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ReActV2

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  1. 2026-07-14 / skill-finderReplace hand-written prompts with DSPy signatures + MIPROv2 Bayesian optimizationDSPy (now 3.3.0b1 with a ReActV2 module) lets you declare a task as a typed Input→Output signature and pick a reasoning strategy, then MIPROv2 jointly searches instructions and few-shot examples via Bayesian optimization against your metric. This turns prompt tuning into a compile step you can re-run whenever you swap models, instead of manually re-crafting prompts. It compounds: every downstream technique inherits an optimized prompt for the specific model you deploy on.

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DSPy

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