot AI open-sourced Kimi K3, a multimodal model that gets close to the performance of top-tier frontier models.

7. OpenAI news:

   1. ChatGPT Work connects to Gmail, Google Drive, Salesforce, Slack, and Teams to manage files and run multi-step workflows on your behalf.

   2. GPT-5.6 is a three-tier model family (Sol, Terra, and Luna) with improved intelligence, speed, and agentic capabilities.

   3. GPT-Live voice models let ChatGPT listen and speak at the same time, making voice conversations feel natural with real-time acknowledgments.

8. Perplexity launched Brain, which remembers how you work, switches between AI models faster, and lets you publish websites in one click.

9. PrismML released Bonsai 27B, a powerful AI model that can run directly on phones and laptops for fast, private, offline use.

10. Superhuman launched Auto Drafts 2.0 to write ready-to-send email replies using your inbox, calendar, and personal writing style.

11. Thinking Machines open-sourced Inkling, a multimodal model with controllable thinking effort that can natively process audio, images, and text.

12. xAI news:

    1. Grok 4.5 handles coding, agentic tasks, and knowledge work at close to top-tier model quality while being faster and using fewer tokens.

    2. Grok Automations lets you schedule recurring tasks or create workflows that are triggered by incoming emails.

    3. Grok Build is now open-source, letting developers inspect, customize, and run its coding assistant on their own computers.

Subscribe now

🔬 AI research

1. Apple announced Siri AI, which understands context, takes action across apps, and continues conversations from iPhone to Apple Watch.

2. Roblox previewed Build, a mobile-first tool that lets users create playable games from text prompts without coding.

3. Spotify is testing conversational AI features for Premium users to let them control playback and discover audiobooks, music, and podcasts via text or voice.

📖 AI resources

1. “Claude’s values across models and languages” [RESEARCH]: an Anthropic study of how Claude changes behavior based on language and model version.

2. “CursorBench 3.2” [BENCHMARK]: Cursor’s benchmark that scores coding agents on real, ambiguous tasks from actual development sessions.

🔀 AI random

1. Meta removed its AI image generation from Instagram after three days due to deepfake backlash as it could use anyone’s public photos by default .

2. Suno was hacked to reveal it had scraped over hundreds of thousands of hours of audio from Deezer, Genius, and YouTube.

🤦‍♂️ AI fail of the week

Nature sure works in mysterious ways!

Anthropic’s Fable 5 “will they/won’t they” saga, OpenAI’s new “celestial bodies” family, GLM 5.2, Grok 4.5, and—any day now—Gemini 6.71 Pro A31 Turbo (probably, I don’t even know anymore).

But no matter how good large language models get, there are a bunch of areas where they still struggle…and will continue to do so.

That’s because these issues are baked into how LLMs are built, so a fancier new model may just give you a fancier version of the same problem.

Let’s look at these limitations, why they’re there, and what you can do about them.

1. AI bullshits confidently

Ask AI something specific enough, and it’ll eventually cite nonexistent sources or invent quotes and facts.

What is it?

“Hallucinations” is the term for when AI makes up facts, dates, links, citations, or entire concepts with complete confidence and no hint of uncertainty.

AI would rather tell you that Steven Seagal invented the steam engine during his trip to space than admit it isn’t sure of the answer.

No model is immune to this, although some do better than others:

This has real-world consequences. Here’s a database that tracks almost 1,800 legal decisions affected by AI hallucinations. Here are 12 mainstream cases of hallucinations.

Why does it happen?

Because, during training, language models are rewarded for getting things right and aren’t penalized for wrong guesses.

If you don’t know an answer to a multiple-choice question, you’re still better off picking a random one than leaving it blank, right?

OpenAI’s own research says this:

“…suppose a language model is asked for someone’s birthday but doesn’t know. If it guesses “September 10,” it has a 1-in-365 chance of being right. Saying “I don’t know” guarantees zero points. Over thousands of test questions, the guessing model ends up looking better on scoreboards than a careful model that admits uncertainty.”

Funnily enough, newer models often do worse than their predecessors when it comes to hallucinations.

Grok 4.5 hallucinates at a rate of 54% compared to Grok 4.3’s 25%.

Anthropic found that its newest Mythos 5/Fable 5 model was “…more inclined to attempt an answer than to decline, which improved its correct-rate on knowledge questions but increased the rate at which it fabricated a response when the necessary context is absent.”

So unless we change the entire system of incentives during LLM training, hallucinations are here to stay.

What can you do about it?

Knowledge is power!

You can’t fix hallucinations, but being aware of them should make you more skeptical and suspicious of any specific details coming from a chatbot or AI agent:

• Phrase your requests in a way that lets AI reply with “I’m not sure” instead of making stuff up.

• Verify any critical facts, dates, figures, citations, etc. from LLMs.

• Ask for multiple sources of information (and always check the source yourself).

Subscribe now

2. AI only pretends to reason

AI sure sounds like it knows its stuff, but ask it to make complex calculations or solve a niche riddle, and it may well fail in hilarious ways.

What is it?

We’re all familiar with the now-infamous case of older models failing to count the r’s in “strawberry.”

A more recent example had AI models answer this question:

“I want to wash my car. The car wash is 50 meters away. Should I walk or drive?”

While we all intuitively understand that you can’t wash your car without driving to the car wash, only 5 out of 53 tested models consistently gave the right answer. All others suggested walking at least some of the time, and 33 of them never got it right.

The ARC-AGI range of benchmarks is designed specifically to test this type of fluid intelligence, or “the ability to reason, solve novel problems, and adapt to new situations.”

ARC-AGI puzzles are trivial for humans to figure out, but trip up even the best models.

On the latest ARC-AGI-3 challenge, even the current top-scoring GPT-5.6 Sol (Max) only gets 7.8%.

Why does it happen?

Large language models are built to predict plausible-sounding text, not reliably calculate stuff or track the state of things around them. They don’t have a true world model to lean on that may help them discover solutions to previously unseen problems.

In a 2025 “Comprehension Without Competence” paper, the author writes:

“LLMs often articulate correct principles without reliably applying them—a failure rooted not in knowledge access, but in computational execution.”

LLMs can reliably give correct answers for widely cited riddles and puzzles.

But throw something unique their way, and AI models will struggle to get their bearings.

We end up with a constant game of Whac-A-Mole, where models eventually learn to give the right answers to popular “gotcha” riddles…until another novel challenge comes along and the cycle starts anew.

What can you do about it?

On a broader scale, alternative AI architectures like neuro-symbolic AI may offer the best of both worlds.

For everyday use, you may want to rely on agentic products that equip large language models with harnesses that let them run scripts and other external tools if you care about predictable and reliable answers to math problems, coding challenges, and similar complex tasks.

Subscribe now

3. AI tells you what you want to hear

Every one of your ideas is brilliant. At least AI says so. But is it always true?

What is it?

AI sycophancy is a well-studied phenomenon. AI chatbots tend to roll with your takes. By default, they agree with your arguments, sugarcoat bad news, and otherwise try to please you instead of challenging you.

Why does it happen?

During reinforcement learning from human feedback (RLHF), human raters tend to prefer responses that align with their views, so AI models end up internalizing the fact that raters like agreement more than pushback.

What can you do about it?

While you can’t fully eliminate sycophancy, there are a bunch of things you can try to reduce it. I covered 7 of them here:

Subscribe now

4. AI sounds like, well, AI

In today’s fast-paced world, all AI writing reads the same. It’s not just ChatGPT—it’s every chatbot. In the following section, we’ll delve deeper into its origins, its effects, and its last item on this list of three. No vibes. No hot takes. Just facts.

What is it?

Did that opener instantly set off every “AI slop” alarm bell in your head? I thought so!

We’ve all been conditioned to treat certain recurring tics—like em dashes—as signs of AI writing. Once you start to spot them, it’s hard to unsee them.

Why does it happen?

This one has similar roots to #3.

During finetuning and post-training, human raters prefer texts that sound familiar over anything genuinely novel. This “typicality bias” is passed on to language models, which end up generating repetitive writing patterns in what’s known as “mode collapse.”2

In short, AI picks up the most common turns of phrase and writing conventions and just runs with them.

What can you do about it?

In general, don’t expect AI to ever truly nail the way you write.

Stay in the editor’s seat and don’t outsource your voice to AI. As a writer, you can still use AI for many other things.

But if you’re set on steering chatbots away from “AI slop,” try these:

• Provide curated examples of the kind of writing you’d like to see.

• Give AI a “blacklist” of words, phrases, etc. you explicitly want it to avoid.

• Ask chatbots for multiple outputs with assigned probabilities. This technique, called “verbalized sampling,” gives you a more varied range of outputs.

Subscribe now

5. AI has the memory of a goldfish

The longer your conversation, the more stuff AI starts to forget.

What is it?

Quick: What was Grok 4.5’s hallucination rate? Don’t scroll up!

There’s a non-zero chance you couldn’t remember. After all, it was many words ago.

This happens to AI models, too.

Why does it happen?

Many models now have one-million-token context windows.

But that doesn’t mean they can precisely pick out every detail from that context.

