Prompt: "reason step by step"
text-to-image
Turning research into products people actually use.
Picked things I'm genuinely into.
Thoughts on AI, leadership, and where this is all going.
The tools I reach for every day.
Harness engineering is where AI agent capability actually lives. Context management, tools, memory and a real workspace decide how much of a model's intelligence you get, explained through four interactive demos.
How an OpenAI system resolved or advanced ten long-standing problems in mathematics and theoretical computer science, with every argument formalised into a machine-checked Lean proof, explained through ten interactive demos.
Why LLMs sometimes print tokens like [control_28] mid-conversation, why it's a serving stack problem rather than a model problem, and why the model can't recover from it on its own.
