Yahya Alhinai
38 lines
1.2 KiB
Markdown
38 lines
1.2 KiB
Markdown
# Continual Learning
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Status: demo-backed / active
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PodMan's continual-learning track owns team memory: what the system learns about
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files, collisions, interventions, outcomes, and future routing for a pod.
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## Files
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| File | Purpose |
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| --- | --- |
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| [`spec.md`](spec.md) | Data model and observe/store/predict/outcome/adapt loop |
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| [`policy.md`](policy.md) | What PodMan may and may not remember |
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| [`prompt.md`](prompt.md) | Memory-agent prompt for outcome-backed learning |
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| [`plan.md`](plan.md) | Demo build order and acceptance criteria |
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## What Is Implemented Now
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- MongoDB-backed `observations`, `collisions`, `interventions`, `outcomes`,
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`engineer_states`, and `team_model` records.
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- Exact signature recall for prior accepted and dismissed outcomes.
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- Outcome writes through `POST /api/outcome`.
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- Team memory graph edges from accepted real outcomes.
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- No raw screenshots or recordings are stored.
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## What Is Intentionally Cut
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- Autonomous model training.
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- Broad cross-pod generalization.
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- Raw screen capture retention.
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- Vector recall as a dependency for the demo proof.
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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.
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