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When working with Machine Learning, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is cost control. Define what a good result looks like before changing tools or settings, then test one variable at a time...

I wanted to start a broader future possibilities thread around PHP. A useful angle is deployment, but it also connects with automation. Different tools and workflows can produce very different results even when the goal is similar. It would be interesting to compare practical examples...