What are you actually evaluating these days: prompts, context, or the whole harness?

Reddit r/AI_Agents News

Summary

A discussion about the focus of AI evaluations, questioning whether practitioners are optimizing prompts, context, or the entire harness, and noting a shift toward holistic optimization.

Asking to the ones who care about evals. What's the main thing you're trying to evaluate and optimize right now? Prompts? Context? The harness itself? Most people I talk to still point evals at individual prompts. But my read is that the frontier has moved: the interesting work now is closing the loop and optimizing the entire context and/or harness, not tuning prompts in isolation. Anyone already doing this in practice? Curious what your setup looks like and where it breaks down.
Original Article

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