Programmer building software systems that humans and agents can understand, change, and verify.
A curious life in software systems: architecture, tools, notes, and experiments.
AI coding does not make architecture less important. It changes what architecture must control.
When editing becomes cheap, the expensive parts become understanding, validation, review, rollout, and recovery.
| Project | Role | What it explores |
|---|---|---|
| Agent-operable Architecture | Architecture | How codebases can expose truth, boundaries, proofs, and safe change paths for humans and agents |
| Agent Skill Control Theory | Agent control | A framework for designing, evaluating, and evolving LLM agent skills |
| DBX Skills | Practice | Claude/Codex skills for planning, reviewing, architecture health, and engineering workflows |
| db.oneir.xyz | Writing | Notes on AI coding, architecture, programming foundations, and software judgment |
- Make source of truth explicit.
- Keep semantic changes locally understandable.
- Bind success claims to executable evidence.
- Treat repository context as part of the architecture.
- Report architecture findings by future failure mode, not by taste alone.
Codebase side Agent-operable Architecture
Agent side Agent Skill Control Theory
Workflow side DBX Skills
Writing side db.oneir.xyz
OCaml 2 hrs 47 mins █████████████▓░░░░░░░░░░░ 55.10 %
Markdown 1 hr 58 mins █████████▓░░░░░░░░░░░░░░░ 39.05 %
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YAML 6 mins ▓░░░░░░░░░░░░░░░░░░░░░░░░ 02.29 %
JSON 2 mins ▒░░░░░░░░░░░░░░░░░░░░░░░░ 00.76 %