Maybe but I’d argue the frontier corps will self destruct via green annd product management enough to make this impractical. So far here’s how I see that going 1) can’t easily autopilot due to security. Ganna keep on prompting you into running weird shell commands 2) it’ll launch your code on weird Anthropic or ChatGPT sites behind a paywall 3) between the two of them it’ll Misalign the solution so it’s unusable

I'm noticing AI catching many bugs in code that previously went unnoticed. Some of them are important, and it's great to catch them early.

The other 11 items in the list of 12 would probably never be hit in practice, but now that you know, you have to sort out how to handle each (even if that just means documenting, filing, or ignoring: you have to understand each of the disparate 12 issues first.)

Maybe for some orgs, I know theres orgs out there where there is no such review only QA and unit testing.

This is from March 2026, but it does match what I've encountered professionally. Code review was always a significant bottleneck and is even more so with agentic coding. We've had discussions about leaning more on automated review, but it hasn't translated into any practical improvements so far. I think senior engineers find it very difficult to give up on line-by-line review, no matter how much better the agents have gotten.

I think if there is a major change in code review culture, it's not going to happen first in established engineering teams. It'll happen in startups that adopt a no-human-review policy from jump and then maintain it as they mature. I'm sure that's happening, but it's likely invisible to most studies and surveys at the moment. If it proves successful, and such companies start shipping significantly faster, the rest of the industry will be forced to adopt.

Wrong thing to index on. Always bet on the slope, not on points in the slope. Things will only get better and better and factor in that downward slope thought while taking actions and pick ones that are favorable. The folks who focus on a point in time will be left behind, period.

As is standard for academic papers, this is an attempt to describe the state of the world as of when they did the research. But then it takes time to write it up and get it out, after which newspapers report it as current events.

In this case, we're looking at a picture from 2025. The models involved in the main agent results were primarily Claude 3.5 through Sonnet 4.5, GPT-4.1 through GPT-5, and Gemini 2.5. And the paper's design means you're mostly looking at the very initial effects of deployment, before companies developed good review processes.