AI Fluency Capability Map P0 Handoff
The Personalization Engine now has a headless product object: learner and role context becomes capability map, simulation, evaluation, proof, and the next curriculum move.
AIFluencyCapabilityMap is now the P0 output. Title coverage, role packets, workflows, tools, evaluator scores, proof refs, and future embeddings all feed five capability layers instead of sitting as disconnected artifacts.
What Changed
Added capability, workflow requirement, map, observation, proof index, and aggregate heatmap models.
Generated decisions and API fixtures now carry the map through `/assess` and nested readiness.
Added `ai-fluency-capability-map` with JSON, JSONL, Markdown, and HTML receipts.
The evaluator now emits dimension scores for task exposure, tool proficiency, judgment quality, data discipline, and outcome evidence. The production readiness board now treats AI Fluency as the product spine and title coverage as an input.
Generated Proof
| Metric | Value |
|---|---|
| Capability layers | 5 |
| Capability definitions | 5 |
| Workflow requirements | 3 |
| Observations | 5 |
| Proof artifact refs | 1 |
| Suppressed heatmap rows | 5 |
| Overall score | 0.858 |
| Failed checks | 0 |
Scope remains local and headless: no public runtime, no real-user data, no external writes, no production telemetry, and no embedding authority promotion.
Files To Know
| Path | Purpose |
|---|---|
src/aina_data_engine/ai_fluency_capability.py | Builder, command logic, and proof report output. |
src/aina_data_engine/schemas.py | New models and additive readiness/profile/evaluator fields. |
src/aina_data_engine/runtime.py | Attaches the capability map to runtime decisions. |
src/aina_data_engine/evaluator.py | Emits five dimension scores and observation refs. |
src/aina_data_engine/api_contracts.py | Adds map support to `/assess` and nested readiness payloads. |
docs/planning/aina-production-readiness-board-2026-06-12.md | Revised mission, milestones, and next goal. |
Resume Commands
cd /srv/aina/aina-data-engine-room
git status --short --branch
uv run aina-data-engine --root /srv/aina/aina-data-engine-room ain-506-p0-gate
uv run aina-data-engine --root /srv/aina/aina-data-engine-room ain-510-retrieval-promotion-gate
uv run aina-data-engine --root /srv/aina/aina-data-engine-room ai-fluency-capability-map
uv run aina-data-engine --root /srv/aina/aina-data-engine-room validate
jq '{schema_version, valid, status, metrics, checks, scope}' artifacts/validation/ai_fluency_capability_map_v0.json
Build capability-source authority first, then top 500/top 1,000 capability coverage. Do not regenerate labels or embed more data before checking donor repos, Linear, PKM/Wiki/Daily, and existing receipts.