Episode
DOP 355: Why AI Coding Slows Down Code Review
- Podcast
- DevOps Paradox
- Published
- Jun 17, 2026
- Duration seconds
- 3350
- Processing state
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Summary
#355: Picture your engineering team a year from now. A coding agent doing the coding. A testing agent on tests. A security agent on security. An infrastructure agent on infrastructure. All of them wired into GitHub and Jira, all of them working right alongside the humans. Not science fiction either - Atlassian and GitHub are already shipping these features. So out come the stats everyone loves to quote. AI code introduces 1.7 times more issues. Half of it ships with security holes. Code duplication is through the roof. AI-assisted PRs take four to five times longer to review. The response to most of it: so what? If you have a way to detect the issue and feed it back, that is just the SDLC doing its job. Couldn't care less if it is 1.7x or 50x more issues - what matters is what is left at the end, per feature shipped. Security holes? You have scanners. Detect, fix, ship. The only real problem is when you skip the detection or sit on the fix for months, and that has nothing to do with AI. Here is the one stat that actually sticks: PR reviews backing up. Speed up coding and leave everything downstream at human speed, and you have not sped up delivery - you have just moved the pile from Jira tickets to pull requests. The review pipeline was built for human speed, and now it is the bottleneck. The blunt fix: stop letting AI write 10,000-line PRs, work in smaller chunks, and accept that the job is about to get mentally harder. Delegate the tedious work and what is left is the demanding work - architecture, taste, is this even the feature we should ship. The silly stuff, does every function have a comment, is it camel case, goes to the machine. Spend your time there and you are wasting your talent. Offshoring never worked when the only goal was cheaper - chase the cheapest en…