Welcome, humans.

Okay, so the main story below is going to talk all about the biggest news of the week: that Anthropic released a new “Mythos-class” model called Fable (we’ll explain that in a sec), and then a few days after, the US government banned it for non-US citizens. But as of this writing, no one can use it right now.  

This is very serious. But the memes have flooded in all weekend, and we need a place to put them, so please enjoy:

Keep scrolling for the full story!

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Here’s what happened in AI today:

• 🙀 The US Gov Shuts Down Claude Fable, Explained

• 📰 Meta started unwinding Manus after Chinese regulatory pressure.

• 📰 Canada introduced teen social media and chatbot rules.

• 🍪 DoorDash turned photos and recipes into shopping carts.

• 🌟 Apple’s Siri beta impressed early testers after WWDC.

…and a whole lot more that you can read about here.

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🙀 The U.S. Government Pulled Fable 5 From Everyone

On Tuesday, Anthropic released a new AI model called Fable 5 (read our full coverage of it here), which was the first “Mythos-class” model normal Claude users could touch. For background on Mythos, it was the big scary model that Anthropic held back from regular people (but released to select partners) due to its cybersecurity capabilities.

Well, over the weekend, the government seems to have smashed the power switch on that.

Anthropic said the U.S. government issued an export-control directive (a rule that restricts who can access sensitive technology) blocking any foreign national from using Fable 5 or Mythos 5. That includes foreign nationals inside the U.S. and even Anthropic’s own foreign-national employees.

Because Anthropic says it cannot separate users by nationality in real time, it disabled both models for all customers.

Here's what happened:

• Anthropic received the directive at 5:21 p.m. ET on Friday (June 12).

• The order cited national security but did not give specific details, Anthropic said.

• Anthropic believes the concern is a narrow Fable 5 jailbreak, meaning a way to bypass safeguards.

• The company says the demo found known, minor software flaws that other models can also identify.

• WSJ reported Amazon researchers flagged the issue to U.S. officials.

For the government’s POV on this, David Sacks’ tweet is a good TL;DR recap.

Why this matters: This moves the AI governance landscape from “companies decide what to ship” to “the government can pull a frontier model after launch now”, and it’s more or less the first time the US government has blocked a model from release (that we know of, anyway). That changes the operating environment for customers, developers, and every global team building on U.S. AI.

The practical headache is huge. If access to this model depends on nationality (or “favorable” nationality, let’s say), AI providers may now need identity checks, employee-access controls, and country-by-country model gates. For a remote team, “who can use the best model?” is now a very real concern. Luckily, World ID has a privacy-friendly solution that could be used for this… but it’s still not an ideal situation for anyone involved.

This Reddit thread captured the buyer anxiety pretty well: if a model can disappear overnight, procurement teams must now consider the geopolitics of a model’s origin.

Our take: Anthropic kinda asked for this? They’ve been asking for the government to regulate the industry and block unsafe deployments like this. Interestingly, now it is arguing that this block skipped the transparent, technical process such power needs. Putting the heavy irony aside, that’s a good argument… probably better to do a longer review cycle and stop things before they go public to avoid the headache this just caused. Anyway, Yann LeCun didn’t mince words about this:

We can also see where a government kill switch may be necessary for truly dangerous models, especially if cyber or bio capabilities cross a real line. The fact that Amazon flagged it is interesting; did they get data-breached, for example? But to do it once a model is public is all kindsa messy. Basically, companies need clear rules so they can comply with them, and before they build businesses on top of models that can vanish by a single, seemingly reactive directive.

The larger issue: If we’re going to now start blocking AI model access on a country by country basis, what’s to stop China from doing the same? That could mean US companies will no longer get access to frontier open weight models (meaning models that anyone can copy the “weights” of and run on their own servers) that help keep AI pricing competitive and prevent US companies from overcharging businesses who rely on these models for their engineering and automation work. And that would be pretty bad for everyone in the AI ecosystem besides OpenAI and Anthropic, TBH.

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🎓 AI Skill of the Day:  Set Up Your Claude Code Like Creator Boris Cherny

So you can apparently make Claude Code way more useful by teaching it how to work like a tiny team, instead of treating it like one very fancy autocomplete box.

In our breakdown of Boris Cherny and Cat Wu’s Claude Code workflow, Boris gives a casual overview of how he uses Claude Code a year later.

