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When your AI system breaks—and what to do about it

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When your AI system breaks—and what to do about it

The announcement of a new AI model or feature fills me with a mixture of anticipation and dread. I’m excited to see what “new thing” I might be able to do, but I also know that some of my existing processes and systems might break as a result.

Every AI tool comes with the disclaimer that it can make mistakes. You might set up a workflow that is perfectly fine one day and perfectly awful the next. 

It’s an ongoing challenge. Unlike traditional software, once an AI system is up and running, it’s not set-it-and-forget-it. Even a system that seems to be working fine needs an occasional check-in or fine-tuning.

AI can stop working in some very predictable ways. Maybe it’s connected to an external tool (like your email), and the connection expired. Some AI tools require your computer to be on/awake for tasks to run. You might get an error message, or the output never shows up. 

These failures are easy to address because it’s often clear what went awry. You reconnect and try again. 

I rely heavily on AI scheduled tasks and have a notification system built in. If something breaks, I get an email telling me to review the process. That way, I realize immediately that something went wrong and can fix it. 

The harder failure is when an AI process runs as expected, but the output gets worse. Models and functionality change almost daily. You may have a well-crafted prompt that gave you what you were looking for last month, but the results are noticeably different today.


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