Commit History
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Wave 7: Phase 2-4 of deep work loop — backlog, parallel research, three ADRs
Imports the gap-closer wave from VISION_VALIDATION.md as a structured backlog, records the deep work loop log, and locks three architecture decisions backed by primary-source research from three subagent recons. Backlog items (CPU-only, no GPU budget): - Spike 006 — real HF model smoke (Wave 7 next) - Spike 007 — real trace ingestion (Wave 8) - Spike 008 — Streaming DiLoCo smoke (Wave 9) - Wave 10 — packaging (pyproject.toml + examples/) - Spike 002a-mini — Modal-gated GPU smoke (Phase 10) Research (docs/research/, 1168 lines total): - MODAL_RECONNAISSANCE.md — Modal pricing + setup, primary-sourced from modal.com/pricing and modal.com/docs. Verdict: Modal L4 is $0.08-0.13 per smoke run but loses to local 5090 by 10x on iteration cycle (3-5min vs 25-40s). Modal becomes correct for parallel sweeps, 7B+ models, multi-node training, or CI repro — none of which apply to gap-closer wave. - DILOCO_RECONNAISSANCE.md — audited 5 candidates. meta-pytorch/torchft wins: BSD-3, 312 com…ac4bfb4