Basically all of my actual programming work has been done by LLMs since January. My team actually demoed a PoC last week to hook up Codex to our Slack channel to become our first level on-call, and in the case of a defect (e.g. a pagerduty alert, or a question that suggests something is broken), go debug, push a fix for review, and suggest any mitigations. Prior to that, I basically pushed for my team to do the same with copy/paste to a prompt so we could iterate on building its debugging skills.
People might still code by hand as a hobby, but I'd be surprised if nearly all professional coding isn't being done by LLMs within the next year or two. It's clear that doing it by hand would mostly be because you enjoy the process. I expect people that are more focused on the output will adopt LLMs for hobby work as well.
Using an LLM as first-level on-call is a fascinating application because on-call is exactly the kind of work where "good enough fast" beats "perfect slow." If the agent can triage correctly 70% of the time and route the hard stuff to humans, that's already a massive win. The question is what happens when it confidently misdiagnoses something at 3am and the human responder trusts the triage. That's where the failure mode gets expensive.
That's sounds like the perfect recipe for turning a small problem into a much larger one. 'on call' is where you want your quality people, not your silicon slop generator.
> It's clear that doing it by hand would mostly be because you enjoy the process.
This is gaslighting. We're only a few years into coding agents being a thing. Look at the history of human innovation and tell me that I'm unreasonable for suspecting that there is an iceberg worth of unmitigated externalities lurking beneath the surface that haven't yet been brought to light. In time they might. Like PFAS, ozone holes, global warming.