docs: EPIPHANIES.md — ledger efficiency + ambient arc-knowledge loss findings#111
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Create .claude/board/EPIPHANIES.md with the finding. PR #110 + lance-graph PR #213 demonstrated the dumb-bookkeeper pattern: ~90 seconds, Haiku, enumerate+match+append. Result is a grep-addressable index of every shipped artifact keyed by the prompt-file brief that birthed it. For every future "what did we ship about X" query the ledger replaces a full-codebase grep with a single line — ~25 tokens vs ~25M tokens. Seven orders of magnitude cheaper. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh
…ambient) Third finding appended to EPIPHANIES.md — orthogonal to cold-start tax (20-30 turns) and find-code discount (10⁷×). This is the AMBIENT channel: 30-50% of every session's token budget burns on rediscovering what code paths exist / what was tried / why code is shaped the way it is. The prompt↔PR ledger collapses all three channels to two text-file reads: - Cold-start: 20-30 turns → 3-5 turns (~6×) - Find-code: ~25M tokens → ~25 tokens (10⁷×) - Ambient: 30-50% → 0% (2×-eternal) https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh
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Summary
Create
.claude/board/EPIPHANIES.mdwith two findings:First deployments: PR #110 (ndarray, 25 prompts mapped, ~90s) + PR #213 (lance-graph, 41 prompts mapped).
Test plan
https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh