I'm still at the bargaining phase, personally.
So I think LLMs have moved the effort that used to be spent on fun part (coding) into the boring part (assessment and evaluation) that is also now a lot bigger..
You can also setup way more elaborate verification systems. Don't just do a static analyis of the code, but actually deploy it and let the LLM hammer at it with all kinds of creative paths. Then let it debug why it's broken. It's relentless at debugging - I've found issues in external tools I normally would've let go (maybe created an issue for), that I can now debug and even propose a fix for, without much effort from my side.
So yeah, I agree that the boring part has become the more important part right now (speccing well and letting it build what you want is pretty much solved), but let's then automate that. Because if anything, that's what I love about this job: I get to automate work, so that my users (often myself) can be lazy and focus on stuff that's more valuable/enjoyable/satisfying.
Once the tools outperform humans at the tasks to which they were applied (and they will), you don't need to be involved at all, except to give direction and final acceptance. The tools will write, and verify, the code at each step.
I don't get why some people are so convinced that this is inevitable. It's possible, yes, but it very well might be the case, that models cannot be stopped from randomly doing stupid things, cannot be made more trustworthy, cannot be made more verifiable, and will have to be relegated to the role of brainstorming aids.
Someone once said that It is hard to make a man understand things if their profit depends on them not understanding it...
Many are still in denial that you can do work that is as good as before, quicker, using coding agents. A lot of people think there has to be some catch, but there really doesn’t have to be. If you continue to put effort in, reviewing results, caring about testing and architecture, working to understand your codebase, then you can do better work. You can think through more edge cases, run more experiments, and iterate faster to a better end result.
But specifically to your examples, the latter: I think the "brute force the program" approach will be more common that doing things manually in many cases (not all! I'm still a believer in people!).
Edit: Well, I wrote a bad blog post on this some time ago, I might as well share it: I think the accepting means engaging with the change rather than ignoring it.
https://riffraff.info/2026/03/my-2c-on-the-ai-genai-llm-bubb...
We don’t have to accept things.
— George Bernard Shaw
The antidote to runaway hype is for someone to push back, not to just relent and accept your fate. Who cares about affording to. We need more people with ideals stronger than the desire to make a lot of money.
When I say AI, I mean specifically LLMs. There isn't a single future position where all the risks are suitably managed, there is a return of investment and there is not a net loss to society. Faith, hope, lies, fraud and inflated expectations don't cut it and that is what the whole shebang is built on. On top of that, we are entering a time of serious geopolitical instability. Creating more dependencies on large amounts of capital and regional control is totally unacceptable and puts us all at risk.
My integrity is worth more than sucking this teat.
Or is it limited to refusal to use LLM, which is a strategy, but more like becoming a hobbyist programmer then.
I think in the foreseeable future we have open models running on commonly available hardware, and that is not a change that can be stopped (and arguably it's the commons getting back their own value). What we can do is fight for proper taxation, for compensatory fees, for regulation that limits plagiarism, for regulation of the most extreme externalities.
But it makes no sense, to me, to fight the technology tout court.
I mean, at some point it was true.
I remember that around 2023, when I first encountered colleagues trying to use ChatGPT for coding, I thought "by the time you are done with your back-and-forth to correct all the errors, I would have already written this code manually".
That was true then, but not anymore.
I'm not a proper software engineer, but I do a lot of scripting and most of my attempts to let a model speed up a menial task (e.g. a small bash or python script for some data parsing or chaining together other tools), end up with me doing extensive rewrites because the model is completely inconsistent in naming convention, pattern reusage, etc.
But the interesting stuff where you don't understand the problem yet, it doesn't make it quicker. Because then the bottleneck is my understanding. Things take time. And sleep. They require hands-on experience. It doesn't matter how fast LLMs can churn out code. There's a limit to how fast I can understand things. Unless, of course, I'm happy shipping code I don't understand, which I'm not.
All the incentives nudge you towards less and less critical evaluation of the output. The results of careful evaluation are much harder to measure than "this guy is cranking out 10x the code compared to last year!" And while you were busy thoughtfully internalizing the output, the guy next to you has been letting Strega Nona's pasta pot go brrr and spew another thousand lines of spaghetti on top, ready for you to review. Eventually "lgtm" becomes the default, and "do you want me to go ahead and implement that for you" starts sounding like the only way to keep your head above water.
To all of you I can only say, you were utterly wrong and I hope you realize how unreliable your judgements all are. Remember I'm saying this to roughly 50% of HN., an internet community that's supposedly more rational and intelligent than other places on the internet. For this community to be so wrong about something so obvious.... That's saying something.
They weren't wrong though. It objectively is just a next turn predictor and doesn't understand code. That is how the thing works.
