The Gate That Said No
Whether to adopt a tool you built is itself a decision under uncertainty, so it deserves a decision rule, not a leaderboard. I built a pre-committed, …
essaysbayesianaidecision-theory
Essays
Make Your OpenClaw Agent Cheaper, and Measure It Yourself
credence-pi is an OpenClaw plugin plus a local daemon that learns your agent and acts at two points by expected utility: it routes each turn to the cheapest …
essaysbayesianaidecision-theory
Make Your OpenClaw Cheaper and Harder to Fool
credence-pi is an OpenClaw plugin plus a local daemon that learns your agent's behaviour and governs its tool calls by expected utility: it blocks the calls …
essaysbayesianaidecision-theory
What a Regex Can't Do
The governor from 'The Brain is Opaque to the Body' now ships as an OpenClaw plugin: wasted tool calls blocked at precision and recall 1.0 on real sessions, …
essaysbayesianaidecision-theory
The Brain is Opaque to the Body
A first-pass body-brain architecture for governing a coding agent's tool_call hook with a Bayesian decision-theoretic brain. The wire schema is fixed by what …
essaysbayesianaidecision-theory
Three Types and a Funeral for Your Inference Library
What would it take to build an agent whose behaviour is derived from a few fundamentals the way physics is derived from conservation laws? Three types, four …
juliabayesianmachine-learningaiessays
Keeping the Coding Agent on the Straight and Narrow
A companion to the PKM Phase 1 post. The foundation was built by two AIs — Claude.ai for design, Claude Code for implementation — with a spec as the contract …
essaysaipython
A Content-Addressed Foundation for Personal Knowledge
Eleven million words of personal documents, four canonical questions none of Khoj, Paperless-ngx, Obsidian, or Karpathy's LLM Wiki can answer, and a …
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Ninety-Six Percent Cheaper and Slightly Better
Credence-proxy sits between an agent and its LLM providers, learns which model is good for which category, and routes accordingly. On an OpenClaw benchmark it …
essaysbayesianmachine-learningai
The Prompting Gradient
Each prompting technique helps. Reasoning traces, strategy guidance, cross-question history --- each one improves accuracy and score. None of them closes the …
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The Agent That Invents Its Own Rules
Most agents are given a fixed set of decision rules. Credence's second tier generates candidate rules from sensor features, scores them by complexity, and lets …
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Sixty-Two Percent Correct and Winning by a Hundred and Twenty Points
A Bayesian decision-theoretic agent scores lower on accuracy than every LLM variant it competes against --- and beats the best of them by 120 points. The …
essaysbayesianmachine-learningai
The Bitter Lesson Has No Utility Function
I wrote about decision theory fading from AI. Hacker News said I was annoyed at Rich Sutton's Bitter Lesson. I wasn't. But the misreading proves the point.
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Why We Stopped Using the Mathematics That Works
Someone asked why decision theory stopped being widely used in AI. The answer involves ImageNet, academic departments, and the seductive power of not having to …
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Agentic AI Is Neither Intelligent Nor an Agent
I built a Bayesian agent and set it against LangChain on a tool-use benchmark. LangChain got more answers right and still lost — by 120 points.
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On Owning Your Data
Why I reverse-engineered a cheap Bluetooth scale to keep my health data out of the cloud
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