Recent content by clara581

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    Understanding AI Troubleshooting: data quality and prompt design

    A useful way to understand AI Troubleshooting is to separate the goal, the input, the model or tool, and the way the output is evaluated. 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 tell...
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    A practical overview of AI Front-End Development for common mistakes

    When working with AI Front-End Development, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is common mistakes. Define what a good result looks like before changing tools or settings, then test one variable...