Don’t make me cite George Hinton or other preeminent experts to show you how wrong you all are.
Use your brain. It is changing the industry from the ground up. It understands.
George Hinton was his mentor and George is the main god father of AI while Yann is more of a malfunctioning student still holding onto the stochastic parrot monicker. Here's George saying what you need to know:
https://www.reddit.com/r/agi/comments/1qwoee7/godfather_of_a...
How was he "proven" wrong?
> Yann is more of a malfunctioning student...
lol what?
Yann is malfunctioning because he cant reconcile his past statements with reality. He can’t admit he’s wrong. As time goes on his past statements will look even more and more absurd as progress on AI keeps moving forward.
At the same time we have Terence Tao using ai to develop new math and Hinton saying the opposite with actual evidence and the entire industry. Yann is a clown: https://www.reddit.com/r/singularity/comments/1piro45/people... and his opinions are not mainstream at all.
Actually that is done by bolting more "fact checking" layers on top. Even that does not fix it very well..
So at a fundamental level, LLMs have not really progressed. On a superficial level, they have, but that is only because marketing wanted to show the "progress" over a short amount of time, so that the "uninitiated" will extrapolate that to mean some god like AI in near future, raking in all the investor money...
Smart move though. It is working very well....
Reinforcement training is done as well. And it fixed it quite well such that we use it on a daily basis now.
>So at a fundamental level, LLMs have not really progressed. On a superficial level, they have,
No those fixes aren't superficial. They're the same fixes you have in your brain. You also fact check, people also hallucinate and people with brain damage hallucinate even more. You can bypass mechanisms in your brain that prevent hallucination by taking drugs.
Essentially the brain is a big hallucination machine with mechanisms to prevent it both low level and high level. We even consciously fact check ourselves and double check our own work. Is that superficial? No.
You look at progress by seeing how LLMs are used. At first they were used as a chatbot. Then it became autocomplete. Now basically most people don't code with their hands anymore and they use it as an agent. That is the most disruptive thing to ever happen to programming. This isn't an investor thing. This is REALITY.
>So at a fundamental level, LLMs have not really progressed. On a superficial level, they have, but that is only because marketing wanted to show the "progress" over a short amount of time, so that the "uninitiated" will extrapolate that to mean some god like AI in near future, raking in all the investor money...
This is you hallucinating. Investor money is raking in because they are closer than ever to creating AI that can replace developers and companies will pay top dollar for that. That's why AI is making money. Very few people are that speculative into making a god AI... but a few are and those are the people throwing money at Yann's AMI venture which is huge gamble and could have that money end up in the trash.
But LLM technology? We use it everyday. It's already a validated technology.
>Smart move though. It is working very well....
I can ask an LLM, "hey, human society is changing before our very eyes. Nobody programs directly anymore" The LLM is not so stupid as to say that's "superficial" progress. That's a smarter answer then a lot of the people here.
I would say 6 months ago, I would get like 5 or 6 detractors responding to one of my posts like this. Now I think this thread got 2 and a bunch of vote downs. People are realizing they're embarrassingly wrong. It'll hit you eventually. It will happen either in the next couple months or next couple years simply because humanity is pouring so much research into this area there is no way it won't progress.
For a good analogy you just need to look at self driving cars. HN used to be loaded with people saying it was a shit venture and totally useless and no progress has been made.... well now I regularly take waymo cars everywhere. Investors were wrong about crypto, but they weren't wrong about self driving.
I would say the HN crowd is just as stupid if not more stupid then investors.
Not really. LLMs will still happily hallucinate and even provide "sources" for their claims and when you check the sources often it does not even exist..
So they will even hallucinate the sources to justify their hallucinated claims. LOL.
And it’s only going to get better.
It’s clear the LLM hallucinates and understands at the same time.
You gonna give some predictable answer about next token prediction and probability or some useless exposition on transformers while completely avoiding the fact that we don’t understand the black box emergent properties that make a next token predicted have properties indistinguishable from intelligence?
I don’t have any questions about LLMs. At least not any more than say an LLM researcher at anthropic working on model interpretability.
My conclusion is that at this point, LLMs are not capable of making good decisions supported by deep reasoning. They're capable of mimicking that, yes, and it takes some skill to see through them.
As of right now the one shot complex solutions AI comes up with are actually frequently extremely good now. It’s only gonna get better and this was in the last 6 months. You could be outdated on frontier model progress. That’s how quick things are changing.
The difference is the arrogance. Developers think they know more. Developers think they're smart. And also there's an existential crisis where the LLM are poised to take over developer jobs first. So the developer calls every other layman an idiot and deludes himself into thinking his skills will always be superior to AI.