Comment by flowerlad
3 hours ago
The assumption here is that senior engineers are still needed to review AI-generated code. That assumption might not be valid for very long. I find myself reviewing AI-generated code less and less because the code quality is very good -- and getting better every month. Soon reviewing AI-generated code will be like manually verifying the results of a calculator--it is a waste of time. At that point all you need is an architect. I predict senior software engineers will be obsolete within a year.
As a principal, I still catch people submitting shitty AI code on a weekly basis. Their brains are rotting to the point that they can't tell if the code is doing the correct thing or not.
Just left my programming job due to this. Stopped thinking, stopped caring. AI destroyed my coding joy, so I’m finished with that. Leadership challenges next - hope to use my brain a bit more.
You won’t, leadership requires even less brain.
2 replies →
I've found myself engaging more with AI writing code. There is no easy time during the work day. I'm talking to product about what they want, communicating with AI to write it, and verifying that it covers what was asked for. And the better I get at it, the more of the product I need to learn at a faster pace. If I find some downtime, I work on additional features at the same time, something I wouldn't do on my own.
Quite simply, I'm more mentally drained at the end of a day working with AI than I am a normal day of coding. There is still a lot of energy and thought that needs to go into what needs to be written.
> mentally drained
Anecdotally, I find the flow-vs-drained state is more about who uses the LLM and whether I'm in a position to know the difference between artifact and intent.
1. [Good] I know what I wanted, I have a concept of what "correct" looks like. I ask the LLM to do the thing, and I check if it's the thing I intended. Even if it's annoyingly wrong, I can fix it up.
2. [Bad] Someone else had a concept once. They put it through an LLM to generate something that reaches me, a ticket, PR, or review comment. However now I have to constantly guess which parts of the thing are "real" and which are nonsense the human never actually intended or even noticed.
The latter is worsened by how reading means inferring/simulate the mind of the writer, but LLM output is not from a mind we typically simulate. Subtle persistent wrongness is exhausting.
The issue is the higher ups don't even seem to care. You just turn into the guy that's yelling at the clouds. I don't know what the future of this industry is.
> At that point all you need is an architect.
What value would an architect provide that a SOTA LLM can't?
As of now it is insufficient to outline the end-user requirements, AI will ask you a bunch of questions that requires you to make architectural decisions. I think within 3 to 5 years that might change as well.
If you say "yeah go with your own recommendation" every time you'll get something that'll at least kinda work sooner or later. Not sure you need an "architect."
But is that workflow enough in a competitive world anyway, or will there be an edge for people who do more than "outline the end-user requirements" like it's the waterfall 70s?
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