Meta-Harness: Scaling LLM Agent Self-Optimization via Raw Execution Traces

Meta-Harness shifts the optimization paradigm from summary statistics to massive context windows of raw execution traces, allowing agents to identify and fix failure modes with surgical precision. By leveraging Islo.dev's efficient sandboxing primitives, developers can now build self-improving agent loops that drastically reduce manual prompt engineering.