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We open-sourced optimize_anything, an API that optimizes any text artifact. You provide a starting artifact (or just describe what you want) and an evaluator and it handles the search. import gepa.optimize_anything as oa result = oa.optimize_anything(
seed_candidate="<your artifact>",
evaluator=evaluate, # returns score + diagnostics
) It extends GEPA (our state of the art prompt optimizer) to code, agent architectures, scheduling policies, and more. Two key ideas:
(1) diagnostic feedback (stack traces, rendered images, profiler output) is a first-class API concept the LLM proposer reads to make targeted fixes, and
(2) Pareto-efficient search across metrics preserves specialized strengths instead of averaging them away. Results across 8 domains show optimize_anything can create:
- learned agent skills pushing Claude Code to near-perfect accuracy simultaneously making it 47% faster,
- cloud scheduling algorithms cutting costs 40%,
- an evolved ARC-AGI agent going from 32.5% → 89.5%,
- CUDA kernels beating baselines,
- circle packing outperforming AlphaEvolve's solution,
- and blackbox solvers matching and outperforming Optuna. |