Initial commit: AirCoding V1.0.0 Alpha architecture baseline

Complete architecture document set with multi-model review remediation:
- Frozen interface contracts, runtime semantics, DB schemas
- Event/tool/error/provider registries
- Scheduler and main agent state machines
- C4 module/code views, solution architecture, baseline V1
- Multi-model review reports and joint assessment
- Phase-gate remediation complete (P0/P1/P2/UX resolved)
- Implementation plan with T-000A through T-045
- Reference folders kept as placeholders only

AirPlan/docs/architecture/branch-deepcode-cli/README.md

@@ -0,0 +1,36 @@
+# DeepCode CLI Branch
+
+Date: 2026-05-28
+Status: AirCoding mainline branch, pre-design research phase
+
+DeepCode CLI is a mainline AirCoding branch (not a downstream simplification like VibeBox). It explores integrating DeepSeek's model architecture innovations and research capabilities into the AirCoding agent runtime.
+
+## Reference Documents
+
+- [DeepSeek Research Survey](deepseek-research-survey.md) — Complete inventory of DeepSeek papers, models, architectures, and technical innovations (36 repos, ~395K stars)
+
+## Key DeepSeek Innovations Relevant to DeepCode CLI
+
+1. **Multi-head Latent Attention (MLA)** — 93% KV cache reduction for long code contexts
+2. **DeepSeekMoE** — Fine-grained experts + shared experts, 37B activated from 671B total
+3. **GRPO** — RL without critic model, applicable to code/debug agent training
+4. **DeepSeek Sparse Attention** — Efficient long-context processing
+5. **DeepSeek-Coder/V2** — Fill-in-Middle, SWE-bench, Codeforces competitive
+6. **DeepSeek-R1** — Emergent chain-of-thought reasoning via pure RL
+7. **DeepSeek-Prover-V2** — Formal Lean 4 theorem proving
+8. **DeepSeek-Math-V2** — Self-verifiable reasoning, IMO 2025 gold
+9. **Engram** — Conditional memory sparsity as new axis beyond MoE
+10. **DeepSeek-OCR/OCR-2** — Visual understanding for GUI evidence
+11. **3FS/FlashMLA/DeepGEMM/DeepEP/DualPipe** — Full inference infrastructure stack
+
+## Open Design Questions
+
+1. How does DeepCode CLI relate to AirCoding mainline — does it add DeepSeek as a provider, or fork architecture?
+2. Which DeepSeek innovations should DeepCode CLI adopt at the runtime level vs. treat as provider capabilities?
+3. Does DeepCode CLI target DeepSeek models as primary, or remain provider-agnostic with DeepSeek optimizations?
+4. Should MLA/MoE-aware context assembly be part of the runtime, or handled by provider adapter?
+5. How should formal proving (Prover-V2) integrate with the existing review/debug workflow?
+6. Should self-verifiable reasoning (Math-V2 style) influence the verification architecture?
+7. Does DeepCode CLI need its own GRPO-trained code agent, or reuse general DeepSeek models?
+8. How does the Engram conditional memory concept map to AirCoding's memory/skills system?
+9. Should infrastructure tools (3FS, smallpond) be optional capabilities for large-codebase workflows?