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When working with AI Testing & Debugging, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is data quality. Define what a good result looks like before changing tools or settings, then test one variable at a...

The point about local and agents is interesting. In practice I would keep the first test simple, record what worked, and only add extra complexity if it solves a specific limitation. That should make it easier to tell whether the change is actually helping.

For Prompt Engineering, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is useful tools. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the...