Is it a bubble?

Same here, and I think it's because I feel like a craftsman. I thoroughly enjoy the process of thinking deeply about what I will build, breaking down the work into related chunks, and of course writing the code itself. It's like magic when it all comes together. Sometimes I can't even believe I get to do it!

I've spent over a decade learning an elegant language that allows me to instruct a computer—and the computer does exactly what I tell it. It's a miracle! I don't want to abandon this language. I don't want to describe things to the computer in English, then stare at a spinner for three minutes while the computer tries to churn out code.

I never knew there was an entire subclass of people in my field who don't want to write code.

I want to write code.

In my heart, I firmly believe in the ability of technology to uplift and improve humanity - and have spent much of my career grappling with the distressing reality that it also enables a handful of wealthy people to have near-total control of society in the process. AI promises a very hostile, very depressing, very polarized world for everyone but those pulling the levers, and I wish more people evaluated technology beyond the mere realm of Computer Science or armchair economics. I want more people to sit down, to understand its present harms, its potential future harms, and the billions of people whose lives it will profoundly and negatively impact under current economic systems.

It's equal parts sobering and depressing once you shelve personal excitement or optimism and approach it objectively. Regardless of its potential as a tool, regardless of the benefit it might bring to you, your work day, your productivity, your output, your ROI, I desperately wish more people would ask one simple question:

Is all of that worth the harm I'm inflicting on others?

It can be an accelerator - it gets extremely common boiler-plate text work out of the way. But it can't replace any job that requires a functioning brain, since LLMs do not have one - nor ever will.

But in the end it doesn't matter. Companies do whatever they can to slash their labor requirements, pay people less, dodge regulations, etc. If not 'AI' it'll just be something else.

This artificial creativity will only go so far, because it's a simulated semblance of human creativity, as much as could be gathered from training data. If not continually refueled by new training data, it will run out sooner or later. And then it will get boring really quickly.

Now imagine a different sort of company. A little shop where the owner's first priority is actually to create good jobs for their employees that afford a high quality life. A shop like that needn't worry about AI.

It is too bad that we put so much stock as a society in businesses operating in this dehumanizing capacity instead of ones that are much more like a family unit trying to provide for each other.

> This strikes me as paradoxical given my sense that one of AI’s main impacts will be to increase productivity and thus eliminate jobs.

The allegation that an "Increase of productivity will reduce jobs" has been proven false by history over and over again it's so well known it has a name, "Jevons Paradox" or "Jevons Effect"[0].

> In economics, the Jevons paradox (sometimes Jevons effect) occurs when technological advancements make a resource more efficient to use [...] results in overall demand increasing, causing total resource consumption to rise.

The "increase in productivity" does not inherently result in less jobs, that's a false equivalence. It's likely just as false as it was in 1915 with the the assembly line and the Model T as it is in 2025 with AI and ChatGPT. This notion persists because as we go through inflection points due to something new changing up market dynamics, there is often a GROSS loss (as in economics) of jobs that often precipitates a NET gain overall as the market adapts, but that's not much comfort to people that lost or are worried about losing their jobs due to that inflection point changing the market.

The two important questions in that context for individuals in the job market during those inflections points (like today) are: "how difficult is it to adapt (to either not lose a job, or to benefit from or be a part of that net gain)?" and "Should you adapt?" Afterall, the skillsets that the market demands and the skillsets it supplies are not objectively quantifiable things; the presence of speculative markets is proof that this is subjective, not objective. Anyone who's ever been involved in the hiring process knows just how subjective this is. Which leads me to:

> the promise is about replacing human creativity with artificial creativity which.. is certainly new and unwelcome.

