Agent learning owns how PodMan can improve its own prompts, detector rules, policies, verifier choices, and routing strategies. This is deliberately narrower than team memory: it is a versioned strategy layer, not autonomous code rewriting.

The constraints in ../../CLAUDE.md still govern this track: one visible self-improving loop, demo stability, no broad platform rewrite, no dashboard-first product, and no overclaiming.

Files

File	Purpose
`spec.md`	Read-only data contract for runs, traces, strategies, and proposals
`policy.md`	Promotion, rejection, evidence, and safety rules
`prompt.md`	Evaluator prompt for narrow strategy improvements
`plan.md`	v1 implementation order if this track is added

What Is Implemented Now

Shared TypeScript contracts for AgentRun, AgentTraceEvent, StrategyVersion, and LearningProposal.
Exact signature recall and accepted/dismissed outcomes that can later feed strategy decisions.
Documentation of future collections and indexes.

What Is Intentionally Cut

Full autonomous strategy promotion.
Autonomous code rewriting.
Multi-agent strategy debates.
Claims that PodMan trains or rewrites itself from live usage today.

Demo Proof Path

Observe screen/git state -> detect collision -> send intervention -> accept or dismiss outcome -> recall similar event -> show changed graph or changed behavior. In the current demo, this proof is team-memory learning; agent strategy promotion remains planned unless records are added.