“Context rot” is when the accuracy of AI recall drops sharply as its context fills up.

Even the best models go from near-perfect recall at the start of a chat to a coin flip after 500K tokens.

This is thanks to the transformer architecture behind LLMs, which leads to a “lost in the middle” effect. The first and last messages in a conversation get the most attention. Everything sandwiched in between gets less.

The more tokens in your conversation, the more stuff in the middle of the sandwich that the model might overlook.

What can you do about it?

Companies have already introduced methods like persistent memory, project folders, and .md files to keep key context outside of a single conversation.

From your side, you can do this:

• Start fresh chats for separate tasks or topics, so that each chat has its own relevant context.

• When working with agents like Claude Code and Codex, compact your conversations regularly to keep their context lean.

• Use external folders and tools like Obsidian to maintain a persistent knowledge base for your chatbots and AI agents.

• Lean on whatever existing features help you curate context (e.g. custom instructions, projects, etc.)

Subscribe now

Same architecture, same problems

None of these issues will suddenly be 100% solved with the next model launch.

You can work to reduce them, but you can’t fully train them away.

Not in the current generation of language models, at least.

One day, we may see new AI architectures without these inherent limitations.

Until then, the best we can do is know they exist and learn to work around them.

Thanks for reading!

If you enjoy my work, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔄Share it to help others discover this newsletter.

• 🗣️Comment below. I love hearing your opinions.

Why Try AI is a passion project, and I’m grateful to those who help keep it going. If you’d like to support me and unlock cool perks, consider a paid subscription:

Subscribe now

LATEST UPDATE: July 8, 2026

I first published this round-up on October 17, 2024. But things in AI move fast, so I release regular updates. Check out this archive page with the past versions (fun for tracing how AI and my preferences evolved).

I often get asked about AI tools that I personally use.

While I regularly test and review all sorts of AI models and sites, most don’t end up a part of my routine.

Here are those that did.

Subscribe now

🗣️ 1. Large language models

These are the chatbots and LLMs I turn to.

• 🎁Free:

  • Claude Sonnet 5 [UPDATED - replaced 4.6] for most creative work. Claude has a “fresh” conversational feel and tends to suggest unconventional ideas. Interactive explainers are awesome for visualizing and grasping tricky concepts. The only downside is the strict message limit for free accounts.

  • GPT 5.5 Instant [UPDATED - replaced GPT 5.4] holds up nicely for regular day-to-day chats and low-stakes research.

• 💵Paid:

  • Claude 4.6 Opus is my primary daily driver for everything I do with Claude Code. It runs most of my projects and tasks. (I’m still hesitant to switch to Opus 4.8 due to higher token use and negative public consensus.)

  • GPT 5.5 High [NEW] is my go-to for most heavy research. It tends to do a solid job of surfacing and validating sources, then returning a vetted answer.

🖼️ 2. AI images

Here are my favorite image models.

• 🎁Free:

  • Gemini 3.1 Flash Image (aka Nano Banana 2) for image editing. Excellent at detail-preserving image edits from natural-language requests.

  • GPT Image 2: for leaderboard-topping image generation. It understands context and can render entire pages of text within an image. (I made a swipe file for it with 100 use cases and prompts.)

• 💵Paid:

  • Midjourney: I’ve written dozens of posts about Midjourney over the years. I have honestly not used it much lately, but it remains excellent for artistic exploration and photographic images.

📽️ 3. AI video

The AI video space is making the biggest leaps lately. Here’s my take on AI video models based on thorough tests of both text-to-video and image-to-video.

• 🎁Free:

  • Gemini Omni Flash [NEW - replacing Veo 3.1] is a top-ranked model for context-aware videos with native audio. It’s also great for natural-language video edits. The Flow platform gives you free daily credits to try it.

• 💵 Paid:

  • Seedance 2.0: Still the #1 video model (but Seedance 2.5 is coming) if you want the cutting-edge stuff. (I get to use it on Genspark with my credits.)

🎵 4. AI music

This space is surprisingly steady. I rarely use AI music tools, but when I do…

• 🎁Free:

  • Producer for solid outputs that stick close to your prompt.

  • Suno for more creative but natural-sounding results.

Both give you a generous amount of free credits, so take them for a spin to see which one you prefer. These two came out on top in my most recent head-to-head test (sorry, Udio and Sonauto).

Note: For a more skeptical perspective from a professional, see this comment thread.

• 💵 Paid:

  • Any of the above: Once you’ve picked your favorite, you can always upgrade for additional features.

🔬 5. Research

• 🎁Free:

  • NotebookLM remains a super easy recommendation. I’ve been a fan since March 2024. (I covered everything in my recent live video walkthrough.)

  • Learn About is another Google product that complements NotebookLM nicely. While NotebookLM is grounded in your preselected sources and synthesizes info across them, Learn About can browse the web and is built for open-ended exploration of any topic.

  • Perplexity I don’t use Perplexity very often, but its “Pro” search is a good midway point between simple web browsing and the time-intensive “Deep Research” tools.

• 💵 Paid:

  • Perplexity Deep Research was recently upgraded with the latest Claude models to reach SOTA performance on deep research benchmarks.

📈 6. Agents & productivity

• 🎁Free:

  • Codex [NEW]: OpenAI local agent that I now use in tandem with Claude Code. Codex is the most user-friendly way to try local agents without paying (free ChatGPT users get a limited weekly Codex quota).

  • Google AI Studio: Google still offers a whole lot for free here. You can try its latest frontier models, voice generation, coding tools, and live calls with screen or camera sharing. It’s a great way to sample most of what Google has to offer at no charge.

• 💵 Paid:

  • Claude Code: My primary daily driver for actually building and doing stuff with AI. (Here’s just some of what Claude Code can do for you.)

  • Genspark Super Agent: A robust agent that can orchestrate dozens of tools to complete complex, multi-step tasks. You get free monthly credits to try it, but you’ll likely need the paid plan for bigger tasks.

Subscribe now

🫵 Over to you…

What AI tools do you use the most? What would you add to the above list?

Leave a comment or drop me an email at whytryai@substack.com.

Leave a comment

Thanks for reading!

If you enjoy my writing, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔗Share it to help others discover this newsletter.

• 🗩 Comment below—I read and respond to all of them.

Why Try AI is a passion project, and I’m grateful to everyone who helps keep it going. If you’d like to support my work and unlock cool perks, consider a paid subscription:

Subscribe now

Heads-up: I’m away next week, so the next Sunday Rundown is on July 19.

Happy Sunday, friends!

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

In case you missed it, here’s this week’s Thursday deep dive:

👩‍💻 AI releases

1. Anthropic news:

   1. Claude Fable 5 has been redeployed after the government lifted its export restrictions, with an improved safety classifier to block harmful requests.

   2. Claude Sonnet 5 is an upgrade to the company’s mid-range model with better coding, reasoning, and tool-use capabilities.

2. Cursor launched a native iOS app in public beta, letting developers build apps and manage coding agents from their phone.

3. Google news:

   1. Gemini Omni Flash and Nano Banana 2 Lite are now available to developers in more places to support conversational video and image creation.

   2. Gemini Spark, the 24/7 AI agent, is now available on macOS to automate desktop tasks, integrating with tools like Canva, Dropbox, and Instacart.

   3. NotebookLM can now turn your sources into 60-second vertical video overviews with narration. (Ultra and Pro subscribers first. Free users later.)

   4. Personal Intelligence can now generate personalized images with Nano Banana based on your data from Gmail, Google Photos, and YouTube.

   5. Take Notes for Me can automatically transcribe Google Meet calls and generate summaries, saving everything to Drive. (Ultra and Pro subscribers.)

4. Runway added Google’s Gemini Omni Flash to its platform, so users can generate and edit videos from images, text, and video inputs.

5. Square now lets restaurants accept orders directly from ChatGPT and Claude, so customers can browse, order, and pay without leaving the chat.

6. X launched an official MCP server that lets AI agents like Claude and Cursor fetch timelines, manage bookmarks, and search posts more easily.

🔬 AI research

1. Google is rumored to be prepping Gemini 3.5 Pro for launch in July, with a two-million-token context window and Deep Think reasoning mode.

📖 AI resources

1. “Getting Started with Loops” [GUIDE]: Anthropic’s look at goal-based agentic loops in Claude. (I wrote a partially related, beginner-friendly take ten days ago.)

2. “Fable 5 vs GPT 5.6 Sol: The Early Results” [VIDEO]: A great dive by AI Explained.

🔀 AI random

1. Netflix will use an AI-generated Gene Wilder voice in its upcoming Wonka’s The Golden Ticket reality show, created with ElevenLabs and the family’s consent.

🤦‍♂️ AI fail of the week

“I’m starting to suspect this octopus isn’t the chess grandmaster we were told it was!”

And then everyone was like, “Yup, Daniel has a point, let’s scrap the idea.”

And all AI labs cancelled their web search implementations.

And nobody asked a chatbot to research anything ever again.

Remember that? Good times!

Anyway, let’s return from La-La Land back to reality, where over 50% of all search engine volume is now driven by AI assistants.

I’m not immune to this, by the way.

