Jason Woltje
36095ad80f
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Co-authored-by: Jason Woltje <jason@diversecanvas.com> Co-committed-by: Jason Woltje <jason@diversecanvas.com>
61 lines
3.3 KiB
Markdown
61 lines
3.3 KiB
Markdown
# Mission Scratchpad — Harness Foundation
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> Append-only log. NEVER delete entries. NEVER overwrite sections.
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> This is the orchestrator's working memory across sessions.
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## Original Mission Prompt
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```
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Jason wants to get the gateway and TUI working as a real daily-driver harness.
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The system needs: multi-provider LLM access, task-aware agent routing, conversation persistence,
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security isolation, session hardening, job queue foundation, and channel protocol design for
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future Matrix/remote integration.
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Provider decisions: Anthropic (Sonnet 4.6, Opus 4.6), OpenAI (Codex gpt-5.4), Z.ai (GLM-5),
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OpenRouter, Ollama. Embeddings via Ollama local models.
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Pi SDK stays as agent runtime. Build with Matrix integration in mind but foundation first.
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Agent routing per task with granular specification is required.
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```
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## Planning Decisions
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### 2026-03-21 — Phase 9 PRD and mission setup
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- PRD created as `docs/PRD-Harness_Foundation.md` with canonical Mosaic template format
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- 7 milestones, 71 tasks total
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- Milestone order: M1 (persistence) → M2 (security) → M3 (providers) → M4 (routing) → M5 (sessions) → M6 (jobs) → M7 (channel design)
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- M1 and M2 are hard prerequisites — no provider or routing work until conversations persist and data is user-scoped
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- Pi SDK kept as agent runtime; providers plug in via adapter pattern underneath
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- Embeddings migrated from OpenAI to Ollama local (nomic-embed-text or mxbai-embed-large)
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- BullMQ chosen for job queue (Valkey-compatible, TypeScript-native)
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- Channel protocol is design-only in this phase; Matrix implementation deferred to Phase 10
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- Models confirmed: Claude Sonnet 4.6, Opus 4.6, Haiku 4.5, Codex gpt-5.4, GLM-5, Ollama locals
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- Routing engine: rule-based classification first, LLM-assisted later
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- Default routing: coding-complex→Opus, coding-moderate→Sonnet, coding-simple→Codex, research→Codex, summarization→GLM-5, conversation→Sonnet, cheap/general→Haiku, offline→Ollama
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### Architecture decisions
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- Provider adapter pattern: each provider implements IProviderAdapter, registered in Pi SDK's provider registry
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- Routing flow: classify message → match rules by priority → check provider health → fallback chain → dispatch
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- Context window management: summarize older messages when history exceeds 80% of model context
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- OAuth pattern: URL-display + clipboard + Valkey poll token (same as P8-012 design)
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- Embedding dimension: migration from 1536 (OpenAI) to 768/1024 (Ollama) — may require re-embedding existing insights
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## Session Log
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| Session | Date | Milestone | Tasks Done | Outcome |
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| ------- | ---------- | --------- | -------------------------------- | ---------------------------------------------- |
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| 1 | 2026-03-21 | Planning | PRD, manifest, tasks, scratchpad | Mission initialized, planning gate in progress |
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## Open Questions
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1. Z.ai GLM-5 API format — OpenAI-compatible or custom? (Research in M3-005)
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2. Which Ollama embedding model: nomic-embed-text (768-dim) vs mxbai-embed-large (1024-dim)? (Test in M3-009)
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3. Provider credentials: env vars for system defaults + DB for per-user overrides? (ASSUMPTION: hybrid)
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4. Pi SDK provider adapter support — needs verification in M3-001 before committing to adapter pattern
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## Corrections
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<!-- Record any corrections to earlier decisions or assumptions. -->
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