lakehouse

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rootandClaude Opus 4.6 2189a6dbee Multi-pass deep analysis workflow: dynamic knowledge discovery

5-pass analysis over extracted knowledge:
1. Corpus overview: LLM characterizes what the data is about
2. Cross-conversation patterns: recurring themes found via SQL + semantic search
3. Decision evolution: contradictions, progressive refinement, consistent principles
4. Gap analysis: recovered knowledge (questions answered elsewhere),
   real gaps (unresolved), blind spots (never discussed)
5. Synthesis: actionable recommendations based on patterns

Demonstrates: SQL (DataFusion) + Vector Search (HNSW) + Local LLM (qwen2.5)
working together for structured analytical workflow.
All local, no data leaves the machine.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-03-27 23:12:13 -05:00

apps/observer-kb

Observer KB: full knowledge base interface

2026-03-27 22:57:19 -05:00

crates

Observer KB: 477 pages from 8 ChatGPT PDFs indexed and searchable

2026-03-27 22:53:27 -05:00

data

Metacognitive knowledge extraction: 496 topics, 300 decisions, 100 insights

2026-03-27 23:06:36 -05:00

docs

Sync memory + phases: all 15 phases marked complete