In a paper titled “Coding Agents are Strong Prompt Optimizers,” published on September 23, 2026, Microsoft researchers introduce Coding-Agent Skill Distillation, or CASD. The method writes improved system prompts directly from a static pile of saved agent logs, and it does so for approximately $1.60 per pass. That price matters because the competition is not cheap. According to the paper, CASD comes in over 22 times cheaper than validation-gated iterative methods, the trial-and-error approach that has become standard for tuning agent prompts. How CASD works, and how it scored CASD needs no iterative search, no live interaction with the environment, and no held-out validation set. Instead, a coding agent takes in an entire corpus of saved trajectories, which are records of what an agent did on past tasks. It runs a single corpus-wide statistical analysis, pulling out aggregate statistics, recurring failure modes, and representative episodes. From that analysis, it distills behavioral rules and writes them into an optimized prompt. The researchers frame this as reading the whole corpus rather than small minibatches. Iterative optimizers typically look at slices of data at a time, whi...
Microsoft’s coding-agent skill distillation beats GEPA at prompt optimization
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