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LLM agents can now autonomously generate complex skills with multi-file dependencies, rivaling human-authored skills, thanks to a co-evolutionary verification process that doesn't need ground truth labels.
LLMs can now remember the past without forgetting the details: an indexed memory system lets agents selectively retrieve full-fidelity interactions from an external database, outperforming lossy summarization methods on long-horizon tasks.