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Posted by poisonfountain 15 hours ago

LLMs are eroding my software engineering career and I don't know what to do(human-in-the-loop.bearblog.dev)
825 points | 811 commentspage 9
viapivov 14 hours ago|
I wonder how do people use LLMs so it does not hallucinates. Like 90% of the time the code is impeccable, but the remaining 10%... Let's say I determine the expertise by how well do people act of these 10%. For me, the first pillar is still there, but not in a good condition
Lionga 14 hours ago|
Easy just add "Make no mistakes" to the proompt, clear skill issue.

In reality people who use LLMs so it does not hallucinate are the ones that just have to little knowledge to actually see when it does, because LLMs do and they always will. That is the only thing you can get with a stochastic word predictor.

jppope 10 hours ago||
Yes, Code Monkey jobs are gone... I can assure you though that there are plenty of hard problems that reduce human suffering which still need humans to solve them.
yoyohello13 12 hours ago||
I’m just continuing to get paid as long as I can, while also going back to school part time to train in a role that’s insulated from AI. Having a backup plan at least makes me feel better day to day.
causal 11 hours ago|
> to train in a role that’s insulated from AI

Would love to know more about that role

Havoc 10 hours ago||
>Would love to know more about that role

Anything that can't be done with a screen and internet connection is a good start

litver 14 hours ago||
"Except that nobody cares anymore." Noone (from mid-management) cared about it also before. You hit the deadline, get promoted and leave the technical debt to the next one. Even if you're the one to deal with it, you set up the next project, get the budget, prioritize the issues etc. Not much changed in this regard with LLMs
tantalor 13 hours ago||
Even if the model can replace a domain expert on the software side, you still need a human who can decide if the technical solution actually meets the business needs and that would require a human with domain expertise.
pfdietz 12 hours ago||
It feels like it's time to start turning the screws on regulation of software engineering.

If productivity is really getting better, regulation can force that productivity to go into increasing software quality.

ozim 13 hours ago||
I am kind of like of in the same place though roughly 5 years more than author.

I thought about going back to college, learning Math, Statistics, advanced Machine Learning and applying for research role at a frontier lab.

That's a super silly take. As much as I did math and even course on machine learning back in the days and I was making basic perceptron in code at university - to get back and be able to do so on frontier level that's years I don't have anymore.

Anthropic is doing all that also with their LLMs so that ship sailed.

Big thing is — business people are not going to spend time prompting LLM to make an application. If they do then they will become "programmers" and we all (experienced developers) know — you touch it you own it — they (business) will not bother running or taking responsibility.

Right now on r/sysadmin there was bunch of posts where admins have "vibe coded apps" requested to be "productionized". Those business types requesting don't know yet — you touch it you own it — they think they can vibe code app drop it at ops and it is all fun and games. When people will start requesting features, start nagging about bugs, start cursing on whatever changes they introduced it will be back to "hey maybe we will just get someone to do that for us".

  You might not need as deep software dev knowledge but with deep software dev knowledge you still will be faster operating LLM to build systems than non-dev
liglam 12 hours ago|
[dead]
amelius 13 hours ago||
It's not just our careers. In the hunks versus nerds wars, it is now clear who has won. The nerds have made themselves obsolete and put the continued evolution of homo sapiens to an abrupt halt.
trumpdong 12 hours ago|
No software developers == no humans?
amelius 12 hours ago||
No, homo sapiens degenerating into homo stupidus.
docheinestages 12 hours ago||
LLMs can synthesize the domain knowledge so long as it's within their training data. At some point, blindly trusting the decisions they make becomes gambling.
tossandthrow 12 hours ago|
There is this over indexing in training data that I find quite problematic.

I have really good results getting LLMs to read documentation and work of these. This is in domains probably sparsely represented in the training data.

docheinestages 9 hours ago||
In my experience, even the best frontier LLMs are very likely to make critical but subtle mistakes and false assumptions the more they're trying to one-shot the solution. One-shotting could be thought of as a broad term and varies depending on the use case. You have great results with LLMs because you did the job of finding the right documentation, and more importantly, those who wrote the documentation both had a deep understanding of the domain, and effectively compiled them into a coherent document. In other words, the more vetting, supervision, and research you do, the better the results. Of coruse, this doesn't mean doing the heavy lifting yourself. But the signal is key.
dalton_zk 11 hours ago|
Use the LLMs to improve your career as software engineer
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