I wanted to start a broader productivity ideas thread around Datasets.
A useful angle is common mistakes, but it also connects with quality versus speed. 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 Datasets is genuinely useful and where it still needs improvement.
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A useful angle is common mistakes, but it also connects with quality versus speed. 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 Datasets is genuinely useful and where it still needs improvement.
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