It remembers every wound
Every correction ECHO receives becomes a Scar — a typed, weighted memory object that lives in the Scar Lattice. Unlike RAG or fine-tuning, Scars form instantly, cost no compute, and grow stronger every time they fire.
The fingerprint is a 128-dim semantic vector computed in pure Rust — no ML model, just math. Similarity search across 10,000 Scars completes in microseconds via Rayon parallel scan.
Risk score = Scar volume + average weight + confidence at mistake. High risk domains get automatic confidence suppression.
Raw query enters ECHO. Before a single token is generated, the Scar system intercepts.
128-dim fingerprint computed in Rust. Cosine similarity scan across all active Scars via Rayon. Top-k matches retrieved in microseconds.
If matching Scars found — a caution prompt is prepended: what was wrong before, what the correction was. Confidence suppressed up to 30% in risky domains.
Full inference via candle. The base model generates with scar context already in its window — no architecture change needed, just smarter input.
POST /v1/echo/correct. Scar crystallizes instantly. Duplicate check — if a similar Scar exists, its weight increases instead of creating a duplicate. Saved to disk atomically.