Just to make this clear up front: I was always very skeptical of LLMs (I'll never call them AI) and still see them as fundamentally limited and unreliable. See my post history if you don't believe me.
Having said that: I work in business software and the models have progressed to the point where typing code and writing classes and functions by hand has become uneconomical. We review the output closely to avoid the idiocy of "vibe-coding", but the quality has improved to the point where we rarely have to outright reject solutions. The discussions have moved to high-level architectural points, where we just request better implementations than the first-shot. We get them, review again and move on. Maybe there are deeper, latent problems beeing embedded in the code-base through this process, but we can't spot any although we are looking intently.
And just like that, my profession has died. Nobody in my team writes code anymore. Things that would have taken days are now done in minutes. We are all just considering design and architecture. We are changing our processes since they are not fit for the new way of doing things. Scrum? What's even the point anymore? We can work through a sprint-backlog that would've taken two weeks in two days now. We do reviews 90% of the time. When we request changes they come back in minutes.
I have a feeling like the ground has been taken from below me. My son wanted to become a developer, that isn't a real job anymore. Everyone around me feels the same way, including our management. We are a small team and a small company, everyone is effective and our jobs are not in danger as long as our product is succesful. But my profession is essentially dead. It's a craft I honed for many, many years and the craft itself is now automated. I wanted to improve my typing skills to code faster, this is now a ridiculous endeavour. We don't know what comes next, but I now only have my analytical skills and knowledge of good architecture to fall back on.
And it all changed so fast. I don't think this will transfer to other professions so easily, but for programming LLMs ended it all in the span of the last four months. I thought I knew what my future holds as a senior dev, now I can barely see past christmas.This is a nightmare.
I work in embedded systems and until recently I would have agreed with you... But it's getting to the point where our agents have access to debuggers/tracers, system I/O logging and basically every tool we would ordinarily use and it's vastly improving the quality of their work.
I always attributed their better performance in web and general software development to more availability of open source examples that they are trained on, but I think the ability to 'self check' was a huge limiting factor. Unit and other pure software testing abstracted away too much of the real system. With real feedback and access to the data sheets it's doing a pretty good job.
Only four months back I told anyone who asked that LLMs would never replace developers, because back then they really couldn't. The modern models in conjunction with their harnesses are a very different thing.
Similar time frame for me. I just spent a few hours documenting how a tool we already have should work (one that's a freaking overcomplicated mess and impossible to manage) and feed those requirements to Argon. It made it 90% accurate in one shot. 5 % difference was an issue with my specifications and 3% a latent bug on the existing framework nobody had noticed.
Freaking scary
That's scary. My most recent experience was a year ago when a coworker vibecoded a bunch of tests that somehow only tested the emulated hardware and forgot to test production code.
Try it again. In the past few months they are good enough for general enterprise dev that what OP said is the reality. We just watch our robots shit out a working solution to a ticket.
doesn't really help you when any proprietary code crossing the network boundary is a security breach.
This is only a short term problem. More and more models are released that are „good enough“ that can be run on local hardware. Prices for components at the moment are a problem, but that’s a money problem not with the technology itself.
What does "good enough" mean here though? At the moment I highly doubt that we'll get anywhere near the performance of frontier models on hardware accessible to the average user, due to the limitations of physics itself. Then on the model side of things I think there's probably a limit on how small we can go before accuracy becomes a major issue, and I don't think that limit would be something that consumer hardware would be able to run (and by consumer hardware I mean your average sub $1000 gaming PC, not bleeding edge M6 Macs)