The Reviewer Is Also Using AI: What Automation Does to Judgment and Junior Engineers
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Every team relies on a two-person safety net where the author writes the change and an independent reviewer checks it. But if the author generated it with AI and the reviewer is checking it with AI, the net you're counting on is often one model quietly agreeing with itself. The approval is real, but the independent second judgment behind it has thinned to almost nothing, and nobody decided that on purpose.
For a lead, the cost isn't only that defects slip through. It's that review used to be where junior engineers built judgment by reading someone else's code, arguing about it, and learning what good looks like. When both sides automate, that teaching disappears silently, and you don't notice until someone can't reason about a change the AI can't help with.
This talk is about what review was actually for, how automation erodes each part, the warning signs, and what a lead does about it.
Neeraj is the co-founder & CTO of Lyntcube, a real estate AI platform & Vivid Climate, a climate management and DMRV platform. Over the years, he has worked on a variety of full-stack software and data-science applications, as well as computational arts, and likes the challenge of creating new tools and applications, and is an active speaker with talks and tutorials presented at multiple conferences.
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