Most People Using AI to Build Software Are Doing It Wrong

“I tried using AI to build my app and it just made a mess.”

I’ve heard some version of that sentence a dozen times in the last few months, always from smart people, always after a real attempt. And every time, the same root cause shows up once I ask a few questions.

They asked the AI to build something without telling it what “done” looks like.

The one-shot trap

The typical failure pattern goes like this: open a chat window, type a paragraph describing an app, hit enter, get back three hundred lines of code, paste it somewhere, and hope. When it breaks, which it usually does, they paste the error back in and get another three hundred lines, often disconnected from the first batch.

That’s not a workflow. That’s a slot machine.

AI tools are extremely good at execution and mediocre at inferring intent. Ask for “a landing page for my business” and you’ll get a landing page. You won’t get the landing page you had in your head, because you never described that one. The tool built the average of every landing page it’s ever seen, filtered through a vague prompt.

What actually works

The people getting real results treat AI like a contractor they’re managing well, not an oracle they’re interrogating.

That means:

• Writing down the actual requirements before opening the tool. What pages, what functionality, what the finished thing needs to do.
• Breaking the build into pieces small enough to verify one at a time, instead of one giant request.
• Reviewing what comes back instead of assuming it’s correct because it looks plausible.
• Iterating against a plan, not against vibes.

None of that is exotic. It’s the same discipline that makes any project work, whether AI is involved or not. The tools just make the cost of skipping that discipline more visible, because now you can generate a wrong answer in ten seconds instead of two days.

AI didn’t lower the bar for what good software requires. It lowered the cost of finding out you skipped a step.

The businesses getting this right

The clients I work with who see the fastest results aren’t the ones with the most AI tools installed. They’re the ones willing to spend an hour on a spec before touching a keyboard. That hour is the difference between software that works and software that looks like it works until someone actually uses it.

If you’ve tried building something with AI and it didn’t go the way you hoped, the tool probably wasn’t the problem. Happy to walk through what a real spec-driven build looks like on a call.