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Also...I think the biggest problem with writing code, you can rarely, if ever, define the requirements to be specific enough. It’s great for some educational boilerplate to code (e.g. write me a based client/server socket comms code in C) but for anything more complex, requirements are usually so poor, even for humans, that to expect it to write anything large or of real substance is asking too much.

Sounds about right. Just like offshoring code (ugh), you have to be very precise in writing requirements (prompts). Humans (other than offshored coders) have the advantage of subject matter expertise and intuitive thinking. Ok, some humans, not all. lol.

This Q(uantum)GPT is a coder-in-your-pocket, and the freakout is over the disruption.

GPT-4 itself is capable of elucidating/extracting more valid code than I ever thought possible; and yet Sam gave an interview nearly a year ago where he was already talking about GPT-6; and reading between the lines, the takeaway was (and is now ever moreso):

AGI-positive is happening in this decade, not 2032.
The first labor group to be seriously detrimentally-impacted, unironically, is probably coders, or at least 'junior devs' as even a thing, along with all marginal overseas outsourced rent-a-coders.
If you thread the commonality between a BA and a Dev, it was always logic, and since AI is exquisitely logic-based, Q(uantum)GPT blurs those lines by offering both a pathway to the desired outcome, based on their ability to precisely extract it querying Q(uantum)GPT, and hopefully recognize any hallucinations before committing it and passing it along to QA. Agile looks a lot different once the next GPT hits the fAIn.
In this scenario, a BA or PM who migrated from Dev and can wrap their head around AI queries to satisfy Business demands, will now drive Agile, until one B2B emerges to own the field on simplified front-end AI querying.