What’s the first thing you usually change when an AI project works in the example but not in your version?

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Summary

A discussion prompt asking AI practitioners about common troubleshooting steps when an AI project fails to replicate an example, focusing on typical issues and time-consuming fixes.

You follow the example. Same steps. Same general setup. Everything looks right. And somehow… yours still doesn't work. So what do you check first? Do you go back through what you put in? Change the prompt? Check the data? Start looking at how everything is connected? Or do you end up changing five things at once and then have no idea what actually fixed it? What’s the most common “works perfectly in the example, breaks in my project” problem you’ve run into? Even better if it was something ridiculously small that ended up eating way too much of your time.
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What is one AI task you stopped automating because it caused more work than it saved?

Reddit r/AI_Agents

I think we talk a lot about what AI agents can automate, but not enough about what they should not automate. Sometimes a workflow looks perfect on paper, but once it runs in the real world there are too many exceptions, wrong decisions, or manual fixes. Have you ever automated something and later turned it off because it created more work? What went wrong? I’m more interested in real examples than successful demos.