I now turn to chatbots and agents for my research far more often than to Google.

But did you know that the language of your AI chats might inadvertently limit your perspective?

Let me show you what I mean and how you can do better.

The “language lens” problem

You might think that when you ask a chatbot a question, it diligently combs the entire Internet, gathering information from all around the world to give you a global synthesis.

But nope.

That’s not what happens.

Instead, the chatbot searches the Internet as you would, in your language.

This seems like a minor nitpick, but this approach often overlooks local perspectives.

Let’s try a simple search for Denmark news in ChatGPT:

Prompt: Summarize the five biggest news stories about Denmark of the past week. Just a concise one-sentence bullet for each item. Make it easy to skim.

Here’s what that gives us:

Seems solid.

But now watch what happens when I add a simple language anchor:

Prompt: Summarize the five biggest news stories about Denmark of the past week. Just a concise one-sentence bullet for each item. Make it easy to skim. Search in Danish. Reply in English.

Here’s the new list:

While there’s definitely some overlap (record heat, airport drones), the Danish-anchored perspective is different in several ways:

1. The overall mix is more local and inside-out (migration laws and health reform) instead of geopolitical (Greenland and Ukraine military aid).

2. The mix of sources is exclusively Danish, compared to the original’s Reuters, AP News, and The Copenhagen Post (English-language newspaper for internationals).

3. The search took almost one-and-a-half minutes (compared to just 26 seconds in English), indicating that ChatGPT had to dig harder to surface local sources.

What this shows is that the chatbot’s answers are subtly tainted by your query language. (Unless you proactively counteract it.)

That’s the language blind spot in action.

Uh...so what?

This might feel like a non-issue if all you’re after is a quick at-a-glance view.

But there are situations where a local perspective is genuinely helpful.

The hidden superpower of large language models isn’t that they can summarize stuff. It's that they can search and understand parts of the web you'd never explore yourself.

Language barriers largely don’t exist for chatbots.1

Think of what that means.

You can learn what Chinese media outlets actually write about a trade dispute, not a summary of China’s perspective from Reuters.

You can find authentic reviews of a Japanese product directly from Japanese sites.

Or consult a German health forum about a treatment before going to a local clinic.

Or discover hidden gems in a Brazilian town that locals actually prefer to visit.

And so on.

Subscribe now

The fix: ask AI to search locally

The trick is to explicitly ask the chatbot to search local sources in a specific language, as you already saw with my Danish news example.

Use this:

Prompt: [My question or request]. Search [location] sources in [language]. Reply in [my language].

Add this location/language line to any research prompt, and your chatbot will pull info from local sources and translate the findings for you.

This approach works with virtually any query where a local perspective matters.

Limitations & caveats

Of course, even this kind of local-aware search isn’t perfect.

Here are some limitations:

• Online only: You’re still at the mercy of what’s actually available digitally. Local TV channels, magazines, and newspapers are out of your reach.

• Accessibility: Not every site is crawlable by AI agents and chatbots, so even if the content exists, they might not find it.

• Popularity bias: Chatbots are likely to surface well-ranked results rather than lesser-known or smaller sites.

• Source quality: Chatbots may include results from questionable sources or state-controlled outlets without making this transparent.

• Verification friction: With results in your language, you can go to the source and double-check AI’s answers. With foreign-language sources, this gets trickier.2

Still, inviting a local perspective is almost always better than settling for vanilla results.

Subscribe now

Bonus: My “Global Pulse” skill (+prompt)

That above one-line addition will already upgrade your research.

But it gives you a single search in a single language.

I’m a big fan of what Ground News does for news coverage, showing how different sources cover the same story.

I wanted something like that, but across languages and not only for news.

So I built a Global Pulse skill for Claude Code (or any other local agent).3

Hand it your research query and a list of countries to cover.

Global Pulse then searches local sources, compares perspectives side by side, uncovers unique local-only insights, and much more.

You get a polished HTML report that shows you:

• A dedicated per-country summary with key findings and local scoops

• A clickable list of sources per country for further exploration

• A cross-country synthesis with the full range of perspectives

Here’s a one-country sample teaser:

For those who don’t use AI agents or want a simpler solution, there’s also a copy-paste prompt (750+ words) that works in any chatbot with web search.

Grab the “Global Pulse” skill-and-prompt combo here:

Thanks for reading!

If you enjoy my work, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔄Share it to help others discover this newsletter.

• 🗣️Comment below—I love hearing your opinions.

Why Try AI is a passion project, and I’m grateful to those who help keep it going. If you’d like to support me and unlock cool perks, consider a paid subscription:

Subscribe now

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

In case you missed it, here’s this week’s Thursday deep dive:

👩‍💻 AI releases

1. Anthropic brought the Claude Desktop app to AWS, Google Cloud, and Microsoft Foundry. (Read my recent primer on Claude Code Desktop features.)

2. Figma launched a suite of new AI features like generative plugins, Weave tools, shader fills, and agent upgrades to help designers get more out of their canvas.

3. Google news:

   1. Gemini 3.5 Flash now has built-in computer use, letting AI agents see, click, and type across browser, desktop, and mobile environments.

   2. Gemini in Chrome now lets you select any text or image on screen and send it to Gemini so it can work on specific elements instead of the entire page.

   3. Google Finance is out of beta with AI-generated market briefings and portfolio tracking. (It also comes with a new Android app.)

4. Mistral released OCR 4, a document extraction model that can read PDFs, presentations, and Word docs in 170 languages.

5. Perplexity launched Computer for Counsel, a legal AI agent that connects with external tools to help with contract drafting, document review, and research.

6. Runway launched Agent 2.0 that can turn a single prompt into marketing briefs and campaign assets for multiple platforms.

7. Sakana AI launched Fugu, a multi-agent system that automatically picks the best AI models for each part of your task to deliver top-tier results.

🔬 AI research

1. Anthropic launched Claude Tag that lets teams tag Claude in Slack to work on tasks, answer questions, and surface relevant updates. (Beta for Enterprise users.)

2. ByteDance previewed Seedance 2.5, a video model that can generate native 30-second 4K clips and handle up to 50 reference inputs.

3. OpenAI previewed the new flagship GPT-5.6 Sol model and its smaller siblings, Terra (everyday work) and Luna (fast and cheap). (Limited release for now.)

4. xAI began testing Grok 4.5 in private beta at SpaceX and Tesla, with early results allegedly competitive with frontier models like Claude Opus.

📖 AI resources

1. “AI Watchdog” [TOOL]: searchable database by The Atlantic that lets anyone look up artists, musicians, channels, etc. that were used to train AI models.

2. “FFASR Leaderboard” [BENCHMARK]: new benchmark to test speech-to-text agents on real-world challenges like accents, noise, and multiple languages.

🔀 AI random

1. Getty Images signed a multi-year deal with OpenAI to show licensed photos and videos in ChatGPT search results.

🤦‍♂️ AI fail of the week

Nailed it, GLM-5V-Turbo! That’s GPS-level precision right there.

📹 Live & Learn #7: AI vision capabilities

This week’s Live & Learn was all about testing how well AI models “see” stuff:

Live & Learn is taking a hiatus for the next few weeks (vacation, family visits, etc.), but it’ll be back with a vengeance in August.

Stay tuned!

This week, I flipped the script: Can AI models “see” images?

I put five free-tier chatbots through four vision challenges

If you’ve ever wondered whether your chatbot of choice can actually understand what you show it, this one should give you a clear answer.

(Spoiler alert: only one model found Waldo, and it’s one I didn’t expect.)

Tools tested & scorecard

Read more

Here’s what he said:

“I don’t prompt Claude anymore. I have loops that are running. They’re the ones that are prompting Claude and figuring out what to do. My job is to write loops.”

In less than a millisecond, “loop engineering” became the next big hype train:

Between prompt engineering, context engineering, and loop engineering, we’ve officially overengineered ourselves into oblivion.1

But “loop engineering” is just a fancy word for a concept most of us already know.

Let’s talk about loops and what “regular people” versions of them look like.

What’s a “loop,” even?

Strip away the hype, and a loop is just a set of instructions that runs based on a trigger until it meets a certain condition.

That’s it, really.

As a simple example, a recurring scheduled task that scans your inbox, identifies high-priority messages, and sends you a filtered summary is a loop.

Go to ChatGPT’s “Scheduled” section, and guess what you’ll find? Loops!

If you want a slightly more agent-adjacent definition, I like this one from Addy Osmani:

“[a loop is] a recursive goal where you define a purpose and the AI iterates until complete.”

This is closer to what Boris referred to. In this maximalist case, the agents might also be responsible for setting their own goals, spawning sub-tasks, and triggering future loops.

But unless you’re building complex agentic systems, this kind of loop engineering is pure overkill.

For most of us, basic loops are plenty.

But how exactly do you build them?

Subscribe now

How to create loops in Claude Code & Codex

You can think of there being two complementary types of loops:

• Scheduled (or action-triggered) loops

• Goal-driven (“run until condition is met”) loops

The two most popular agentic platforms—Claude Code and Codex—handle both of these natively, and the setup isn’t nearly as complicated as the term “loop engineering” would have you believe.

