Recent content by craftowen

A practical understanding of AI Robots starts with knowing what the system does well, where it is unreliable, and how to validate the result. One important area is data quality. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can...

The point about approach and evaluation 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 way you can improve the workflow without losing track of what caused the improvement.

When working with Meta AI, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. 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...