Disagree that that's what the promise about. That IS happening, I don't disagree there, but that's not the promise that corporate is so hyped about. If we're being honest and not trying to blow smoke up people's ass to artificially inflate "value," AI is fundamentally about being more OBJECTIVE than SUBJECTIVE with regard to costs and resources of labor, and it's outputs. Anyone who knows what OKR's are and has been subject to a "performance review" in a self professed "Data driven company" knows how much modern corporate America, especially the tech market, loves it's "quantifiables." It's less about how much better it can allegedly do something, but the promise of how much "better" it can be quantified vs human labor. As long as AI has at least SOME proven utility (which it does), this promise of quantifiables combined with it's other inherent potential benefits (Doesn't need time off, doesn't sleep, doesn't need retirement/health benefits, no overtime pay, no regulatory limitations on hours worked, no "minimum wage") means that so long as the monied interests perceive it as continuing to improve, then they can dismiss it's inefficiencies/ineffectiveness in X or Y by the promise of it's potential to overcome that eventually.

It's the fundamental reason why people are so concerned about AI replacing Humans. Especially when you consider one of the things that AI excels at is quickly delivering an answer with confidence (people are impressed with speed and a sucker for confidence), and another big strength is it's ability to deal with repetitive minutia in known and solved problem spaces(a mainstay of many office jobs). It can also bullshit with best of them, fluff your ego as much as you want (and even when you don't), and almost never says "No" or "You're wrong" unless you ask it to.

In other words, it excels at the performative and repetitive bullshit and blowing smoke up your boss' ass and empowers them to do the same for their boss further up the chain, all while never once ruffling HR's feathers.

Again, it has other, much more practical and pragmatic utility too, it's not JUST a bullshit oracle, but it IS a good bullshit oracle if you want it to be.

0: https://en.wikipedia.org/wiki/Jevons_paradox

https://www.youtube.com/watch?v=_zfN9wnPvU0

Drives people insane:

https://www.youtube.com/watch?v=yftBiNu0ZNU

And LLM are economically and technologically unsustainable:

https://www.youtube.com/watch?v=t-8TDOFqkQA

These have already proven it will be unconstrained if AGI ever emerges.

https://www.youtube.com/watch?v=Xx4Tpsk_fnM

The LLM bubble will pass, as it is already losing money with every new user. =3

I no longer believe this. A friend of mine just did a stint a startup doing fairly sophisticated finance-related coding and LLMs allowed them to bootstrap a lot of new code, get it up and running in scalable infra with terraform, and onboard new clients extremely quickly and write docs for them based on specs and plans elaborated by the LLMs.

This last week I extended my company's development tooling by adding a new service in a k8s cluster with a bunch of extra services, shared variables and configmaps, and new helm charts that did exactly what I needed after asking nicely a couple of times. I have zero knowledge of k8s, helm or configmaps.

More importantly, the web is now dominant for enterprise SaaS applications, which is a category of software that did not really exist before the web. And the web post–dot-com bubble spawned a lot of unicorns.

In short, there was an investment bubble. But the core tech was fine.

AI feels like one of those things where the tech is similarly transformational (even more so, actually). It’s another investment bubble predicated on the price of GPUs, which is mostly making Nvidia very rich right now.

Right now the model makers are getting most of the funding and then funneling non-trivial amounts to Nvidia (and their competitors). But actually the value creation is in applications using the models these companies create. And the innovation for that isn’t coming from the likes of Anthropic, OpenAI, Mistral, X.ai, etc. They are providing core technology, but they seem to be struggling to do productive things in terms of UX and use cases. Most of the interesting things in this space are coming from smaller companies figuring out how to use the models these companies produce. Models and GPUs are infrastructure, not end-user products.

And with the rise of open-source models, open algorithms, and exponentially dropping inference costs, the core infrastructure technology is not as much of a moat as it may seem to investors. OpenAI might be well funded, but their main UI (ChatGPT) is surprisingly limited and riddled with bugs. That doesn’t look like the polished work of a company that knows what they are doing. It’s all a bit hesitant and copycat. It’s never going to be a magic solution to everyone’s problems.

From where I’m sitting, there is clear untapped value in the enterprise space for AI to be used. And it’s going to take more than a half-assed chat UI to unlock that. It’s actually going to be a lot of work to build all of that. Coding tools are, so far, the most promising application of reasoning models. It’s easy to see how that could be useful in the context of ERP/manufacturing, CRM, traditional office applications, and the financial world.