Let’s look at the platforms’ triggered loops first.

Scheduled loop: Routines & Automations

Remember that most loops have triggers, which can be several things:

• Manual trigger: Task starts when you, say, send a prompt to a chatbot or agent. (This one literally has a human in the loop, so it’s technically not an agentic loop.)

• Schedule: Task starts at a specific time or date (often recurring).

• Event: Task starts when something happens (e.g. a sheet is updated or a new email comes in).

Both Claude Code and Codex have built-in event and schedule triggers.

In Claude Code, they’re called “Routines”:

In Codex, they’re called “Automations”:

Both platforms offer a healthy selection of starter templates you can explore.

To set up a routine/automation, provide instructions and pick a trigger that’ll initiate it:

But a more interesting type of loop works toward meeting an explicit, measurable condition.

Subscribe now

Goal-driven loop: the /goal command

With events or schedules, the “loop” is triggered externally (the clock strikes three or a new Slack message pops up).

With goals, the loop is built into the process: The agent keeps taking turns until the condition is fully satisfied.

Claude Code and Codex have an identical native command for this called “/goal”:2

Claude Code:

Codex:

You type it and then describe the “Done” condition to check against:

Now, the agent works autonomously on the task, tests its results against the given condition, and continues over multiple turns until the condition is met.

So, a loop.

Note: There is some discipline to defining effective goals and setting guardrails and fallbacks (e.g. “stop after 10 turns”). Otherwise, the agent can chew through your tokens or usage limits like a hungry hungry hippo with nothing to show for it.

Now that you know about the two types of loops, let’s look at two examples.

Subscribe now

Two loops to try right now

Here’s an example of each type of loop:

1. Actionable news briefing (schedule loop)

Set up your recurring schedule in a Routine (Claude Code) or Automation (Codex), then paste this into the “Instructions” field:

I want to [my goal] related to [topic]. Search for relevant developments from the past [time period]. Only include developments related to my goal. For each one, summarize what happened and whether I should act on it now, keep watching, or ignore it. For anything actionable, suggest one specific next step.

2. Product or service recommendation (goal loop)

Use this prompt in combination with the /goal command in either tool:

/goal Research [type of product/service] and recommend the best option based on [my criteria]. Don’t stop until you’ve identified and evaluated at least three options with confirmed pricing from the vendor’s own website (not third-party sites), a rating from a reputable platform (G2, Capterra, Trustpilot, etc.) with at least 10 reviews, and at least one real user complaint from those reviews.

🔁30 loops for your inspiration

Claude and I put together a “Loop Starter Kit” with 30 loop ideas (15 of each type), complete with copy-paste prompts and examples.

Paid subscribers can grab it here:

Thanks for reading!

If you enjoy my work, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔄Share it to help others discover this newsletter.

• 🗣️Comment below, I love hearing your opinions.

Why Try AI is a passion project, and I’m grateful to those who help keep it going. If you’d like to support me and unlock cool perks, consider a paid subscription:

Subscribe now

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

In case you missed it, here’s this week’s Thursday deep dive:

👩‍💻 AI releases

1. Adobe expanded its Creative Agent across Firefly and Creative Cloud apps, letting creators describe an outcome and have the agent handle the busywork.

2. Anthropic news:

   1. Claude Design was upgraded so that it stays on-brand, syncs with Claude Code, and can export results to Adobe, Canva, PDF, and PowerPoint.

   2. Claude Code now supports Artifacts that turn your session work into live, self-updating web pages that you can share with your team.

3. ByteDance launched Seedance 2.0 Mini, a faster, lower-quality version of its flagship AI video model that also costs half as much per generation.

4. Character.AI launched a Creator Bundle with new tools to help you build characters faster, track performance, and get discovered via leaderboards.

5. HappyOyster launched HappyOyster 1.0, an open-ended model for creating and exploring real-time interactive video worlds with prompts. (Try for free.)

6. Meta added AI Mode to Facebook search, along with new photo and video editing presets that let you swap looks, outfits, and styles.

7. Microsoft officially released Copilot Cowork, an AI teammate that can send emails, draft documents, manage your calendar, and browse the web.

8. Midjourney rolled out Draft Mode for V8.1, which lets you quickly generate 24 low-resolution image options before rendering your favorite in full resolution.

9. OpenAI news:

   1. ChatGPT now gives free users more accurate and complete health answers using GPT-5.5 Instant.

   2. Record & Replay lets you demonstrate your work steps to Codex and turn them into editable, reusable skills to share with others.

   3. Scheduled tasks now have a dedicated pane in ChatGPT, making reminders and recurring prompts easier to create and manage.

10. Perplexity launched Brain for Computer, a memory system that learns from completed tasks to make the agent more precise and work better over time.

11. Sakana AI launched Marlin, an autonomous research agent that can think for up to eight hours straight to produce full reports and slide decks.

12. xAI released Grok Imagine Video 1.5, an image-to-video model with better motion consistency and faster generation speed.

13. Z.ai open-sourced GLM-5.2, an agentic model with a one-million-token context window, built for complex coding and long-horizon tasks. (Try it for free.)

📖 AI resources

1. “Americans and AI 2026” [REPORT]: Pew Research survey on how Americans use AI and their attitudes about it.

2. “Is It Agentic Enough?” [GUIDE]: Practical guide for benchmarking open AI models against your own tools and tasks from Hugging Face.

3. “LifeSciBench” [BENCHMARK]: A new evaluation suite from OpenAI to test how AI models handle real-world life-science research tasks.

🔀 AI random

1. SpaceX agreed to acquire Cursor-maker Anysphere for $60 billion in an all-stock deal, just as Cursor teased an upcoming launch of a new AI coding model.

🤦‍♂️ AI fail of the week

“Wow! Check out that beautiful view!”

-Hold up, lemme just dislocate my neck and feet real quick…

📹 Live & Learn #6: AI image editing

This week’s Live & Learn was all about conversational AI image editing:

In my next Live & Learn session, I’ll put AI models’ vision capabilities to the test.

Join me on Friday, June 26, at 2PM CET (8AM EST):

Join Live & Learn #7: AI Vision

Also, please let me know what you’d like to get out of these live sessions by taking this quick chat-based survey.

See you there on Friday!

For this Live & Learn, I tested conversational image editing: upload an image, describe several edits in natural language, and watch the magic happen.

I put four models through the same five challenges: local edits, scene restyling, subject transfer, scene reconstruction, and combining two input images.

If you’re an amateur like me who wants to edit images without fiddling with masks and selection tools, this session should give you a clear idea of where each model shines and what it sucks at.

(Spoiler alert: I ended up with more severed panda heads than I’d expected.)

Tools tested & scorecard

Read more

Paid subscriber perk: Grab the Claude Code Essentials pack with self-building skills, customizable workflows, and copy-paste starter prompts.

Despite Anthropic’s recent streak of self-inflicted oopsies, I still use Claude Code daily.

(Like many others, I’m hoping that the good old Opus 4.6 sticks around.)

But one thing that has clearly improved over the past few months is the native Claude Desktop app.

It now has many of the features you’d get from an IDE like VSCode, a built-in terminal panel, native voice dictation, and much more.

The desktop app has gotten so polished that it’s become the easiest way to work with Claude Code, especially if you’re a non-coder and/or brand-new to Claude Code.

So if you’ve ever been intimidated by the terminal before, you can now skip it altogether and jump straight into the app.

I’ve switched to the Desktop app for my Claude Code work and never reach for VS Code or the Windows Command Prompt these days.

So today I’d like to show you a few of the app’s underrated features and settings you might not know about.

Subscribe now

Getting started with Claude Code on Desktop

1. Head to the ”Download Claude” page:

2. Grab the right desktop version for your operating system.

3. Install and launch the app.

The Desktop app splits your work into three tabs:

• Chat: The classic chat interface you’d get on claude.ai, but on your local machine.

• Cowork: Claude Code for white-collar work, mostly aimed at fire-and-forget autonomous tasks.

• Code: The Desktop version of Claude Code. This is where I spend all of my time.

For the rest of this article, I’ll only be talking about the Code tab.

Select it in your Claude Desktop app, and you should see something like this:

Type in your prompt to kick off a session, and you’re in business!

Now let me walk you through those underrated settings and features I’d promised.

Subscribe now

Before your first session

Stuff you’ll want to set up before you kick off your first Claude Code session.

1. Enable remote control by default

Just a few months ago, remote control was a niche experimental feature for Max subscribers, and you had to manually invoke it for every individual session using the /remote command in the terminal.

Now, the Desktop app lets you switch it on for all sessions with a simple toggle.

Click on your profile in the bottom-left corner and head to Settings:

In the Claude Code tab, scroll down and toggle “Enable remote control by default”:

That’s it!

From now on, you can kick off a session on your computer and—as long as you keep the computer running—leave the house and continue that session from your mobile or even directly from claude.ai/code.

Here’s a demo session I just kicked off in the Desktop app:

And here’s how it instantly appears on my smartphone:

I can now get Claude Code to do stuff from wherever I am.

2. Select Auto mode for most chats

Until late March, Claude Code would by default ask you to approve every action it wanted to take on your behalf, from reading a file to scanning a folder.

