Yahya Alhinai
44 lines
1.6 KiB
Markdown
44 lines
1.6 KiB
Markdown
# Agent Learning
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Status: planned / narrow v1
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Agent learning owns how PodMan can improve its own prompts, detector rules,
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policies, verifier choices, and routing strategies. This is deliberately
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narrower than team memory: it is a versioned strategy layer, not autonomous code
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rewriting.
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The constraints in [`../../CLAUDE.md`](../../CLAUDE.md) still govern this track:
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one visible self-improving loop, demo stability, no broad platform rewrite, no
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dashboard-first product, and no overclaiming.
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## Files
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| File | Purpose |
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| --- | --- |
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| [`spec.md`](spec.md) | Read-only data contract for runs, traces, strategies, and proposals |
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| [`policy.md`](policy.md) | Promotion, rejection, evidence, and safety rules |
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| [`prompt.md`](prompt.md) | Evaluator prompt for narrow strategy improvements |
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| [`plan.md`](plan.md) | v1 implementation order if this track is added |
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## What Is Implemented Now
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- Shared TypeScript contracts for `AgentRun`, `AgentTraceEvent`,
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`StrategyVersion`, and `LearningProposal`.
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- Exact signature recall and accepted/dismissed outcomes that can later feed
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strategy decisions.
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- Documentation of future collections and indexes.
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## What Is Intentionally Cut
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- Full autonomous strategy promotion.
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- Autonomous code rewriting.
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- Multi-agent strategy debates.
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- Claims that PodMan trains or rewrites itself from live usage today.
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## Demo Proof Path
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Observe screen/git state -> detect collision -> send intervention -> accept or
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dismiss outcome -> recall similar event -> show changed graph or changed
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behavior. In the current demo, this proof is team-memory learning; agent
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strategy promotion remains planned unless records are added.
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