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

docs/adr/0001-monorepo-polyglot.md

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+# ADR-0001: Polyglot monorepo, TS for apps, Python for ML
+
+## Status
+Accepted — 2026-04-13
+
+## Context
+We ship web and mobile clients, backend services, and ML training/serving. Splitting into many repos early creates cross-repo PRs for every contract change and hurts velocity.
+
+## Decision
+One monorepo, managed with pnpm workspaces for TS and uv/poetry for Python. Shared contracts live in `packages/shared-types` generated from OpenAPI. ML is Python; everything else is TS.
+
+## Consequences
+- One CI system, one versioning flow, atomic cross-service PRs.
+- Requires disciplined boundaries: services must still be independently deployable.
+- Tooling complexity: two package managers, two lint stacks. Acceptable given the ML/app split.

docs/adr/0002-recommender-contract.md

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+# ADR-0002: Recommender as the stable contract, policy as a plugin
+
+## Status
+Accepted — 2026-04-13
+
+## Context
+v0 picks a random Todoist task. v1+ will use a contextual bandit, then learned rankers, then collaborative signals. If the HTTP contract and the candidate-generation path are coupled to today's "random", every change is a migration.
+
+## Decision
+`recommender` exposes `POST /recommend` as the one stable contract. Internally it has three seams:
+1. **Candidate sources** — async functions that yield `TipCandidate`s from integrations, advice libraries, etc.
+2. **Context assembler** — pulls features (today: inline; later: feature store).
+3. **Policy** — `Policy.pick(candidates, context) → tip`. Registered by name; selected per-request by the experiments framework (Phase 4) or a static config (now).
+
+Swapping a policy never changes the contract or the client.
+
+## Consequences
+- v0 policy is `RandomPolicy`, trivially 50 lines.
+- v1 moves scoring to `ml/serving` behind the same `Policy` interface (`RemotePolicy` wrapper).
+- A/B is introduced without touching clients.