I wanted to start a broader productivity ideas thread around Kling AI.
A useful angle is privacy considerations, but it also connects with learning curve. 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 Kling AI is genuinely useful and where it still needs improvement.
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A useful angle is privacy considerations, but it also connects with learning curve. 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 Kling AI is genuinely useful and where it still needs improvement.
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