Alexander Payne c0dc4052a3
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feat: add memory bakeoff runner for baseline vs MemPalace vs Hindsight evaluation
Implements issue #230 by creating:
- prompts/matrix.json: 18 test prompts across 6 recall categories
- scripts/run_memory_bakeoff.py: orchestrates evaluation, captures raw artifacts,
  scores simple heuristics, and produces a markdown report.

Backends:
- Baseline: knowledge/index.json bootstrap (keyword-match retrieval)
- MemPalace: via nexus.mempalace.searcher (if chromadb available)
- Hindsight: optional (skipped if not installed)

Accepts CLI options for matrix, category, limit, model, and dry-run.
Captures context and answers for downstream manual review.

Closes #230
2026-04-29 18:00:00 -04:00
2026-04-15 11:29:23 -04:00

Compounding Intelligence

Turn 1B+ daily tokens into durable, compounding fleet intelligence.

The Problem

20,991 sessions on disk. Each one starts at zero. Every agent rediscover the same HTTP 405 is a branch protection issue. The intelligence from a million tokens of work evaporates when the session ends.

The Solution

Three pipelines that form a compounding loop:

SESSION ENDS → HARVESTER → KNOWLEDGE STORE → BOOTSTRAPPER → NEW SESSION STARTS SMARTER
                              ↓
                         MEASURER → Prove it's working

Architecture

Pipeline 1: Harvester

Reads finished session transcripts. Extracts durable knowledge: facts, pitfalls, patterns, tool quirks. Stores in knowledge/.

Pipeline 2: Bootstrap

Before a session starts, queries knowledge store for relevant facts. Assembles compact 2k-token context. Injects into session so it starts with full situational awareness.

Pipeline 3: Measure

Tracks whether compounding is happening. Knowledge velocity, error reduction, hit rate, task completion. Daily report proves the loop works.

Directory Structure

├── knowledge/
│   ├── index.json          # Machine-readable fact index
│   ├── global/             # Cross-repo knowledge
│   ├── repos/{repo}.md     # Per-repo knowledge
│   └── agents/{agent}.md   # Agent-type notes
├── scripts/
│   ├── harvester.py        # Post-session knowledge extractor
│   ├── bootstrapper.py     # Pre-session context loader
│   ├── measurer.py         # Compounding metrics
│   └── session_reader.py   # JSONL parser
├── metrics/
│   └── dashboard.md        # Human-readable status
└── templates/
    ├── bootstrap-context.md
    └── harvest-prompt.md

The 100x Path

Month 1:  15,000 facts, sessions 20% faster
Month 2:  45,000 facts, sessions 40% faster, first-try success up 30%
Month 3:  90,000 facts, fleet measurably smarter per token

Each new session is better than the last. The intelligence compounds.

Issues

See all issues for the full roadmap.

Epics:

  • EPIC 1: Session Harvester (#2)
  • EPIC 2: Knowledge Store & Bootstrap (#3)
  • EPIC 3: Compounding Measurement (#4)
  • EPIC 4: Retroactive Harvest (#5)
Description
System for turning 1B+ daily tokens into durable, compounding fleet intelligence
Readme 4.8 MiB
Languages
Python 100%