Why Claude and Codex keep over-engineering your code
Peter Verhas noticed something while pairing with Claude and Codex on architecture decisions: both assistants consistently propose designs that go further than the problem requires. More general. More extensible. More “future-proof.”
That last word is the tell. The models have no visibility into what your software will actually need next month. They’re applying a familiar engineering heuristic: anticipate change, keep components reusable, leave room to extend. Classic advice. Wrong default for a lot of real situations.
The YAGNI problem with AI assistants
YAGNI, You Aren’t Gonna Need It, is the principle that you should not build features or abstractions until you actually need them. AI coding assistants seem to have absorbed the opposite instinct from their training data, defaulting toward the more elaborate design even when the simple one would do.
The result is code you didn’t ask for, covering cases you may never encounter, adding maintenance surface you now have to own.
The operator takeaway
If you’re using Claude or Codex for architecture conversations, treat their first proposal as a starting point, not a blueprint. Push back explicitly: ask for the simplest design that handles what you have today. The models can generate that version too, but they won’t lead with it.
I’m founder of BizStack at Cagri Sarigoz LLC and a passionate advocate for entrepreneurs.
With over 14 years in tech, marketing, and AI, including my role as Head of SEO at CitizenShipper and co-founder of TaleBot at Intale AI, I’m dedicated to sharing genuine, useful product insights and tips.
At BizStack, I aim to cut through the digital noise to provide clear, actionable advice.
And more than all else, I’m a father to a (always) little girl and a husband.
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