Those each represent verticals with many established players trying to figure out how to use all this new stuff — and loads more startups eager to displace them. That’s where the money is going to be post-bubble. We’ve seen nothing yet. Just like after the dot-com bubble burst, all the money is going to be in new applications on top of the new infrastructure. It’s untapped revenue. And it’s not going to be about buying GPUs or offering benchmark-beating models. That’s where all the money is going currently. That’s why it is a bubble.

Also in a case of just prose to code, Claude wrote up a concurrent data migration utility in Go. When I reviewed it, it wasn't managing goroutines or waitgroups well, and the whole thing was a buggy mess and could not be gracefully killed. I would have written it faster by hand, no doubt. I think I know more now and the calculus may be shifting on my AI usage. However, the following day, my colleague needed a nearly identical temporary tool. A 45 minute session with Claude of "copy this thing but do this other stuff" easily saved them 6-8 hours of work. And again, that was just talking with Claude.

I am doing a hybrid approach really. I write much of my scaffolding, I write example code, I modify quick things the ai made to be more like I want, I set up guard rails and some tests then have the ai go to town. Results are mixed but trending up still.

FWIW, our CEO has declared us to be AI-first, so we are to leverage AI in everything we do which I think is misguided. But you can bet they will be reviewing AI usage metrics and lower wont be better at $WORK.

> Coding performed by AI is at a world-class level, something that wasn’t so just a year ago.

Wow, finance people certainly don't understand programming.

Lots of people are outing themselves these days about the complexity of their jobs, or lack thereof.

Which is great! But it's not a +1 for AI, it's a -1 for them.

Surely that revenue is coming from people using the services to generate code? Right?

>The key is to not be one of the investors whose wealth is destroyed in the process of bringing on progress.

They are a VC group. Financial folks. They are working largely with other people's money. They simply need not hold the bag to be successful.

Of course they don't care if its a bubble or not, at the end of the day, they only have to make sure they aren't holding the bag when it all implodes.

But to say that they don't write any code at all, it's really stretched. Maybe I'm not good enough at AI-assisted and vibe coding, but code-quality always seems to drop down really hard the moment one steps a bit outside the common patterns.

It has become a standard tool, in the same way that most developers code with an IDE, most developers use agentic AI to start a task (if not to finish it).

Error bars, folks, use them.

Though I do think "advanced software team" is kind of an absurd phrase, and I don't think there is any correlation with how "advanced" the software you build is and how much you need AI. In fact, there's probably an anti-correlation: I think that I get such great use out of AI primarily because we don't need to write particularly difficult code, but we do need to write a lot of it. I spend a lot of time in React, which AI is very well-suited to.

EDIT: I'd love to hear from people who disagree with me or think I am off-base somehow about which particular part of my comment (or follow-up comment https://news.ycombinator.com/item?id=46222640) seems wrong. I'm particularly curious why when I say I use Rust and code faster everyone is fine with that, but saying that I use AI and code faster is an extremely contentious statement.

This is mission critical robotics software

I wrote 4000 lines of Rust code with Codex - a high throughput websocket data collector.

Spoiler: I do not know Rust at all. I discussed possible architectures with GPT/Gemini/Grok (sync/async, data flow, storage options, ...), refined a design and then it was all implemented with agents.

Works perfectly, no bugs.

Well, except developers have never had to worry about code as even in the pre-compiler days coders, a different job done by a different person, were responsible for producing the code. Development has always been about writing down what you want and letting someone or something else generate the code for you.

But the transition from human coders to AI coders happened like, what, 60-70 years ago? Not sure why this is considered newsworthy now.

Not sure it's a wild speculative claim. Claiming someone had achieved FTL travel would fall into that category. I'd call it more along the lines of exaggerated.

I'll make the assumption that what I do is "advanced" (not React todo apps: Rust, Golang, distributed systems, network protocols...) and if so then I think: it's pretty much accurate.

