Self-improving skills for any coding agent
Team-wide memory pool for agents when most tools stay siloed on one workstation.

Targeted correction loop updates retrieval instantly, unlike standard vector DBs.
AI engineers and enterprise teams building RAG applications
LangSmith · Arize Phoenix · LlamaIndex
Team-wide memory pool for agents when most tools stay siloed on one workstation.
40 cognitive engines with LLM as one component, not the substrate.
Tops LongMemEval and LoCoMo benchmarks with local-first AI memory architecture.
Claude agent that learns from mistakes via structured signal tracing—interesting approach, unclear real-world ROI.
Turns repeated agent corrections into AGENTS.md updates before you forget them.
Deterministic folding beats LLM summarization with 92% cache hits and zero extra model calls.