I wanted to start a broader creative experiments thread around DeepSeek.
A useful angle is data quality, but it also connects with setup choices. 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 DeepSeek is genuinely useful and where it still needs improvement.
A useful angle is data quality, but it also connects with setup choices. 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 DeepSeek is genuinely useful and where it still needs improvement.