Blog
From Prompt to Context to Harness: Notes on the Agent OS
2026-05-27
Coding with AI keeps shifting under us, from prompt engineering to context engineering to harness engineering. A working-through of what a harness actually is, two ways to build an operating system for agents, and a guess at how models might start writing their own skills.
The Spec Is the Code: A Loop for Agent-Driven Development
2026-05-23
When agents write the code, the spec becomes the artifact you actually review. This sketches a spec-exec-eval-bench-improve loop — the format, the agent swarm, and the self-improving harness it would take to make it real — while engaging the spec-driven camp that already named most of the pieces.
Skills, Tools, MCP, Agents: How I Think About the Pieces
2026-03-24
A working taxonomy of the agent stack — tools, MCP, skills, and agents — plus notes on the parts I find more interesting: subagents versus agent teams, and the context- and harness-engineering ideas that seem to decide how far a single setup can scale.
The Filesystem Is Agent Infrastructure
2026-03-16
Three connected ideas about the substrate agents run on: the filesystem as critical infrastructure (and whether a tree is the right shape for it), the benchmark gap for skills and agents that's only now starting to close, and whether we should save prompts instead of generated code.
Chunk Size Might Beat Model Power
2026-03-12
A short experiment idea and the reasoning behind it: a weaker model with better workflow and tighter task boundaries might outperform a stronger one — and a hunch that harness engineering is more about rules than flows.
Field Notes from Vibe Coding
2026-03-11
Learnings from a stretch of vibe coding with Claude Code, skills, and agents — why subagents are usually enough for coding, how complexity breeds regressions, the OpenClaw files-as-memory idea and its failure mode, and a three-role sandbox I'm sketching for an agent that holds personal data.
Make Regenerating Code Safe, Not Generated Code Good
2026-01-30
Vibe coding shines on small tasks but I'm skeptical it scales to large projects. A colleague argues the bottleneck shifts from prompts to context — I'm not even sure that's solvable. My hunch: stop trying to make generated code better and instead make regenerating it safe, with small isolated units and a controlled blast radius.