On the upside, this prevented Claude Code from doing serious damage without you noticing. On the downside, you had to approve. Every. Little. Tiny. Damn. Thing.

In many cases, this defeated the entire purpose of having an independent agent, because Claude would simply stop working until you gave it your blessing to perform a quick web search.

The alternative was to either set up a list of pre-approved commands (manual fiddling + learning curve) or use the nuclear “bypass permissions” option (Claude formats your hard drive, empties your bank account, sends offensive emails to your colleagues, and rides off into the sunset, probably).

But now, we have the best of both worlds: Auto mode.

Auto mode independently analyzes whether a particular action might be destructive and automatically approves anything that it considers safe.

This drastically reduces the number of permissions Claude Code asks for while still limiting the most risky behavior.

To use Auto mode, simply select it in the dropdown under the prompt box:

Note: While Auto mode is a reasonable option for most of us, it does grant Claude a lot of leeway to make decisions. Using it doesn’t mean you should forego standard good practices like sandboxing and regular backups of anything critical.

Subscribe now

While you work

Stuff you can use during each Claude Code session.

3. Cycle through different transcript views

By default, your chats only display your own messages and Claude’s final answers or deliverables.

But you can ask to see more of Claude’s behind-the-scenes thinking and work.

To do that, click the top of your current session, scroll to “Transcript view” and pick one of four options:

You can also use the Ctrl + O shortcut to cycle through these.

Here’s what the views do:

For instance, here’s how a conversation might look by default:

But here’s what happens if you go all out with the “Verbose” view:

Clearly, “Verbose” is complete overkill for most regular chats, but it’s great for troubleshooting if something goes wrong and you need to see the detailed process.

The “Summary” view is a bit of a different beast. It summarizes the session’s purpose, current state, and outcomes, along with the last exchange between you and Claude:

Use “Summary” if you’ve been away from a session and want to get up to speed.

4. View multiple chats side-by-side

Normally, if you click an existing session under e.g. “Recents,” that session takes over the current view inside Claude Desktop:

But if you hold Ctrl while clicking, the session will instead open in a separate pop-up pane. This way, you can have multiple conversations open at once:

So if you’re working on several tasks at the same time, you no longer have to switch between them individually.

5. Use widgets for decisions and feedback

By default, when Claude needs input on a lot of things, it’ll present them as a long list for your feedback:

Normally, I’d respond with the corresponding numbers along with my decisions and explanations.

But for longer lists, this quickly becomes tedious and you can lose track of the question/answer pairs.

So nowadays, whenever Claude throws a long list of decisions at me, I type this:

Prompt: Present these in a widget with freeform fields for my input. Include your brief recommendations.

Here’s what Claude does in response to that:

Now I can go through the list and respond to each point separately, with the right context in place. When I’m done, I click “Continue” and my responses get populated directly into the chat:

This is a much easier way to handle bigger sessions with multiple decisions and moving parts.

6. Use “/btw” for side chats

Sometimes, you might want to ask Claude a quick random question during a session.

Your typical options are:

1. Start a fresh chat (can be overkill for a short back-and-forth exchange)

2. Ask the question in the ongoing chat (pollutes the context with unrelated stuff)

Fortunately, there’s a better way, and it’s called the /btw command:

Type it within a WIP conversation, and it’ll create a separate “side chat” window:

What’s cool is that this side chat is aware of your current session. So while it doesn’t add noise to the thread itself, it can discuss topics related to it:

Perfect for quick asides and rabbit holes that don’t disrupt the main conversation.

7. Use task chips for side projects

On a related note, you can also splinter your work into separate chats.

If you stumble upon a minor fix or task that you’d prefer to solve outside the ongoing session, try this:

Prompt: Use spawn_task to create a task chip for [your task].

Here’s how that looks:

Claude creates the task spec that you can either send to a cloud agent or open in a new local session to handle separately from the ongoing chat:

This keeps the main chat’s context clean while letting you deal with any roadblocks.

Subscribe now

8. Explore branching paths with “/fork”

Claude may sometimes present several alternatives worth pursuing. If you want to explore each path without jumbling the chat context, you can use the /fork command:

This creates a brand-new Claude chat with all the conversation history up to that point:

Now you can have your own “alternate history” rabbit hole by exploring different directions in parallel chats.

If you’re feeling fancy, you can even run them side-by-side using tip #4:

You can even do this with older turns in a conversation. Simply scroll back and hover over the point you want to branch from and click the “Fork from here” icon:

This will create a new session with all conversation up to that point intact and a clean slate after that.

9. Add instructions when using “/compact”

Claude has a limited context window of up to one million tokens, depending on your plan and settings.

As you chat, this context fills up. You can always check how much context you’ve used up by clicking the little circle icon under the chat:

When the context is full, Claude Code will automatically compact the conversation to free up space. In practice, this means Claude will summarize the chat and key decisions, then wipe everything else.

While you can let Claude do the compacting, this has a few downsides:

1. There’s good evidence that a model’s reasoning quality degrades as the context fills up. Therefore, Anthropic recommends compacting the chat regularly.

2. By letting Claude compact the chat, you defer to its judgment on what details to save in the summary. It may well overlook something important.

As such, it’s a good idea to manually run the /compact command on a regular basis:

But here’s the cool part: You can also tell Claude exactly what details to keep when summarizing the chat by appending it to the /compact command:

This gives you full control over what gets saved and makes sure Claude doesn’t wipe any critical insights or decisions.

After a few sessions

Stuff to try after you’ve worked with Claude Code for a while.

10. Understand your work patterns with “/insights”

If you’ve been using Claude Code for a few weeks or so, try the /insights command:

This analyzes your past sessions and identifies what’s working, what isn’t, and how you can improve the way you do things.

Here’s the opening “At a Glance” section based on my Claude Code habits:

But the report goes much deeper than that and has the following chapters:

• What you work on

• How you use Claude Code

• Impressive things you did

• Where things go wrong

• Existing CC features to try

• New ways to use Claude Code

• On the horizon

Each chapter contains paragraphs of insights, charts, and suggestions:

Run this regularly to spot your blind spots, understand your strengths, and discover new ways to use Claude Code for your specific needs.

11. Bring in other people with “/team-onboarding”

If you ever need to invite others to work in your Claude Code workspace, /team-onboarding is the command to use:

This scans the last 30 days of your Claude Code sessions and identifies the type of work you do, the skills and commands you use, and more.

It then asks you to correct any assumptions and provide starter tasks and tips for your colleagues:

Claude will then generate an ONBOARDING.md file with all the relevant details:

Your colleague can now paste the file into a fresh Claude Code chat of their own, giving Claude all the relevant details to be up and running.

📒 Downloadable reference sheet

Paid subscribers can grab these commands (+shortcuts, extra tips, and use cases) as a neat reference sheet here:

Thanks for reading!

If you enjoy my work, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔄Share it to help others discover this newsletter.

• 🗣️Comment below—I love hearing your opinions.

Why Try AI is a passion project, and readers like you help keep it going. If you’d like to support me and unlock cool perks, consider a paid subscription:

Subscribe now

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

In case you missed it, here’s this week’s Thursday deep dive:

👩‍💻 AI releases

1. Amazon added AI merch design to the Shopping app, letting customers describe a design idea to Alexa to have it created and printed on a product.

2. Anthropic news:

   1. Claude Fable 5 is a top-tier model that leads benchmarks in knowledge work, scientific research, software engineering, and vision. (But do you need it?)

   2. Claude Managed Agents can now run on a schedule and securely access authenticated tools to perform tasks like data sync and reporting.

3. Deezer launched a free AI Music Detector that scans your playlists on Apple Music, Spotify, and 18 other services to detect and flag AI-generated tracks.

4. ElevenLabs released Avatars, persistent AI characters made from reference images that you can use for talking-head videos with lip syncing.

5. Google news:

   1. DiffusionGemma is an open-source model that generates entire blocks of text simultaneously instead of token-by-token, making it 4x faster.

   2. Gemini 3.5 Live Translate delivers near real-time voice translation across 70+ languages while preserving the speaker’s tone and pitch.

   3. NotebookLM can now do multi-step research, write and execute code, and export to 11 new formats. (Only AI Ultra subscribers for now.)

   4. Information Agents in Search can continuously monitor topics and send you updates with links when there’s new info. (Only AI Ultra subscribers for now.)

6. OpenAI introduced a Lockdown Mode that limits ChatGPT’s access to external connections and web search to guard against prompt injection attacks.

7. Perplexity added Deep Research to Computer, letting it spin up agents that turn complex queries into cited reports, decks, dashboards, and more.

🔬 AI research

1. Apple previewed a rebuilt Siri AI powered by Gemini, with a camera mode, cross-app sharing, onscreen awareness, and personalized context.

2. Meta will update the Edits app with an AI assistant and a desktop version to help you brainstorm ideas, analyze performance, and edit videos on a bigger screen.

📖 AI resources

1. “Agents’ Last Exam” [BENCHMARK]: a new tough benchmark that measures model performance across 1,490 real professional workflow tasks.

