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Mine AGENTS.md brain onto disk: resolve TODOs, extract AI subsystem guide

Retrofit per the playbook. Resolve both AGENTS.md TODOs with verified
facts (make-target set; db:seed is live at image-build + local dev),
reconcile the AI-provider count (4 files -> 5 registered providers), and
extract the AI subsystem cheat-sheet into docs/guides/ai-subsystem.md,
lazy-loaded via a .claude/rules symlink with an index line in AGENTS.md.

All AGENTS.md commands verified green (tests 177/177, build, tsc, lint).

2026-06-12 20:26:14 -05:00

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paths

proof-of-work/lib/ai/**

proof-of-work/app/api/ai/**

AI subsystem

Scoped guidance for the AI generation subsystem (proof-of-work/lib/ai/** and the generate/generations route handlers). Whole-repo rules live in AGENTS.md.

Architecture

generate/route.ts kicks off a detached background runner (generationRunner.ts) and returns an id; the client attaches via SSE (generations/[id]/stream) and can also poll the row. Navigating away does NOT cancel generation.
System prompt = systemPromptBase.ts (output contract: JSON-only, library exerciseIds only, suggested weights) + the template's coaching prompt + PROGRAM_OUTPUT_SHAPE + library + optional history block (historyContext.ts).
Multi-config: AIConfigProfile rows per user; UserPreferences.activeAIConfigId points at the active one and is mirrored into the legacy ai* columns for back-compat.

Provider abstraction

Each provider yields an async iterable of GenerateChunk (text / usage / done / error); add new ones under lib/ai/providers/ and register in index.ts. openai.ts exports both openai and openai-compatible, so the four provider files register 5 providers (claude, openai, openai-compatible, gemini, ollama).
Streaming AI uses SSE; partial JSON is recovered with lib/ai/lenientJson.ts.
Pricing/model menus live in lib/ai/pricing.ts (PRICES, MODEL_MENU) — keep them paired so every menu model has a price entry (there's a test enforcing this).

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AI subsystem

Architecture

Provider abstraction

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