Prompt: "reason step by step"
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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.
Cutting tool-output tokens can raise your AI agent bill instead of lowering it. Why prompt caching means token reduction isn't cost reduction, and what to measure instead.
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.