Here’s how to copy his playbook:

1. Start in the Claude Code desktop app. Boris says he uses it because it handles worktrees for him. A worktree is a separate copy of your repo (where you store code), so agents can work in parallel without overwriting each other.

2. Open agent view in the terminal. This replaces the old “six terminal tabs” setup with one dashboard for background agents you can use alongside the desktop app (to my knowledge, desktop doesn’t have agent view yet).

3. Launch one scoped task per agent. Give each agent a specific job, then let it run as its own session.

4. Use auto mode for everything. Boris says newer models need less planning, so he starts a Claude in auto-mode once the task is scoped, lets it work, and moves to the next one.

   1. He and Cat actually say this is safer because it only asks permissions for the most important stuff instead of your eyes glazing over approving everything manually.

5. Turn repeated mistakes into memory. When Claude makes the same mistake twice, tell it to update CLAUDE.md, the project instruction file, or create a reusable skill with the proper instructions.

6. Make Claude verify it, not run “tests”. Claude should run the thing itself, click through the UX, test edge cases, fix issues, and recheck it, not do test-driven development.

   1. Kun Chen recently warned that so-called “test-driven development” can make agents overfit to their own weak tests and stop too early, and his deeper dive report found worse pass rates with higher token use in ProgramBench evaluation. So use tests as one signal, but make the final check behavioral: does the thing actually work for the user?

7. Move recurring work into routines, /loop, or /goal . Goals are basically loops with a goal “completion looks like XYZ” attached. Think PR review, CI fixes, rebasing, bug reports, stale tickets, or docs cleanup.

8. Use Remote Control to check on sessions from your phone. Start the session from the destkop, type /remote-control to activate it, and then you can check agents, starts new ones, and keep work moving away from your laptop.

9. Use voice mode for ideas on the fly. When a new idea comes up mid-conversation, start an agent immediately in the app with the mic.

10. Keep context minimal. Give Claude the goal, constraints, and a way to find more context. Don’t micromanage the whole path.

If you’re new to coding projects, you can do all of this as well; just copy these instructions into Claude Code and ask Claude to help guide you through the project you want to build!

Have a specific skill you want to learn? Request it here. 

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4. Linear coding sessions turn bug reports into agent-run investigations, fixes, PRs (code-change requests), and status updates inside Linear, no pricing details.

5. Honen turns docs, call recordings, kickoff videos, or topics into structured training courses your team can actually finish, no pricing details.

6. fal Pixelcut removes video backgrounds, including hair and movement, so creators can clean clips without opening a full editing suite, no pricing details.

New from The Neuron: AI Skills vs. Agents vs. GPTs: Which One Do I Use?

As a normie or newbie AI users, you now have Projects, Custom GPTs, Gems, Skills, Agents, Plugins, Connectors, Loops, and Subagents to try and figure out. Good luck babes! JK: we made a super simple guide to explain what each one does and when to use it.

Watch/read: YouTube live stream | Blog version to follow along

📰 Around the Horn

• Meta split operations from Manus and began unwinding the acquisition after Chinese regulatory pressure; The Next Web said the founders were reportedly exploring a buyback.

• Canada introduced the Safe Social Media Act, a proposal that would restrict under-16 social media access unless platforms meet safety standards and regulate AI chatbots.

• Prometheus reached a huge valuation for Jeff Bezos-backed industrial AI tools focused on speeding the idea-to-prototype-to-manufacturing loop.

• Genspark raised $100M at a $2.6B valuation for its agentic workplace platform, bringing total funding above $645M.

• Amazon said its directly operated data centers used 2.5B gallons of water in 2025 while improving efficiency and using reclaimed water at some sites.

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🌟 Sunday Special: 5 Stories We Saved for Sunday

1. Apple’s Siri beta impressed early testers with more natural conversation, personal app context, on-screen awareness, and Camera Control as an instant visual-intelligence trigger.

2. Google DiffusionGemma brought diffusion-style text generation to the Gemma family, which means the model refines blocks of text in parallel instead of writing one token at a time.

3. Agents’ Last Exam tested AI agents on 1,500+ real professional tasks and showed frontier systems still struggle with hard, long-horizon work.

4. Recursive shared early results from an automated research system that proposes ideas, runs experiments, validates results, and combines promising branches.

5. Xiaomi MiMo Code launched as an open-source terminal coding agent with persistent memory, Compose workflows, voice input, and Claude Code compatibility.

For all the week’s top hits, read the Around the Horn Digest here.

A Cat’s Commentary

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