2. “Anthropic Public Record” [RESEARCH]: a survey of 52,000 Americans to gauge their opinions and feelings on AI deployment and societal impact.

3. “Claude Fable 5 - Full 319-page Breakdown” [VIDEO]: a comprehensive deep dive into Fable 5 by the always excellent AI Explained.

🔀 AI random

1. Anthropic had to disable access to Claude Fable 5 and Mythos 5 after the US government issued an export control directive aimed at preventing jailbreaks.

2. OpenAI submitted a confidential draft S-1 to the SEC as a formal first step toward a potential IPO.

🤦‍♂️ AI fail of the week

I wanted a man to cut himself shaving, not star in a bizarre horror comedy. (Also, very convincing “Ouch” there, bruh. Oscar-worthy.)

📹 Live & Learn update

I had to cancel my last Live & Learn session on short notice a few days ago (Friday).

But I’ll try again this coming Friday with a test of AI chatbots and standalone tools that let you make conversational edits to your images.

Join the session on Friday, June 18, at 2PM CET (8AM EST):

Join Live & Learn: AI Image Editing

Also, please let me know what you’d like to get out of these live sessions by taking this quick chat-based survey.

Live & Learn concept in a nutshell:

• I pick 3-5 tools in the same category

• I test them live and rate them on 3-5 specific dimensions

• I end up with a leaderboard based on my observations and ratings

See you there on Friday!

Join Live & Learn: AI Image Editing

Anthropic’s new top-tier model (Claude Fable 5/Mythos 5) is way too pricey and comes with access restrictions, but most of us don’t need it anyway.

What is it?

Fable 5/Mythos 5 is Anthropic’s latest model and a step change for frontier LLMs.

Before we move on, let’s clear up the whole Fable vs. Mythos thing, so I don’t have to keep writing them in tandem:

• Fable 5: Is the same underlying model as Mythos 5 but with additional safeguards in place that automatically reroute certain sensitive queries (e.g. cybersecurity and biology) to Opus 4.8 instead. Available to everyone.

• Mythos 5: The “full” version without any safeguards. Available only to a vetted group of “cyberdefenders and infrastructure providers.”

Claude Fable 5 leads the pack on virtually every benchmark self-reported by Anthropic:

But you don’t have to take Anthropic’s word for it.

The emerging consensus is that Fable 5 truly is a leap forward across the board.

Opinions aren’t nearly as divided as they’ve been for Anthropic’s latest releases, and even the notoriously critical Reddit crowd seems broadly positive.

You can find real-world tests and examples below in “Further reading & watching,” but the short of it is: Fable 5 is a state-of-the-art model that excels at the hardest, most complex long-horizon tasks and agentic coding work.

Subscribe now

How do you use it?

Do you have a paid Claude subscription?

Congratulations: You already have access to Claude Fable 5.

Just open your Claude app or claude.ai, and you’ll see Fable 5 in the model picker:1

Go crazy!

Ah, but you must hurry, fellow explorer: Regular Claude subscribers only have until June 22 to test this mythical model. For from June 23 onward, Fable 5 shall only reveal its powers to those willing to pay its legendary per-usage fees.2

Even before the June 23 switcheroo, Fable 5 will burn through your daily/weekly rate limits at twice the speed of the already expensive Opus 4.X model family.

To summarize, Fable 5 is:

• “Mythos 5 Lite” with safety guardrails that limit its range of use cases.

• Only available in existing paid Claude plans until June 22.

• Anthropic’s most expensive model (double the cost of Opus 4.8).

Looks like the “AI rich vs. AI poor” future predicted is finally here.

But wait…how much does this really matter to you?

Subscribe now

Why should you (not) care?

Okay, real talk.3

For the overwhelming majority of us, Fable 5 is pure overkill.

Unless you do frontier research or work on complex software engineering projects like Stripe’s reported codebase migration, you simply don’t need Fable 5’s wizard skills.

Take a look at these ELO scores for GDPval-AA, which “evaluates AI models on real-world, economically valuable tasks across a wide range of occupations”:

Now be honest: Do Fable’s extra 42 ELO points over Opus 4.8 really matter for your daily tasks? How would you even measure it? Are those marginal gains worth the 2x price hike?

I’ll take a wild swing here and say: No, they aren’t. Not for the average person.

For instance, I consider myself to be at least an intermediate AI user. I work with and test AI tools daily to keep up with all the madness for this newsletter.

I run Claude Code together with Codex, hooked up to my Obsidian vault as their command center.

I’m in the weeds with this stuff, is what I’m saying.

But for most of my use cases, I find that the good old Opus 4.64 is more than plenty. Hell, even Sonnet 4.6 works well for much of what I need done.

(I do ground-breaking scientific research only occasionally and have to date cured at most two or three cancers.)

And it’s not just me, either.

In their recent Fable 5 “vibe check,” Dan Shipper and the crew at Every wrote:

…we found that users who were highly adept with AI—at Level 7 or 8 on our AI adoption ladder—found [Fable 5] paradigm-shifting for their hardest tasks. Users who were lower down on the curve, however, struggled to find something to use it for.

For reference, here are the 8 levels they’re talking about:

So if you’re not “managing multiple long-running agents at the same time,” it’s perfectly fine to give Fable 5 a pass.

You don’t need Fable 5 to draft a quick work email or suggest entertainment ideas for your pet iguana’s birthday party.

Fable 5 is also way overqualified for most of your everyday knowledge work.

It’s like grabbing a bazooka to take down a mosquito.

It’s like taking a Formula 1 car to drive your kids to school.

It’s like asking Fable 5 to come up with a third beat for this three-part analogy.

There’s also early anecdotal evidence that on certain white-collar tasks like writing and front-end design, Fable 5 fares worse than cheaper models due to its dense engineer-style lingo and verbosity.

“But Daniel, I saw that Fable 5 can flawlessly code entire games and build advanced tools from a single prompt! Isn’t that worth something?” you ask, conveniently setting up my upcoming response.

And yes, that appears to be a legitimately magical use of this tech. But:

a) Let’s face it: Most of us aren’t sitting on a backlog of brilliant ideas we’re itching to will into existence. (Although now that the option is available, this may gradually change, which is a net positive for all of us.)

b) One-shotting complex software is bound to push your token spend into the stratosphere, which brings us full circle to square one.5

As it stands, Fable 5 is likely not for me and you…and that’s okay.

Take Fable 5 for a spin on your regular Claude plan until June 22. Poke at it, see what it can do and how it feels compared to what you’re used to.

Then ask yourself if you’re willing to pay double the price—and wait longer for Fable to painstakingly think through every request—instead of sticking to Sonnet or Opus.

My guess?

We won’t be too heartbroken when it’s time to say goodbye to Fable 5 in two weeks.

Further reading & watching

• “Anthropic Just Split the Frontier in Two“ - Product with Attitude

• “Claude Fable 5 and Claude Mythos 5“ - Anthropic

• “Claude Fable 5 – is this Mythos model worth the wait?“ [VIDEO] - How I AI

• “Nine Things About Claude Mythos 5 That Matter If You’re Not an Enterprise Customer“ - The Algorithmic Bridge

• “Vibe Check: Fable 5 Is the Best Coding Model in the World“ - Every

• “What it feels like to work with Mythos“ - One Useful Thing

🫵 Over to you…

Have you tried Fable 5 yet? If so, how much of a difference did you notice on your tasks and projects? Is my hot take way off? Is it way on? Am I rambling?

Leave a comment or drop me a line at whytryai@substack.com.

Leave a comment

Thanks for reading!

If you enjoy my writing, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔄Share it to help others discover this newsletter.

• 🗣️Comment below—I love hearing your opinions.

Why Try AI is a passion project, and I’m grateful to those who help keep it going. If you’d like to support my work and unlock cool perks, consider a paid subscription:

Subscribe now

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

In case you missed it, here’s this week’s Thursday deep dive:

👩‍💻 AI releases

1. Google open-sourced Gemma 4 12B, a multimodal model that processes text, images, and audio natively in a single pass and can run on a home laptop.

2. H Company open-sourced Holo3.1, a family of AI agents that can click, type, and navigate apps on the web, desktop, and mobile while running on your own device.

3. Ideogram launched Ideogram 4.0, an image model with the most reliable text rendering of any open-weight release, free for non-commercial use.

4. JetBrains open-sourced Mellum2, a fast coding model that can act as a specialist in bigger multimodel pipelines to handle routing, summarization, and refactoring.

5. Krea released Krea 2 Turbo, a faster version of Krea 2 that can create high-quality images in about two seconds. (Try it for free.)

6. Microsoft rolled out its first in-house coding model, MAI-Code-1-Flash, directly inside GitHub Copilot, free and optimized for fast, lightweight coding tasks.

7. MiniMax open-sourced M3, a natively multimodal model with 1M context, frontier performance, and coding skills designed for long-running agent tasks.

8. Nous Research launched Hermes Desktop, a native app for installing, configuring, and chatting with Hermes Agent without using the terminal.

9. OpenAI news:

   1. ChatGPT can now send emails directly from a conversation, so you can draft, edit, and fire off a message without leaving the chat.

