Anthropic opens the files on global Claude misuse

Good morning, {{ first_name | AI enthusiasts }}, and welcome to our 3,672 new readers. Need a feel-good AI palate cleanser after yesterday’s extinction doom? Anthropic has the opposite: a full accounting of everything bad actors attempted with Claude over the last eight months.

A 150+ page threat report walks through case studies of misuse it shut down across the globe, from rocket guidance, bioweapons, and espionage to Chinese labs training off Claude (and even serving the model to customers as their own). Feeling better yet?

The Rundown: Anthropic published its latest Threat Report, detailing the most notable cases of Claude misuse it disrupted over the last eight months, including bioweapon flags, espionage, and acts of Chinese AI labs serving Claude in place of their own model.

Why it matters: This is just a brief, so read on for Claude running 4,700 dating-app personas, cloning an activist’s writing style to talk with his contacts, rebuilding malware to avoid antivirus detection, and more. These were all attempted with Opus-level models and below, making future reports with more capable models even harder to fathom.

The Rundown: You may have the best product, but no buyers will sign these days without proof of your security. Example: A prospect asks for proof of compliance. The deal stalls while you scramble, your engineer gets pulled off the roadmap to audit prep, and every enterprise conversation turns into a fire drill.

Rowan: OpenAI’s GPT-6 Astra model came out last week to ChatGPT paid plans, and I’ve been having an absolute blast pushing it to its limits (and waiting for limits to reset…).

The capabilities that make it genuinely feel like a step up are its computer use, visual consistency, long one-prompt jobs — and, to my pleasant surprise, personal life use cases.

One personal use case that is improving my life is getting Astra to redesign my entire wardrobe and give me a system for picking clothes based on real-time local weather.

For quick context, I wear a lot of black, usually a black T-shirt and jeans. It works in tech, but I’ve been trying to level up my wardrobe. The problem is that my absolute worst nightmare is a closet full of clothes creating more clutter in my brain every day when picking an outfit.

So I systematized it (tech nerd brain, can’t help it). One outfit per day of the week, per season, plus gym and lounge: 30 looks total, everything hung up and ready.

Astra turned that idea into an app. I gave it full-body portraits, my sizes, my colors, some niche details about my style, and a master prompt, and it generated 30 looks with 70 try-on images where I’m the model in every photo, pulling real-time local weather so the daily pick changes with what’s outside.

The virtual try-on is genuinely incredible. If I can’t find a piece online, I update the model, and it rebuilds the wardrobes.

I posted my exact step-by-step and full master prompt in our Workflow Hub. Hope it’s useful to those in a similar boat.

The Rundown: In this guide, you will learn how to set up a ChatGPT Work project for a recurring workflow, processing the work once and then automating it.

Pro tip: Tell ChatGPT to turn those automated routines into skills that you can call at any time manually with a slash command.

The Rundown: Tines 3B gives every team the power to build with AI, and gives IT the control to run and monitor that work safely.

The Rundown: Chinese AI lab DeepSeek just released V4.1-Flash, an efficient new open-weight model that edges out systems like Claude Opus 5 and GPT-5.6 Sol on several agentic, coding, and cyber benchmarks at extremely low price points.

Why it matters: DeepSeek’s efficiency and pricing remain its edge, with Chinese labs in general (perhaps helped by the distillation efforts Anthropic detailed above) squeezing margins just as users are growing more price-sensitive. The frontier still sits pretty clearly in the U.S., but the volume play is still very much up for grabs.

▸ Rich built a streaming recommender that knows who’s on the couch

Today’s workflow comes from reader Rich Kroll:

“I built Show Hole to solve my family’s classic streaming problem: we spend too much time deciding what to watch, and the answer changes depending on who is actually on the couch.

We each have different tastes, but the more interesting problem is that our tastes overlap differently in different combinations. I watch one kind of thing with my spouse, my spouse watches something different with our kid, and my kid and I have our own lane too. Most recommendation tools flatten that into one account profile, one watch history, or broad genre buckets, so they miss the real context of a household.

Show Hole treats people and viewing contexts as first-class citizens. It recommends titles “in the vein of” something we liked, filters recommendations to the streaming services we actually subscribe to, avoids titles that the people present have already seen or vetoed, and explains why a recommendation fits tonight. I designed the app using Claude Design, then used those designs with Claude Code to build it.”

See Rich’s full workflow here. How do you use AI? Tell us for a chance to be featured.

Cognition rolled out SWE-2 inside Devin, a Kimi K3-based coding model that claims to match Fable 5.1 and GPT-6 Astra on certain coding benchmarks while costing 64% less.

Thinking Machines co-founder Andrew Tulloch is moving from Meta to Anthropic, months after initially rejecting Mark Zuckerberg’s reported $1.5B package and then signing on anyway at an undisclosed compensation.

OpenAI denied to the NYT that Tristan Buckmaster’s Codex prompts shaped its Navier-Stokes proof, while claiming “substantial progress” on another Millennium Prize problem.

OpenAI launched ChatGPT for Financial Services, an edition of ChatGPT Work with PitchBook, Crunchbase, and LSEG data baked in for valuation models and pitch decks.

Universal Music Group is partnering with AI audio startup ElevenLabs on a licensing deal, with a fan platform for remixing participating artists’ tracks in development.

Rowan, Zach, Shubham, Jennifer, and Nate — the humans behind The Rundown