You're jumping to conclusions not supported by the comment at all.
Also, the comment has two parts: One about writing code, and one about integrating models in workflows.
To the latter, the point is that for a whole lot of uses you can trivially ensure the failure modes are safe.
E.g. I am integrating gpt with my email. "Mostly ok most of the time" applies to things like e.g. summaries and prioritisation, because worst case I just get to an email a bit later. "Sufficient checks" applies to things like writing proposed replies: There's no way I'd send one without reading it, and it's sufficient for me to read through it before pressing send (and making adjustments as needed). Failures here would matter if I intended to make a product of it, but as a productivity tool for myself it just needs to be close enough.
There are a whole lot of possibilities like that.
But even for coding related tasks there are a whole lot of low risk tasks,such as e.g. generating HTML or CSS, or provide usage examples, or providing a scaffold for something you know well how to do but which are time consuming.
If you're trying to make it do things that'd be time consuming to verify sufficiently well, then that's a bad use. The good uses are those where errors are low impact and easy to catch.
> You’re jumping to conclusions not supported by the comment at all.
That might be true, but you’re making assumptions that your first comment is clear and being interpreted the way you intended. I think it’s fair to point out that your words may imply things you weren’t considering, that asking people to re-read the same words again might not solve the problem you had.
The bigger picture here is that you’re talking about using AI to write code that for whatever reason you couldn’t write yourself in the same amount of time. The very topic here also implicitly suggests you’re starting with code you might not fully understand, which is fine, there’s no reason to get upset because someone else disagreed or read your comment that way.