I wanted to start a broader creative experiments thread around AI Workflows.
A useful angle is reliability, but it also connects with troubleshooting. 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 Workflows is genuinely useful and where it still needs improvement.
A useful angle is reliability, but it also connects with troubleshooting. 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 Workflows is genuinely useful and where it still needs improvement.