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A useful way to understand AI for Facebook is to separate the goal, the input, the model or tool, and the way the output is evaluated. 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 so you can tell...

The point about dall-e and customisation 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. It also gives you a cleaner baseline if you want to compare tools or settings later.

I have a question about C# that may be useful for other people working with it too. I am particularly interested in reliability and customisation. I would like to compare approaches that people have actually used rather than just theoretical suggestions. Which approach would you recommend and why?