Kamen Dimitrov retweeted
I highly recommend cloudflare's security audit skill: github.com/cloudflare/securi…
Run it on all your software. Run it with the free models. Use it even if you used a model to audit something - it will find much more things. Works in all agent harnesses and is model independent.
Kamen Dimitrov retweeted
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.
• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from scratch in under 4 months
Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
Kamen Dimitrov retweeted
Here's the replay of our Evals for Financial Services at @aiDotEngineer NYC 🗽
It was so much fun delivering this workshop with @annabellschfr last week in the world's financial capital. Getting evals right remains a challenge in regulated industries, and we provide guidance to help you get started.
youtube.com/watch?v=obfPzbap…
Kamen Dimitrov retweeted
We are making Markdown files work natively across Google Drive and Docs.
You can now preview .md files in Drive, open them in Docs, edit them, comment on them, and collaborate without converting the file into a Google Doc!
Kamen Dimitrov retweeted
This is an extremely good watch.
The things that felt novel/interesting to me:
1. Lock down your agents
Humans tend to like 'sharp knife' abstractions - that are powerful, but you can cut yourself if your use them wrong. Lauren says agents perform much better in extremely locked-down environments. Abstractions are designed so they can't screw up, and lint rules enforce it.
They built a whole internal framework (Dune) to keep the agent on track.
That helps optimise agents that don't have a large context window to work productively in your codebase.
2. Create verification infrastructure
To trust the results of any agent, you either need to sit and watch it OR have it provide evidence of its improvement. This has always made sense to me, but Lauren really pushes it hard here:
- Invest in custom CLI's that let the agent drive the app and measure its performance
- Make the app "factory ready" from the get-go - i.e. deployable to an environment where the agent can mess about with it
3. Feature Maps
Lauren's software factory (what she calls an 'outer loop') often requires the agent to break down vague bug reports from users and to turn those into potential fixes.
To aid that, they built a 'feature map' of all the main features in their application, which describe exactly how the app is supposed to function.
This has become essential for helping the agent navigate the codebase, and figure out quickly how things are supposed to work. It's maintained along with the codebase, and kept in sync via automations.
This is the kind of documentation I usually warn against. It goes stale quickly and can confuse agents if it's not kept up to date.
But Lauren's team are using it as critical navigation infrastructure, and it makes it possible for agents to explore faster and better - even on a large codebase. So it sounds like navigation docs like this are worth it if they enable new behavior.
Banger talk - watch the whole thing on 2x.
here's how i shipped 2,500 PRs last month to production
this was originally supposed to be for Cursor Compile in London. i couldn't make it since i was livestreaming for Grok @Bot Galaxy so i'm making it available for free here on X! watch it on 2x speed, i talk slowly
just take it easy on the fearmongering and read what this guy has to say!
Jev by @typesafeai is so fun! In this demo I use it to classify support conversations in almost realtime and flag the critical moment a human-in-the-loop is needed
Kamen Dimitrov retweeted
Introducing Atlas:
The world's first multimodal world model that generates image and video frames with pixel-perfect camera control and reconstructs them in 3D.
Model the world, move the camera, and simulate space & time.
Kamen Dimitrov retweeted
Crossword layout of all 1,009 distinct words of 12 or more letters in Moby Dick, arranged in the shape of a whale
One-shot by Claude Fable 5 Max
🥳
Introducing Unsloth Desktop 🦥
The first desktop app to run and train models locally.
• Open-source. Runs on Mac, Windows and Linux
• Supports MLX, diffusion image/video, audio, GGUF
• Connect Claude Code and Codex to local LLMs
• 50% more accurate, self-healing tool calls + sandboxed code exec
• Works for CPU + multiGPU setups - NVIDIA, AMD, Intel, Mac
• Train models 2× faster with 70% less VRAM
• Private web search, deep research, RAG, MCP and exports (NVFP4, GGUF)
• Use Unsloth’s OpenAI-compatible API and cloud models
• Securely deploy LLMs remotely and access anywhere
Unsloth Desktop is now available on unsloth.ai and GitHub.
GitHub: github.com/unslothai/unsloth
Blog and Guide: unsloth.ai/docs/desktop
Kamen Dimitrov retweeted
recommended reading. similar observations on my end, albeit at much smaller scale.
