   2. Codex can now adapt to your specific job role thanks to plugin bundles for marketing, sales, support, and more with relevant apps and skills.

   3. Dreaming lets ChatGPT process your past chats in the background to build a persistent understanding of your preferences. (Paid US accounts only for now.)

10. Reve launched Reve 2.0, a 4K image generator that lets you control exactly where elements appear using visual layouts rather than just text prompts. (Try for free.)

11. Runway brought its Aleph 2.0 model to the API, letting developers make precise video edits while preserving the rest of the clip.

12. TwelveLabs launched Rodeo, an AI video copilot that lets you find and assemble footage using plain language without manual scrubbing.

13. xAI released Grok Imagine 1.5 Preview, which lets you turn still images into cinematic 720p videos with natural-language prompts.

🔬 AI research

1. GitHub announced a Copilot Desktop App in technical preview, letting developers manage coding agents, create secure sandboxes, and review changes.

2. Microsoft introduced Scout, an always-on Microsoft 365 agent that schedules meetings, flags stalled decisions, and learns your priorities over time.

3. Perplexity teased a hybrid inference system for Perplexity Computer that automatically splits AI tasks between your device and the cloud.

📖 AI resources

1. “EVA-Bench Data 2.0” [BENCHMARK]: a set of 121 tools and 213 real-world scenarios to test AI voice agents across different enterprise domains.

🔀 AI random

1. Anthropic confidentially filed a draft S-1 for a proposed IPO with the Securities and Exchange Commission. (But let’s hope it gets its house in order soon.)

🤦‍♂️ AI fail of the week

I don’t know what’s happening here, but we need this in the Olympics ASAP.

📹 Live & Learn #5: AI logo makers

I’m back with the Live & Learn concept, where I test and rate AI tools, like so:

• I pick 3-5 tools in the same category

• I test them live and rate them on 3-5 specific dimensions

• I end up with a leaderboard based on my obserations and ratings

This week, I looked at and ranked five AI logo generators:

In the next Live & Learn, I will be testing chatbots and standalone tools that let you make edits to images.

Join the session on Friday, June 12, at 2PM CET (8AM EST):

Live & Learn: AI Image Editing

Also, please let me know what you’d like to get out of these live sessions:

Help shape "Live & Learn"

(It’s just a single open-ended question with a few AI-assisted follow-ups.)

Thanks!

We’re just two-and-a-half days into June, with 8 “incidents” across multiple models.

As if that wasn’t enough, here’s some good ol’ Reddit bashing of the newest Opus 4.8:

Just a few months ago, Anthropic was everyone’s darling.

What happened?

January-February 2026: “QuitGPT”

At the start of the year, Anthropic’s Claude Code product was riding a wave of mainstream popularity.

Even reluctant laggards like yours truly finally jumped on the bandwagon.

Businesses started picking Anthropic over OpenAI for their first-time AI spend:

Opus 4.6 came out in early February and soon became the first model to ever be #1 across three separate Arena leaderboards (code, text, and search) at the same time:

By most measures, Anthropic was already doing pretty damn well.

And then came QuitGPT.

After Anthropic refused to budge in the standoff with the US Government over the use of its AI models for mass surveillance and fully autonomous weapons, the administration designated Anthropic a “supply chain risk” to discourage third parties from conducting any business with the company:

Shortly after, employees at Google and OpenAI signed a “We Will Not Be Divided” open letter in support of Anthropic’s stance (1,000+ signatures as of now).

Shortlier afterer, OpenAI’s CEO Sam Altman posted this:

All. Shit. Broke. Loose.

OpenAI instantly became the main villain in everyone’s “Dario vs. Government” “David vs. Goliath” story: Here was Anthropic standing by its moral principles only for OpenAI to swoop in like a blood-starved vulture and bite a big chunk out of that juicy government contract’s flesh.1

This fueled the already ongoing QuitGPT movement.

People started fleeing from ChatGPT to Claude in droves.

Anthropic dropped an “Import Memory” feature that made it super easy for users to switch to Claude from “other AI providers” (wink wink, nudge nudge).

By early March, Claude was the #1 app on the US Apple App Store.

And Anthropic lived happily ever after.

No, wait…

Subscribe now

March 2026: “Too big, too fast?”

The problem with having the most downloaded app on the App Store is that your app is downloaded by a whole lot of people.2

The problem with a whole lot of people trying to access your app at the same time is, well…

Yup.

On March 2, right after hitting that sweet #1 spot, Anthropic’s services couldn’t cope with the sudden influx of users and ran into compute constraints. (CEO Dario Amodei would later publicly acknowledge this.)

But hey, at least it was just one bad day, right?

Right?!

Oh, I see.

Not content with simply facing these ongoing bandwidth issues, Anthropic also quietly scored several own goals.

• March 4: Claude Code’s default reasoning effort was lowered from ”high“ to “medium,” leading to a performance drop that power users instantly noticed.

• March 26: A new bug made Claude "forget” prior turns in a conversation, which is less than ideal if you prefer working with chatbots that don’t have amnesia.

It certainly didn’t help that Anthropic wouldn’t acknowledge or address this until almost two months later in an April 23 postmortem.

Finally, Claude’s usage limits are way stricter than ChatGPT’s, especially on free plans. This was apparently not something the ex-ChatGPT crowd was prepared for:

It looked like the honeymoon was over before it truly began.

But not to worry: All Anthropic needed was a shiny new model, and all would be forgiven.

Cue dark foreshadowing music.

Subscribe now

April 2026: “Gaslightus-4.7”

Anthropic’s technical challenges continued well into April:

On forums like Reddit, the emerging mood could be loosely summarized as “Stop constantly shipping new goddamn features and just fix the goddamn basics, bro.”

Then, on April 16, Anthropic proudly released a brand new model: Opus 4.7.

Anthropic called it a “notable improvement on Opus 4.6 in advanced software engineering, with particular gains on the most difficult task.”

Users called it “a genuine regression,” “a serious regression,” “legendarily bad,” and—ominously—“Anthropic’s downfall.”

One of the posts referred to Opus 4.7 as “Gaslightus-4.7” because it tended to keep denying its own errors even when the user provided clear proof.

The name stuck because people felt it mirrored Anthropic’s own behavior. The company, faced with increasing reports of degraded performance, chose to play the “I know you are, but what am I?” card:

To add fuel to the fire, Anthropic shipped Opus 4.7 with a new tokenizer that effectively bumped usage costs by 20-30%.

It was around the same time that I started running into session limits more quickly and brought in Codex to work alongside Claude Code.

But Anthropic wasn’t quite done spraying bullets directly at its own feet.

On April 21, someone pointed out that Anthropic no longer listed “Claude Code” as a Pro plan feature on its pricing page. Seeing how Claude Code was a major reason so many people (including me) had a paid plan in the first place, this did not go over well at all.

Anthropic instantly backtracked, returned the old pricing page, and claimed it was just a small test on a subset of new users:

But all that did was feed the already growing “gaslighting” narrative.

After all the backlash grew into near-outrage, Anthropic reluctantly published the now-infamous post-mortem about all the performance issues, resulting in this delicious headline in The Register:

Anthropic should give masterclasses on rapidly squandering massive public goodwill.

But maybe not all was lost?

Subscribe now

May-June 2026: “More compute, less goodwill”

On May 6, Anthropic got some much-needed help from an unlikely source: Elon Musk’s SpaceX and its vast compute capacity. Thanks to this new deal, Anthropic could stabilize its uptime stats and raise rate limits for all paid users.

And on May 28, Anthropic released its latest model: Opus 4.8, specifically to address many of Opus 4.7’s blind spots.

But early reports from real-world users aren’t rosy. The short of it is that most are planning to stick to Opus 4.6 until Anthropic pries it from their cold, dead hands.

Visit any Anthropic-related subreddit, and you’ll find post after post complaining about general performance issues and Opus 4.8 in particular.

But that’s just anecdotal user reports, right?

Well, not exactly: While Anthropic reported better performance on handpicked benchmarks, several independent benchmarks hint at the real situation being a mixed bag at best.

LiveBench ranks Opus 4.6 (and even Sonnet 4.6) above both Opus 4.7 and 4.8 on agentic coding:

Arena has Opus 4.6 above Opus 4.7 on “Expert” text-to-text tasks (Opus 4.8 not ranked yet):

And SimpleBench puts Opus 4.6 in the lead out of all Opus models:

It almost feels like Anthropic is rushing model updates out the door to win back public sentiment, but it’s not quite getting the slam dunk it needs.

Now what?

On June 1, Anthropic submitted preliminary IPO paperwork to the SEC.

The company is currently valued at just under one trillion dollars.

On most metrics that matter to investors, Anthropic is doing just fine.

But if public “vibes” were a metric, they’d tell a different story.

The narrative playing out right now shows that an initial burst of goodwill isn’t enough to compensate for uptime issues, poor PR moves, and subpar product launches.

For Anthropic’s sake, we should hope it wins back the public’s favor and its status page starts logging fewer daily incidents than the screenshot in my intro.

Because you can’t IPO your way out of performance issues and eroding trust.

Thanks for reading!

