docs(architecture): baseline current design (#109)

Capture the brownfield architecture and its relationship to the project vision.\n\n- add the current-state SAD and five retrospective ADRs\n- classify vision vectors against implementation evidence\n- record requirements, risks, gates, and construction handoff

.aiwg/architecture/vision-alignment.md

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+# Vision-to-Code Alignment Matrix
+
+**Reference:** `VISION.md`  
+**Rule:** Alignment is directional; only code/tests/receipts establish implementation maturity.
+
+| Vision vector | Current maturity | Current evidence | Gap / next architectural proof |
+| --- | --- | --- | --- |
+| Cognitive architecture | Partial / experimental | Admiral planning, context packs, prompts, operator roles, adjudication | Demonstrate durable reasoning-state architecture and comparative outcomes beyond prompt composition |
+| Swarm dynamics | Partial / experimental | Eight operator archetypes, orchestration, task assignment, shared mission context | Reproducible end-to-end swarm benchmark showing coordination reliability and value over solo baselines |
+| Adversarial machine learning | Research / partial | Refusal-frontier probes, model matrices, adversarial benchmarks, anti-fitting | Formal threat model and stable adaptive defenses against prompt/model manipulation |
+| Continuous autonomous operations | Future with small foundations | Mission lifecycle, lessons, update/preflight tooling | Persistent scheduler, safe pause/resume, operator governance, resource budgets, and incident controls |
+| Knowledge architecture | Partial / research | Evidence, reports, lessons, benchmark corpora, context packs | Unified provenance-aware knowledge model with retention, conflict, and poisoning controls |
+| Distributed and edge execution | Future | Local agents, local model servers, Docker, multiple surfaces | Authenticated worker protocol, tenancy, distributed state, failure recovery, and zero-trust execution design |
+| Evaluation science | Strongly implemented | `bench/`, `verify-claims`, ground truth, model matrix, anti-fitting/provenance CI | Broaden external replication, workload/cost measures, and statistically powered comparisons |
+
+## Alignment Rules
+
+1. `README.md` and `FEATURES.md` maturity labels are product claims and must remain consistent with this matrix.
+2. A benchmark validates only its defined corpus, model, harness, and metric.
+3. Promotion to stable requires deterministic safety tests, an operational path, documentation, and a reproducible receipt.
+4. Persistent autonomy, distributed execution, or shared knowledge services trigger new threat models and ADRs.
+5. The SAD is updated from implementation evidence; the vision is not reverse-engineered into fictitious components.