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I am trying to improve my approach to Kling AI and could use some practical advice. I am particularly interested in customisation and useful tools. I would like to compare approaches that people have actually used rather than just theoretical suggestions. What would you tell someone trying...

I think setup and choices is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. That way you can improve the workflow without losing track of what caused the improvement.

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