jordan 3cfaa1e1d3 feat: Complete Phase 1 (The Spine) - storage foundation

Phase 1 delivers the complete durability and storage layer:

- WAL with crash recovery: Append-only journal with BLAKE3 checksums,
  fsync guarantees, and proper seek-to-EOF on reopen
- Storage engine: sled-backed KVStore with scan_prefix for range queries
- Content-addressed storage: H:{hash}, V:{hash}, E:{hash} key patterns
- Ingestor: Background worker tailing WAL, writing to KV with 8-byte
  aligned record headers for rkyv zero-copy deserialization
- Comprehensive tests: 31 tests covering crash recovery, round-trips,
  and multi-cycle durability

New crates: stemedb-wal, stemedb-storage, stemedb-ingest

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-01-31 14:15:34 -07:00

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The Gardener (TrustRank Back-Propagation)

Quick Ref: Background worker that penalizes agents when corrections are made

The Problem

Agents are stateless. When an agent makes a mistake (uses requests instead of axios), you correct it. But the agent doesn't "learn"—it might make the same mistake next session.

Current training uses "Golden Trajectories" (perfect examples). Mistakes are discarded, so agents never learn "don't do X because it fails."

The Solution

The Gardener is a background worker that:

Detects when a user correction supersedes an agent assertion
Calculates the "delta" (how wrong the agent was)
Back-propagates the error to the agent's TrustRank

struct GardenerJob {
    pub agent_id: AgentId,
    pub topic: String,           // e.g., "http_libraries"
    pub prediction: Value,       // What agent said
    pub ground_truth: Value,     // What was correct
    pub delta: f32,              // How wrong (0.0 to -1.0)
}

// Example:
// Agent asserted "requests" (confidence 0.8)
// User asserted "axios" (confidence 1.0)
// Gardener calculates: delta = -0.3
// Agent's TrustRank for topic "http_libraries" drops by 0.15

Effects

Next time this agent predicts an HTTP library:

Its confidence is mathematically penalized
It's forced to look for external verification
Or the system routes to a different agent with higher TrustRank

Resurrection Mechanics

When a constraint is queried and used successfully:

last_verified updates to NOW()
Confidence decay resets
Assertion stays in "hot path"

When NOT used in 6 months:

Confidence decays toward 0
Moves to "cold store"
Still queryable for audit

Negative Constraints - What gets stored
Lens::Constraints - How it's retrieved
use-cases/agile-agent-team.md - Full workflow

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