The Hidden Cost of Letting AI Agents Ship Your Code

I started building a platform with AI agents writing most of the code. Two different models. Eleven project phases. Over 1,500 tests. More than 200 features shipped.

Then one morning I opened my own repository and couldn’t trace the execution path through a service I’d supposedly built.

The code was clean. The tests passed. The architecture followed every pattern I’d specified. But when I tried to explain why a particular order validation happened before portfolio sync instead of after, I just… stared at the screen. The logic was there. My understanding wasn’t.

That’s not a horror story. It’s just what happens when you adopt a tool without vetting it the way you’d vet any other dependency in your stack. I started asking different questions — the kind you’d ask before adding something critical to a production system.

Here are four that keep surfacing.

What Changed About the Work — and...

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