Let's be honest, Generative AI isn't going all that well • Hacker News Board

Re: Let's be honest, Generative AI isn't going all that well

#71

Post by falloutx » Tue, Jan 13, 2026, 11:42 PM UTC

tombert wrote: post #56

falloutx wrote: post #53

Earlier quoted context omitted.

I am an AI-skeptic but I would agree this looks impressive from certain angles, especially if you're an early startup (maybe) or you are very high up the chain and just want to focus on cutting costs. On the other hand, if you are about to be unemployed, this is less impressive. Can it replace a human? I would say no its still long way to go, but a good salesman can convince executives that it does and thats all that…

I just think Jevins paradox [1]/Gustafson's Law [2] kind of applies here. Maybe I shouldn't have used the word "replaced", as I don't really think it's actually going to "replace" people long term. I think it's likely to just lead to higher output as these get better and better . [1] https://en.wikipedia.org/wiki/Jevons_paradox [2] https://en.wikipedia.org/wiki/Gustafson%27s_law

Not you, but the word replaced is the being used all the time. Even senior engineers are saying they are using it as a junior engineers while we can easily hire junior engineers (but Execs don't want to). Jevon's paradox wont work in Software because user's wallets and time is limited, and if software becomes too easy to build, it becomes harder to sell. Normal people can have 5 subscriptions, may be 10, but they wont be going to 50 or 100. I would say we would have already exhausted users already, with all the bad practices.

Re: Let's be honest, Generative AI isn't going all that well

#72

Post by smithkl42 » Tue, Jan 13, 2026, 11:43 PM UTC

tombert wrote: post #43

drewbug01 wrote: post #32

Earlier quoted context omitted.

> If your metric is an LLM that can copy/paste without alterations, and never hallucinate APIs, then yeah, you'll always be disappointed with them. I struggle to take comments like this seriously - yes, it is very reasonable to expect these magical tools to copy and paste something without alterations. How on earth is that an unreasonable ask? The whole discourse around LLMs is so utterly exhausting. If I say I don't…

I think what they're best at right now is the initial scaffolding work of projects. A lot of the annoying bootstrap shit that I hate doing is actually generally handled really well by Codex. I agree that there's definitely some overhype to them right now. At least for the stuff I've done they have gotten considerably better though, to a point where the code it generates is often usable, if sub-optimal. For example, a…

I think it USED to be true that you couldn't really use an LLM on a large, existing codebase. Our codebase is about 2 million LOC, and a year ago you couldn't use an LLM on it for anything but occasional small tasks. Now, probably 90% of the code I commit each week was written by Claude (and reviewed by me and other humans - and also by Copilot and ZeroPath).

Re: Let's be honest, Generative AI isn't going all that well

#73

Post by iwontberude » Tue, Jan 13, 2026, 11:44 PM UTC

habinero wrote: post #66

fzeroracer wrote: post #33

Earlier quoted context omitted.

> Meanwhile, my cofounder is rewriting code we spent millions of salary on in the past by himself in a few weeks. This is one of those statements that would horrify any halfway competent engineer. A cowboy coder going in, seeing a bunch of code and going 'I should rewrite this' is one of the biggest liabilities to any stable system.

Every professional SWE is going to stare off into the middle distance, as they flashback to some PM or VP deciding to show everyone they still got it. The "how hard could it be" fallacy claims another!

Definitely been in that room multiple times.

Re: Let's be honest, Generative AI isn't going all that well

#74

Post by the-grump » Tue, Jan 13, 2026, 11:45 PM UTC

zozbot234 wrote: post #60

gejose wrote: post #42

I believe Gary Marcus is quite well known for terrible AI predictions. He's not in any way an expert in the field. Some of his predictions from 2022 [1] > In 2029, AI will not be able to watch a movie and tell you accurately what is going on (what I called the comprehension challenge in The New Yorker, in 2014). Who are the characters? What are their conflicts and motivations? etc. > In 2029, AI will not be able to r…

> In 2029, AI will not be able to read a novel and reliably answer questions about plot, character, conflicts, motivations, etc. Key will be going beyond the literal text, as Davis and I explain in Rebooting AI. Can AI actually do this? This looks like a nice benchmark for complex language processing, since a complete novel takes up a whole lot of context (consider War and Peace or The Count of Monte Cristo ). Of cou…

Yes they can. The size of many codebases is much larger and LLMs can handle those.

Consider also that they can generate summaries and tackle the novel piecemeal, just like a human would.

Re: movies. Get YouTube premium and ask YouTube to summarize a 2hr video for you.

Re: Let's be honest, Generative AI isn't going all that well

#75

Post by idreyn » Tue, Jan 13, 2026, 11:45 PM UTC

zozbot234 wrote: post #60

gejose wrote: post #42

I believe Gary Marcus is quite well known for terrible AI predictions. He's not in any way an expert in the field. Some of his predictions from 2022 [1] > In 2029, AI will not be able to watch a movie and tell you accurately what is going on (what I called the comprehension challenge in The New Yorker, in 2014). Who are the characters? What are their conflicts and motivations? etc. > In 2029, AI will not be able to r…

> In 2029, AI will not be able to read a novel and reliably answer questions about plot, character, conflicts, motivations, etc. Key will be going beyond the literal text, as Davis and I explain in Rebooting AI. Can AI actually do this? This looks like a nice benchmark for complex language processing, since a complete novel takes up a whole lot of context (consider War and Peace or The Count of Monte Cristo ). Of cou…

Yes. I am a novelist and I noticed a step change in what was possible here around Claude Sonnet 3.7 in terms of being able to analyze my own unpublished work for theme, implicit motivations, subtext, etc -- without having any pre-digested analysis of the work in its training data.

