In this post:
- The office-supply “Easy” button chirps “that was easy.” A website prompt promises the same thing, and delivers on it about as reliably.
- An independent review of AI-generated websites found the same defects over and over, missing alt text and broken heading structure chief among them.
- A missing alt tag doesn’t inconvenience a screen reader user. It excludes them entirely.
- You can’t catch what went wrong in a process you never understood in the first place.
- Research shows prompt performance is inconsistent even on the same model. More tries doesn’t mean more reliability.
The Easy Button
There’s a novelty item that’s been sitting on office supply store shelves for years, a big red button labeled “EASY.” Press it, and it chirps back, “That was easy.” It’s a joke. It’s also completely accurate. Most people want the easy button. We want the shortcut that skips the complicated part and still gets us the result.
AI website builders are the new version of that button. Type a sentence, wait a few minutes, and a website appears like you ordered it from a vending machine. It’s genuinely impressive as a piece of technology, and it’s easy to see why it’s tempting for a small business trying to get online fast and cheap.
Why It’s a Coin Flip
The easy button skips right past one detail. Looking finished and being finished are two different things, and the crater between them is invisible to whoever just built the site.
One independent review of AI-generated websites ran a hundred of them through a technical audit. The pattern showed up again and again, and it would almost be funny if it weren’t the whole website. Images missing alt text, headings jumping from H1 to H4, favicons nobody swapped out, mobile layouts nobody had tested on an actual phone, the same handful of mistakes on site after site.
Alt text is the clearest example of why this matters. A missing alt tag doesn’t make a site harder to use for someone relying on a screen reader. It makes that part of the site not exist for them at all. That’s the real coin flip, whether what you get holds up or fails the people and systems relying on it, and you don’t find out which side you landed on until it costs you something.
You Can’t Automate What You Don’t Understand
The issue isn’t automation or AI tools themselves. Is there real expertise underneath the process? Who is accountable when something breaks?
Those two things go together. A useful rule from writing about business automation more broadly is to only automate what you already understand well enough to do it yourself. If you can’t explain how a process is supposed to work, you can’t tell when an automated version of it has gone wrong. That’s exactly the position a business owner could be in when they press the easy button without a background in how websites are supposed to work. There’s no way to catch the parts that didn’t come out right, because there was never a way to know what “right” looked like in the first place.
Automated systems don’t stay finished. Every system that looks like it’s running on its own is really just something that works for now, until a plugin update breaks a layout or a search algorithm stops rewarding whatever the tool defaulted to. Every automated system needs attention eventually, that part’s guaranteed. What matters is whether anyone notices in time and knows how to fix it when they do.
The Real Easy Button
Part of what makes the easy button appealing is the promise that you can skip the whole complicated process. That promise has a weak spot, and it’s a big one. Prompting isn’t a skill that reliably improves with more attempts. Research on large language models has found that prompt performance is inconsistent even within the same model, so there’s no such thing as a prompt you can eventually land on that guarantees a good result. More tries doesn’t convert into more reliability. Sometimes it’s just more time spent hoping.
So “easy” needs a better definition. Real ease looks like a guarantee, a result you can count on, with someone accountable if it doesn’t stick. Buying a service and hoping it delivers the outcome you wanted is the opposite of easy, even when the first step feels effortless.
None of this makes automation the villain. Plenty of good work gets built with AI in the loop. What you’re paying for is a person who knows what “done” is supposed to look like, and who’s still answering the phone when the easy button’s work quietly comes apart six months later.
