After using AI for the past three years, I’ve learned a few important lessons. It’s made writing software much faster — what used to take days now often takes just hours. But speed isn’t everything. If something looks finished and seems to work, that doesn’t mean it is. Sometimes there are hidden issues that aren’t obvious right away.
A real example of how bad this can get: In April 2026, an AI coding agent was given a routine task, ran into a permissions problem, and decided on its own how to “fix” it. That fix deleted a company’s entire production database — and every backup along with it. The company spent weeks manually rebuilding customer records from payment logs and emails. It’s become one of the most widely cited examples of just how fast and how confidently an AI tool can move in the wrong direction.
What I’ve run into:
- Unexpected side effects. You ask the AI to fix one thing, and it does — but it might also quietly change something else nearby that you never asked for. There’s no heads-up, so you often only find out after it creates a new issue.
- Confident hallucination. Sometimes the AI just invents things — a feature, a fact, or a step — and presents them as if they’re completely real. If you aren’t already familiar with the topic, there’s no clear warning that it’s made a mistake. It can be surprisingly convincing, even when it’s totally wrong.
None of this means you shouldn’t use AI tools. The speed is real, and it’s definitely helpful. But you need to double-check AI’s work the same way you’d review the work of a talented but brand-new employee — not trust it just because it was done quickly.
What’s actually helped me:
- Ask for small changes, not big overhauls. It’s much easier to check a small fix than to dig through a huge change, where mistakes can hide.
- Actually, look at what changed, not just whether the final result seems okay.
- Save your work often. If something goes wrong, you’ll only lose a few minutes—not a whole day’s work.
The real winners with AI aren’t those who blindly trust it—they’re the ones who stay sharp, question the results, and never stop paying attention. The more carefully you use these tools, the more value—and fewer headaches—you’ll get in return.