Add member work history and learning docs

docs/agent-learning/README.md

@@ -0,0 +1,43 @@
+# Agent Learning
+
+Status: planned / narrow v1
+
+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`](../../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`](spec.md) | Read-only data contract for runs, traces, strategies, and proposals |
+| [`policy.md`](policy.md) | Promotion, rejection, evidence, and safety rules |
+| [`prompt.md`](prompt.md) | Evaluator prompt for narrow strategy improvements |
+| [`plan.md`](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.

docs/agent-learning/plan.md

@@ -1,6 +1,6 @@
 # Agent Learning Plan
 
-Status: draft  
+Status: planned / narrow v1
 Goal: ship a visible recursive self-improvement loop without overbuilding
 
 ## Must-Have
@@ -86,4 +86,3 @@ rejected or open.
 - The changed behavior is visible.
 - The strategy has a parent and evidence.
 - Rejected or failed changes are not deleted.
-

docs/agent-learning/policy.md

@@ -1,6 +1,6 @@
 # Agent Learning Policy
 
-Status: draft  
+Status: planned / narrow v1
 Scope: guardrails for recursive self-improvement
 
 ## Prime Rule
@@ -81,4 +81,3 @@ Reject and retain the candidate when:
 Seeded strategy versions are acceptable when labeled as demo-backed. Do not claim
 a strategy was learned live unless a run and outcome actually created the
 promotion evidence.
-

docs/agent-learning/spec.md

@@ -1,7 +1,7 @@
 # Agent Learning Spec
 
-Status: draft  
-Scope: how PodMan agents improve their own prompts, policies, detectors, and routing behavior  
+Status: planned / narrow v1
+Scope: how PodMan agents improve their own prompts, policies, detectors, and routing behavior
 Owner: agent learning / recursive self-improvement
 
 ## Purpose
@@ -19,6 +19,20 @@ The demo claim:
 5. The new strategy is versioned.
 6. A later run uses the improved strategy and shows a better result.
 
+## What Is Implemented Now
+
+- Shared TypeScript record shapes exist for the core objects below.
+- Exact signature recall and accepted/dismissed outcomes exist in the team
+  memory loop.
+- No write path currently promotes autonomous strategy changes.
+
+## What Is Intentionally Cut
+
+- Autonomous code rewriting.
+- Full autonomous strategy promotion.
+- Multi-agent strategy debates.
+- Claims that model self-evaluation alone can promote a strategy.
+
 ## Core Objects
 
 ### Agent run
@@ -182,4 +196,3 @@ Graph discovery may show:
 - Rejected strategies are retained with a reason.
 - Agent traces are append-only.
 - The system can answer: "What changed, why, and did it help?"
-