> 2. That output often looks correct to an untrained eye and requires expert intervention to catch serious mistakes
The thing is this is true of humans too.
I review a lot of human code. I could easily imagine a junior engineer creating CVE-2025-4143. I've seen worse.
Would that bug have happened if I had written the code myself? Not sure, I'd like to think "no", but the point is moot anyway: I would not have personally been the one to write that code by hand. It likely would have gone to someone more junior on the team, and I would have reviewed their code, and I might have forgotten to check for this all the same.
In short, whether it's humans or AI writing the code, it was my job to have reviewed the code carefully, and unfortunately I missed here. That's really entirely on me. (It's particularly frustrating for me as this particular bug was on my list of things to check for and somehow I didn't.)
> 3. The process automates away a task that many people rely on for income
At Cloudflare, at least, we always have 10x more stuff we want to work on then we have engineers to work on it. The number of engineers we can hire is basically dictated by revenue. If each engineer is more productive, though, then we can ship features faster, which hopefully leads to revenue growing faster. Which means we hire more engineers.
I realize this is not going to be true everywhere, but in my particular case, I'm confident saying that my use of AI did not cause any loss of income for human engineers, and likely actually increased it.