feat: add learner memory ingestion

.planning/phases/003-learner-memory/003-PLAN.md

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+# Phase 3 Plan: Learner Memory
+
+**Status:** Ready for execution
+**Phase Goal:** Convert graded answer evidence into structured learner memory.
+
+## Requirements Covered
+
+- MEM-01: System stores learner profile with role, stack, timeline, and
+  preferences.
+- MEM-02: System stores concept mastery states with evidence.
+- MEM-03: System stores recurring misconceptions with supporting answers.
+- MEM-04: System stores intervention history and review schedule.
+- MEM-05: Temporary session context does not become durable memory without
+  evidence.
+
+## Tasks
+
+### 1. Add learner memory package
+
+- Create `internal/learnermemory`.
+- Define profile, concept mastery, misconception, intervention, review schedule,
+  and snapshot types.
+- Add in-memory store with clear interface.
+
+### 2. Add memory extraction workflow output
+
+- Extend `workflows.StubRunner.ExtractLearningMemory` to return evidenced
+  memory update candidates from a graded answer.
+- Ensure candidates without evidence are not applied.
+
+### 3. Wire diagnostic answers to memory
+
+- Inject learner memory service into interview service.
+- After grading an answer, extract and apply memory updates.
+- Keep diagnostic session records and learner memory records separate.
+
+### 4. Add memory read endpoint
+
+- Add `GET /api/v1/learners/{userID}/memory`.
+- Return learner profile, mastery, misconceptions, interventions, and review
+  schedule.
+
+### 5. Add tests and verification
+
+- Test memory applies only evidenced updates.
+- Test diagnostic answer submission updates learner memory.
+- Test memory HTTP read endpoint.
+- Run Go tests, OpenSpec validation, and line-count check.
+
+## Out of Scope
+
+- Persistent database.
+- Memory ranking/decay.
+- Progression readiness map.
+- Frontend UI.
+
+---
+*Plan created: 2026-04-26*