Self-Evolving Agent Harness for Fixed-Weight Model Scaffolding
October 16, 2026
This framework enables agents to autonomously revise software scaffolding, including prompts, memory, and executable code, while keeping model weights constant. It uses a feedback-driven process with formal generalization and retention bounds to ensure stable evolutionary optimization.
HOW THIS AFFECTS YOU
●
builderYou can use this to build agents that automatically improve their own tools, workflows, and code repositories.
●
researcherThe framework provides formal PAC-learning bounds for evaluating the reliability of self-evolving agent architectures.