I’ve seen some impressive AI workflows that seem flawless at first glance. They respond to WhatsApp messages, answer voice calls, and even embed PDFs. But let’s be real – these demos often hide the fact that they’re not robust systems, but rather experiments waiting to break.
As someone who’s worked with automation, I’ve learned to ask the tough questions to test any workflow. Here are some of the key ones:
* What happens when an external call fails? Is there a retry mechanism in place, or does it just fail silently?
* How does the system handle user input that doesn’t make sense? Does it stop or try to move on?
* Do you have control over the limits of the API you’re using? What happens when you hit the speed limit?
* Can your workflow run twice in a row without conflicts? Are you prepared for the consequences?
* How much traceability do you have? Can you easily find out why something failed without digging through logs manually?
It’s easy to get caught up in the hype of AI demos, but we need to be honest with ourselves – automation without error handling, status checking, or logging is not production-ready. It’s a proof of concept with good aesthetics, but not much else.
If you’re building something serious, test it thoroughly. If you’re going to share it, explain it thoroughly. No smoke and mirrors, no magic. Step by step, including what breaks and what doesn’t.
That’s the kind of content that really helps. And that’s why I’ve created a community on Discord where we can talk about mistakes and not fake demos. No hype, just real conversations about what works and what doesn’t.