I wanted to start a broader productivity ideas thread around AI Level Generation.
A useful angle is customisation, but it also connects with evaluation. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Level Generation is genuinely useful and where it still needs improvement.
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A useful angle is customisation, but it also connects with evaluation. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where AI Level Generation is genuinely useful and where it still needs improvement.
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