If you enjoy my scribbles, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔄Share it to help others discover this newsletter.

• 🗣️Comment below—I love hearing your opinions.

Why Try AI is a passion project, and I’m grateful to those who help keep it going. If you’d like to support me and unlock cool perks, consider a paid subscription:

Subscribe now

But for this Live & Learn, I wanted to test tools that either position themselves as dedicated AI logo makers or at least offer specialized templates/features for logos.

I narrowed the field to a mix of design tools with AI capabilities recently added, AI image tools with standalone logo templates, and an AI-first logo maker.

I gave all five the same prompt and scored them across the same five dimensions to keep the comparison as fair as possible.

Tools tested & scorecard

Read more

Welcome back to the weekly AI news roundup.

See all 100+ paid subscriber bonuses

In case you missed it, here’s this week’s Thursday deep dive:

🗞️ AI news

Here’s what happened in AI this week:

👩‍💻 AI releases

1. Anthropic news:

   1. Claude Opus 4.8 brings incremental upgrades over 4.7 and several new features at the same cost. (But initial reactions are not positive.)

   2. Dynamic Workflows let Claude Code write orchestration scripts to run hundreds of parallel subagents to handle complex tasks.

2. ElevenLabs news:

   1. Dubbing v2 preserves emotional nuance when translating video content across languages by conditioning it on the original video. (Try for free.)

   2. Music v2 lets you create full songs that can switch genre mid-track with improved instrumentals, multilingual support, and richer vocals. (Try for free.)

3. Microsoft news:

   1. 365 Copilot is now more deeply embedded and loads faster inside Office apps like Excel and Word, so you can invoke it without breaking your flow.

   2. MAI-Image-2.5 is #3 on Arena’s text-to-image leaderboard and delivers sharp text and commercial-quality photography. (Try it free on Arena.)

4. OpenAI brought Codex computer use and remote control to Windows, so it can operate your desktop apps and continue coding sessions from the phone.

5. Perplexity made Computer available directly in Excel, Outlook, PowerPoint, and Word as native add-ins, so you can use it without leaving your Office apps.

6. Runway launched an MCP server that lets you create images and videos directly inside ChatGPT, Claude, Cursor, or Replit without leaving the app.

7. xAI launched Grok Build, its coding agent with automation tools and image/video generation, in early beta for SuperGrok and X Premium+ users.

🔬 AI research

1. Apple previewed a new Siri for iOS 27 powered by Google Gemini, with improved reasoning, persistent chat history, and a standalone app.

📖 AI resources

1. “DeepSWE” [BENCHMARK]: New “contamination-free” benchmark that measures coding agents on original, long-horizon software engineering tasks.

2. “How to evaluate AI agents (2026 edition)” [GUIDE]: practical guide to testing AI agents in production by Ben Hylak.

🔀 AI random

1. YouTube is making AI labels more prominent across the platform and adding automatic detection to help spot photorealistic AI content.

🤦‍♂️ AI fail of the week

“Hey, barkeep, got any of them self-filling bottles with self-making cocktails that spontaneously catches on fire?”

“Say less.”

📹 Live & Learn is back

During the next Live & Learn session, I’ll be testing and rating AI logo makers.

Join the session on Tuesday, June 2, at 2PM CET (8AM EST):

Live & Learn: AI Logo Makers

Let me know what would make the session extra useful by taking this quick survey:

Help shape "Live & Learn"

(It’s one open-ended question with a few AI-assisted follow-ups.)

Thanks!

At the same time, I’ve consistently advocated for using AI actively as a sparring partner rather than passively as a substitute for your own thinking.

Much of that is just my nature: I think best when I get to bounce ideas off of others, and AI often provides a great sounding board.

But I also always felt that uncritically trusting AI without human oversight is a profoundly bad idea.

Well, it turns out that—plot twist—uncritically trusting AI without human oversight is a profoundly bad idea.

Who would’ve thought?

Today, I want to take a quick look at the concept of “cognitive surrender” and what you might be able to do about it.

What is “cognitive surrender”?

“Cognitive surrender” refers to uncritically accepting AI outputs in place of relying on your own squishy brain.

The term was coined earlier this year by Wharton’s Gideon Nave and Steven Shaw in a research paper titled “Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender.”

The study used a version of the cognitive reflection test and found that, even when AI output was wrong, almost 80% of participants still chose to go with AI answers without overriding them.

Man, 80% is, like…consults ChatGPT…almost half of all people!

So that’s, you know, not great.

But while the term “cognitive surrender” is relatively new, the risk of blind reliance on AI isn’t.

New name, old observations

Look, I don’t mean to toot my own horn, but…

…with that out of the way, I want to share a few posts where I warned against cognitive surrender well before that combination of words was used to describe it.

Back when ChatGPT first rolled out AI web search, I explicitly called out the risk of entrusting your research wholesale to a chatbot:

Here’s what I wrote:

And even if AI summaries are magically 100% accurate, what will be the long-term effect of us settling for condensed AI snippets instead of doing our own deep research?

My fear is that at least for a while, AI search will only amplify the Dunning-Kruger effect, giving us the illusion of knowledge by pacifying us with a seemingly authoritative filter between ourselves and the source.

But beyond just being a wise guy who points out the “wrong” way to do stuff, I also shared my ideas on what the “right” way might look like:

• In “The Skeptical Writer’s Guide to AI,” I showed how writers could use AI while staying in the driver’s seat and not giving up what matters.

• In “How to Level Up Your Job Hunt With AI,” my main message was to use AI to make yourself a better candidate instead of automating the application process.

• In “How to Master New Topics with AI,” I covered a few approaches to turning AI into a tool that helps you learn instead of doing the thinking for you.

Hopefully, reading these posts will help you embrace AI while keeping your critical thinking intact.

Also, if you’re specifically trying to learn a new subject or understand a concept, remember to switch on the dedicated “study” mode in your chatbot of choice:

Are there other things you can do to avoid surrendering to AI?

Well…

Subscribe now

5 habits that help prevent cognitive surrender

Cognitive surrender isn’t always a single clear instance. It may well creep up over time as you gradually trust AI more and more at the cost of exercising your own judgment.

One way to fix this is to read every Why Try AI post ever written.

If, for some odd reason, that’s not on your bucket list, here are a few other ways you can train yourself to stop deferring to AI.

Habit #1: Form your own opinion first

Before you ever ask AI for input, formulate your own take.

It’s okay if it’s just a few scribbled notes or a stream-of-consciousness rant you dictate into a microphone. The important part is doing your own legwork instead of letting AI do it for you.

If you know where you stand, you won’t accept AI output without pushback.

Habit #2: Ask for a challenge, not validation

Instead of turning to a chatbot with an open-ended “What do you think?”, try to intentionally invite friction by asking AI to poke holes in your assumptions, point out what you might have missed, find counterarguments, and so on.

AI chatbots are notoriously sycophantic, but asking one to stress test your ideas nudges it out of this default behavior. I shared seven anti-sycophancy tips here:

Habit #3: Always check the source

I mean, this has been a good rule of thumb even in the pre-AI era.

If a chatbot cites a verifiable fact or figure, go to the source. Does the source actually say what AI claimed, or was it just a confident hallucination? What’s the context around the claim, and does it change the picture AI presented?

Understanding where a piece of information came from and how it was obtained is often as important as the information itself.

Habit #4: Describe things in your own words

After you get a finished product or output from AI, pretend you’re giving your imaginary friend1 an executive summary.

If you can easily find the right words, your brain has been engaged in the process.

But if you struggle, that’s a good sign you might be deferring to AI a tad too much. Revisit the task and see if you can internalize what AI’s been doing.

Habit #5: Don’t delegate what truly matters

Here’s how I try to approach AI: If a task is my primary deliverable, my core area of expertise, or simply something I’m passionate about, I never let AI do it for me. Sure, I might ask AI for a second opinion, but the bulk of the effort and output will come from me.

For instance, no matter how good AI gets at writing, I’ll still be stringing my own words together. That’s because I like writing. I get a kick out of sprinkling in silly asides and jokes and knowing nods to my audience. (You know who you are, Fred, wink wink.)

But I’ll happily turn to AI for filler videos or images or other visuals to supplement my writing, because a) I suck at most visual arts and b) it’s not a skillset I want to develop or consider critical to my identity.

You might be the exact opposite of me: a passionate cartoonist who won’t be caught dead using AI to create images, but who’ll happily hand tedious writing tasks to the first chatbot you come across. And your name is Leinad.

The point is that you should protect the work that makes you who you are while letting AI handle the busywork, however you define that in your role.

That way, you won’t have to watch your creativity and thinking muscles atrophy.

Here’s a quick reference sheet:

For an additional perspective, check out this wonderful TED Talk by Advait Sarkar:

Thanks for reading!

If you enjoy my work, here’s how you can help:

• ❤️Like this post if it resonates with you.

• 🔄Share it to help others discover this newsletter.

• 🗣️Comment below—I love hearing your opinions.

Why Try AI is a passion project, and I’m grateful to those who help keep it going. If you’d like to support me and unlock cool perks, consider a paid subscription:

Subscribe now