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Continually improving our agent harness · Cursor

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Models need a harness to become fully useful, and improving that harness means continuously iterating on context, evaluation, and model-specific tuning.

We approach building the Cursor agent harness the way we'd approach any ambitious software product. Much of the work is vision-driven, where we start with an opinion about what the ideal agent experience should look like. From there, we form hypotheses about how to get closer to that vision, run experiments to test them, and iterate using quantitative and qualitative signals from evals and real usage. That process depends on having the right online and offline instrumentation, so we can tell when a change actually makes the harness better. When we get early access to new models, all of…

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