chore: scaffold oO monorepo with architecture, roadmap, and module stubs

ml/README.md

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+# ml/
+
+Python. Owns models, features, training, online scoring.
+
+| Dir | Role | Phase |
+|---|---|---|
+| `serving/` | FastAPI online scorer (`/score`), called by `recommender` | 1 |
+| `features/` | feature definitions + store adapter (Feast later) | 1 |
+| `pipelines/` | batch feature + training DAGs (Prefect/Airflow) | 4 |
+| `registry/` | MLflow-backed model registry integration | 4 |
+| `experiments/` | A/B assignment + multi-armed bandit policies | 4 |
+| `notebooks/` | research; never imported by production code | — |
+
+## Principles
+
+- Every model has a **model card** in `registry/` describing inputs, offline metrics, fairness checks, and rollout history.
+- Online inference must be stateless and < 50ms p99.
+- Training reads from the offline feature store; serving reads from the online feature store; definitions are shared (no train/serve skew).
+- Shadow deploys before any policy change that affects real users.