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Self-Optimizing Agents
Agents that generate, test, compare, and promote variants under measurable constraints instead of relying on intuition.
How optimization works
The system proposes workflow variants, runs them against eval datasets, compares trace-level behavior, and promotes only the candidates that improve without breaking quality gates.
What can change
Optimization can target model routing, prompt policy, retrieval shape, tool budget, memory scope, node count, and generated code.