Re: Let's be honest, Generative AI isn't going all that well

#76

Post by xp84 » Tue, Jan 13, 2026, 11:46 PM UTC

elzbardico wrote: post #41

maccard wrote: post #14

Earlier quoted context omitted.

> Generative AI, as we know it, has only existed ~5-6 years, and it has improved substantially, and is likely to keep improving. Every 2/3 months we're hearing there's a new model that just blows the last one out of the water for coding. Meanwhile, here I am with Opus and Sonnet for $20/mo and it's regularly failing at basic tasks, antigravity getting stuck in loops and burning credits. We're talking "copy basic exam…

There’s a subtle point a moment when you HAVE to take the driver wheel from the AI. All issues I see are from people insisting to use far beyond the point it stops being useful. It is a helper, a partner, it is still not ready go the last mile

It's funny how many people don't get that. It's like adding a pretty great senior or staff level engineer to sit on-call next to every developer and assist them, for basically free (I've never used any of the expensive stuff yet. Just things like Copilot, Grok Code in JetBrains, just asking Gemini to write bits of code for me).

If you hired a staff engineer to sit next to me, and I just had him/her write 100% of the code and never tried to understand it, that would be an unwise decision on my part and I'd have little room to complain about the times he made mistakes.

Re: Let's be honest, Generative AI isn't going all that well

#77

Post by kokanee » Tue, Jan 13, 2026, 11:46 PM UTC

dreadsword wrote: post #18

This feels like a pretty low effort post that plays heavily to superficial reader's cognitive biases. I work commercializing AI in some very specific use cases where it extremely valuable. Where people are being lead astray is layering generalizations: general use cases (copilots) deployed across general populations and generally not doing very well. But that's PMF stuff, not a failure of the underlying tech.

I think both sides of this debate are conflating the tech and the market. First of all, there were forms of "AI" before modern Gen AI (machine learning, NLP, computer vision, predictive algorithms, etc) that were and are very valuable for specific use cases. Not much has changed there AFAICT, so it's fair that the broader conversation about Gen AI is focused on general use cases deployed across general populations. After all, Microsoft thinks it's a copilot company, so it's fair to talk about how copilots are doing.

On the pro-AI side, people are conflating technology success with product success. Look at crypto -- the technology supports decentralization, anonymity, and use as a currency; but in the marketplace it is centralized, subject to KYC, and used for speculation instead of transactions. The potential of the tech does not always align with the way the world decides to use it.

On the other side of the aisle, people are conflating the problematic socio-economics of AI with the state of the technology. I think you're correct to call it a failure of PMF, and that's a problem worth writing articles about. It just shouldn't be so hard to talk about the success of the technology and its failure in the marketplace in the same breath.

Re: Let's be honest, Generative AI isn't going all that well

#78

Post by hamdingers » Tue, Jan 13, 2026, 11:46 PM UTC

jbs789 wrote: post #20

tombert wrote: post #10

I find it a bit odd that people are acting like this stuff is an abject failure because it's not perfect yet. Generative AI, as we know it, has only existed ~5-6 years, and it has improved substantially, and is likely to keep improving. Yes, people have probably been deploying it in spots where it's not quite ready but it's myopic to act like it's "not going all that well" when it's pretty clear that it actually is g…

Because the likes of Altman have set short term expectations unrealistically high.

I maintain that most anti-AI sentiment is actually anti-lying-tech-CEO sentiment misattributed.

The technology is neat, the people selling it are ghouls.

Re: Let's be honest, Generative AI isn't going all that well

#79

Post by kleene_op » Tue, Jan 13, 2026, 11:48 PM UTC

thethirdone wrote: post #63

gejose wrote: post #42

I believe Gary Marcus is quite well known for terrible AI predictions. He's not in any way an expert in the field. Some of his predictions from 2022 [1] > In 2029, AI will not be able to watch a movie and tell you accurately what is going on (what I called the comprehension challenge in The New Yorker, in 2014). Who are the characters? What are their conflicts and motivations? etc. > In 2029, AI will not be able to r…

Which ones of those have been achieved in your opinion? I think the arbitrary proofs from mathematical literature is probably the most solved one. Research into IMO problems, and Lean formalization work have been pretty successful. Then, probably reading a novel and answering questions is the next most successful. Reliably constructing 10k bug free lines is probably the least successful. AI tends to produce more bugs…

> Reliably constructing 10k bug free lines is probably the least successful.

You imperatively need to try Claude Code, because it absolutely does that.

Re: Let's be honest, Generative AI isn't going all that well

#80

Post by el_benhameen » Tue, Jan 13, 2026, 11:50 PM UTC

nsoonhui wrote: post #45

mattmaroon wrote: post #6

Meanwhile, my cofounder is rewriting code we spent millions of salary on in the past by himself in a few weeks. I myself am saving a small fortune on design and photography and getting better results while doing it. If this is not all that well I can’t wait until we get to mediocre!

It's not directly comparable. The first time writing the code is always the hardest because you might have to figure out the requirements along the way. When you have the initial system running for a while, doing a second one is easier because all the requirements kinks are figured out. By the way, why does your co-founder have to do the rewrite at all?

I find the opposite to be true. Once you know the problem you’re trying to solve (which admittedly can be the biggest lift), writing the fist cut of the code is fun, and you can design the system and set precedent however you want. Once it’s in the wild, you have to work within the consequences of your initial decisions, including bad ones.