Learn Kaizen by using it on a repo where you already run a coding agent (Cursor, Claude Code, Codex, or another tailed agent). You will wire capture, read the local store, interpret metrics, run a retro, and see how experiments and optional sync fit the same loop.
Kaizen is a feedback loop, not a dashboard:
flowchart LR
capture[Capture]
summarise[Summarise]
change[ProposeChange]
measure[Measure]
capture --> summarise
summarise --> change
change --> measure
measure --> capture
Transcripts and hooks capture; summary, insights, guidance, and metrics summarise; retro, eval, and exp propose and measure change. The deep data story is in telemetry-journey.md.
After you have sessions in the store you can run kaizen eval run to call an LLM judge (requires [eval].enabled = true and ANTHROPIC_API_KEY). Low-scoring sessions appear as the H15 bet in kaizen retro. See evaluation usage and config.md#eval for setup.
Optional: enable [collect.outcomes] and [collect.system_sampler] in config to attach post-stop test rows and per-PID CPU/RSS samples (local-only); see outcomes.md and system-telemetry.md.
- How
initwires hooks and where data lands on disk. - When to use cache-first reads vs
--refresh. - How
--source local|provider|mixedchanges observe-style commands when sync identity and[telemetry.query]are configured (optional). - How
--all-workspacesaggregates across repos you have opened. - Which workflows are MCP vs shell-only.
- Where to read next for proxy, sync, and experiments detail.
| Time | Do this |
|---|---|
| ~5 min | Part 1 → Part 2 first sections |
| ~30 min | Parts 1–4 |
| Deep dive | All parts 1–9 + linked reference docs |
- Setup: install, init, doctor
- Observe: Web, sessions, summary, TUI
- Interpret: insights and guidance
- Repo intelligence: metrics and refresh
- Improve: retro
- Improve: experiments
- Optional: proxy, sync, telemetry
- Agents calling Kaizen: MCP
- Housekeeping: gc and completions
Full command flags: usage.md. Glossary: concepts.md.