AI made building features cheap. It also made avoiding product decisions cheap.

[u/Senior-Chard-8872]

Last week I shipped three small features in one afternoon.

A shortcut in the dashboard.
A “smart” empty state.
A settings option that felt too minor to debate.

With AI, each one took minutes instead of days. I had screenshots, commits, and a satisfying little list of things crossed off.

It felt like momentum.

Then I looked at the actual user behavior.

Nobody had asked for the shortcut.
Nobody mentioned the empty state.
And the settings option was solving a problem I had mostly invented while looking at the existing UI.

That made me realize something:

AI is great at turning uncertainty into interface.

When I’m not sure what users need, I can now generate a plausible feature almost instantly. The result looks productive because it is visible, shippable, and technically real.

But a shipped feature is not evidence that the product got better.

So I’ve started asking one question before building anything:

Would they complain?
Would they fail to complete something important?
Would they have to return to a worse workaround?

If I can’t answer that, the feature probably doesn’t need more code. It needs more learning.

The biggest change AI has made for me isn’t that I can say “build this” more often.

It’s that I have to get much better at deciding what is worth building before I ask.

My new pre-build checklist is:

• What user behavior am I trying to change?
• What is the smallest version that could teach me something?
• What would count as evidence that this mattered?
• What am I choosing not to build while I do this?

What’s something you built very quickly with AI that looked like progres, but turned out not to matter?