Something I've realized about LLM tool use is that it means that if you can reduce a problem to something that can be solved by an LLM in a sandbox using tools in a loop, you can brute force that problem.
The challenge then becomes identifying those problems and figuring out how to configure a sandbox for them, what tools to provide and how to define the success criteria for the model.
That still takes significant skill and experience, but it's at a higher level than chewing through that problem using trial and error by hand.
My x86 assembly experiment with Claude Code was the thing that made this click for me.
Recent articles
- LLM 0.27, the annotated release notes: GPT-5 and improved tool calling - 11th August 2025
- Qwen3-4B-Thinking: "This is art - pelicans don't ride bikes!" - 10th August 2025
- My Lethal Trifecta talk at the Bay Area AI Security Meetup - 9th August 2025