Department series
The Harness
How to work with agents day to day — memory, coordination, habitats.
Dispatches
Filed from the floor — the patterns unfreeze in Miami, and the Linux moment arrives on the laptop.
- The harness is to the neural net what the compiler was to source code — and the harness is open. — Neural Harness · May 1
Proofs
Show your work — 131 models, honest margins, and the thesis that it's agents all the way down.
- Agents need habitats — state, memory, and bounded decisions, living in a git repo you can inspect. — The Agent Habitat · Feb 5
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The Agent Habitat
An agent isn't just automation with LLM calls. It carries state, accumulates memory, and makes bounded decisions under uncertainty — and a git repo is where all of that lives.
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The Data Flywheel Pattern
Build applications by dropping in data and letting AI handle parsing, structuring, and synthesis. Three case studies.
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Claude Code, not Code
The real power of Claude Code isn't writing software—it's orchestrating skills for research, newsletters, browser automation, and turning one-off requests into repeatable workflows.
Instruments
Reading the gauges — before you trust an agent, you need instruments that show you when it's lying.
Field Trials
Take the tools outside and see what breaks — agents become products, and products can be raced.
- How you talk to an agent is an operational parameter — clarity and directness measurably change the work you get back. — Don't Be Passive-Aggressive with Your Agents · Jun 25
Blueprints
Drawing up the system — memory, MCP, structured output: the quarter the chat window stopped being the product.
- Memory is the missing organ: a file of project rules turns an agent from intern into colleague. — Coding with a Memory System · Mar 30
