Self-Optimizing Agents
Agents that generate, test, compare, and promote variants under measurable constraints instead of relying on intuition.
Production AI is not a prompt. It is a system of context, tools, permissions, traces, evals, and feedback loops.
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.
Related resources
Evaluation suites that mutate prompts, models, retrieval policies, generated code, and node structure before promotion.
A gateway strategy for choosing the right model per task based on privacy, cost, latency, quality, and failure mode.
Trace-level visibility into model calls, retrieval, tools, decisions, approvals, costs, and failures.