How do you manage quality when AI write code faster than humans can review it?

3 points by lostsoul8282 ↗ HN
We are shifting to an agentic workflow. My thesis is "Code at Inference Speed." My CTO's counter-argument is that reviewing code is harder than writing it.

His concern is simple: If AI increases code volume by 10x, human review becomes a fatal bottleneck. He predicts technical debt will explode because humans can’t mentally verify that much logic that quickly. My concern is as competitors,clients, etc are able to release code quickly then we need to be faster on our product - clients expectations are increasing.

How do handle this? I know one option is to slow down releases but is there any other approaches people are taking.

4 comments

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You stop using AI.
Your CTO is right, reviewing code is harder than writing it. Any experienced programmer will confirm that.

If the human is the bottleneck the logical step is to use a different AI to review the code produced by the original AI. You can even use two different AIs to review the code generated by the first one and accept the code if both agree it does not have bugs. I doubt this will guarantee a high quality product, but it is the solution to doing all your code with AI.

The prudent choice would be to push any generated code to production only after it was tested and reviewed by an experienced human programmer.

As an employee and engineer, it is still your job to produce and validate working code. AI makes its easier, faster, but that still doesn't absolve you of the responsibility. At the end of the day, humans are responsible for what ships. If your code breaks the product because AI went nutz and inserted a Guacamole recipe in a library, then that's on us for not catching it.

I work at a security focused company, top in the entire industry, and blaming AI is not allowed. We use AI, even integrated inside our product, but we aren't ignorant. AI can and will write bad and broken code.

There was a thread on LinkedIn recently about this, and basically I think the answer is platform engineering. More testing, more guardrails in production, experiments instead of manual reviews of code.

Stop caring what the code looks like, and start caring about what the code does.