AI-Assisted Development Is a Taste Problem
Why the bottleneck isn’t the model—it’s knowing what to ask for.
Everyone is talking about AI replacing developers. The conversation is wrong. The bottleneck was never typing speed. It was always taste.
I’ve been shipping with AI-assisted tooling for over a year now. Copilot, v0, Claude, cursor-based workflows—the whole stack. The people who get the most out of these tools aren’t the ones who type the best prompts. They’re the ones who know what good code looks like before the model generates it.
The model doesn’t know your system’s constraints. It doesn’t know your team’s conventions. It doesn’t know that the reason you chose a specific pattern three months ago was because of a performance cliff that only shows up at scale. You do.
Taste is the ability to look at generated output and immediately know: this is wrong, this is close, or this is exactly right. It comes from years of shipping things that break in production, refactoring code that someone else will inherit, and building systems that need to survive contact with real users.
The developers who will thrive aren’t the ones who can out-prompt each other. They’re the ones who can out-think the machine. Who can see the shape of a solution before the code exists. Who can say ‘no, not like that’ and know exactly why.
AI-assisted development amplifies whatever you already are. If you have taste, it makes you faster. If you don’t, it makes you confidently wrong at scale.