Announcement
Self-Direction turns AI agent mistakes into reusable skills
The researchers say its small LoRA adapters store procedural lessons while the base model stays frozen.
TLDR
Self-Direction’s researchers describe a method that reflects on failed tasks, trains small LoRA adapters from corrective examples and stores them for use on related tasks. Across 185 prior mistakes in their tests, the share solved in all three encounters rose from 9.7% with base retrying to 18.9% with Self-Direction.
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