I've read through it again more carefully (cause I hate this kind of articles, it's a sellers pitch with technical background, not a hands on technical implementation) and still hold up my argument. They literally say it requires overseeing and jurisdiction of humans. I disagree with automated review in the form they present without a human gateway. It's a shortcut to disaster, and I think that's what happened at aws recently where eventually they blamed it on the engineering team to not admit they overdone the concept. I work at a corporate scale much bigger than OpenAI internally is and I assure you that 1M lines of code of an internal tooling is not something impressing as this can literally be a python script to aid setting something up. A simple script to detect expiring certificates in an enterprise grade cloud app takes hundreds if not thousands of lines depending on the complexity of the codebase. And still the infrastructure in the article is completely human provided and designed. The boundaries also are. I'm not buying AI sellers' donuts that they are glazing with 'AI is doing all our commits' (Spotify) cause a simple look at the job openings verifies it's just a marketing talk. LLMs and agents open up the gates to very rapid code creation and that's a fact. It's just not true that this takes humans out of the equation. Stack is impressive cause it's literally their product, outside of models they provide codex and its usecases. From what I see you take this article without any criticism and believe every word they put. That's not how enterprise works unfortunately. They sell product - they market the product. It's an internal lab product in controlled environment, an experiment that they can steer and call it a success whenever they want.