That said, this is only over the past few moths. For the first few years of LLM-dom I spent my time learning how they worked and thinking about the implications for understanding of how human thinking works. I didn't use them except to experiment. I thought my colleagues who were talking in 2022 about how they had ChatGPT write their tests were out of their tiny minds. I heard stories about how the LLM hallucinated API calls that didn't exist. Then I spent a couple of years in a place with no easy code and nobody in my sphere using LLMs. But then around six months ago I began working with people who were using LLMs (mostly Claude) to write quite advanced code so I did a "wait what??..." about-face and began trying to use it myself. What I found so far is that it's quite a bit better than I am at various unexpected kinds of tasks (finding bugs, analyzing large bodies of code then writing documentation on how it works, looking for security vulnerabilities in code) or at least it's much faster. I also found that there's a whole art to "LLM Whispering" -- how to talk to it to get it to do what you want. Much like with humans, but it doesn't try to cut corners nor use oddball tech that it wants on its resume.

Anyway, YMMV, but I'd say the statement is not entirely false, and surely will be entirely true within a few years.

---------------

This was quoted in the article and it says something really important very succinctly. Was the internet transformative? Absolutely. A lot of companies had solid ideas, spent big, and went tits up waiting for the money to roll in.

AI can be both "real deal" and "bubble" simultaneously.

This seems like a factually correct sentence. Emphasis on "potential".

...AI is currently the subject of great enthusiasm. If that enthusiasm doesn’t produce a bubble conforming to the historical pattern, that will be a first.

I get that laymen and the media do it, but imo this looks really bad for an investor.

AI data centers in space? In five years? Really? No fiber connections? Does any sane person actually believe this? No. But if that is what keeps the billions flowing upwards then who am I to judge.

People seem to have forgotten about the dotcom bubble.

See, AI is a field... and it's also a buzzword: once a technology passes out of fashion and becomes part of the fabric of computing, it is no longer called AI in the public imagination. GOFAI techniques, like rules engines and propositional-logic inference, were certainly considered AI in the 1970s and 1980s, and are still used, they're just no longer called that.

The statistical methods behind machine learning, transformers, and LLMs are certainly game changers for the field. Whether they will usher in a revolutionary new economy, or simply be accepted as sometimes-useful computation techniques as their limitations and the boundaries of their benefits become more widely known, remains to be seen but I think it will be closer to the latter than the former.

You know how to? What language does it speak?

As a founder of an AI company, I actually agreed with most of the article and found it to be very close to my mental model of the world. Turns out you might actually not need to understand what's causing the hype if you know that history rhymes...!

But you don't need to understand to explore the ramifications which is what he's done here and it's an insightful & fairly even-handed take on it.

It does feel like AI chat here gets bogged down on "its not that great, its overhyped etc." without trying to actually engage properly with it. Even if it's crap if it eliminates 5-10% of companies labour cost that's a huge deal and the second order effects on economy and society will be profound. And from where i'm standing, doing that is pretty possible without ai even being that good.

https://metr.org/blog/2025-07-14-how-does-time-horizon-vary-...

FWIW, the only optimism I have is that humanity seemingly always finds a way to adapt and its, to me, our greatest superpower. But yeah, this feels like a big challenge this time

Another huge issue that particularly Anthropic and OpenAI tend to avoid, despite AGI being their goal, is how they essentially want synthetic slaves. Again, I do not think they will achieve this but it is pretty gross when AGI is a stated goal but the result is just using it to replace labor and put billionaires in control.

Right now I am pretty anti-AI, but if these companies get what they want, I might find myself on the side of the machines.

With respect to the microphone test site I don't need it as my OS provides everything I need for this and I also don't trust your site (that's just by default for what you're asking to have access or my machine).

As for the speed test, OK? There are far better options that already exist and are fully open source.

Building things that are trivial, or already exist aren't exciting. It's great that you feel you went from MVP to "full feature". But IMO both of these are MVPs as they stand. They're not worth much to anyone but you, most likely.

The final thing I'll say is both of these examples have the vibe coded look. It's just like text, images and audio now: AI content is easy to pick out. I'd gather things will get better, but for now there's low likelihood I'm interacting with these in any meaningful way and zero chance I'm buying anything from sites like these.

I've built tools like this on the web in the past. They were never more than a weekends worth of work to begin with.

I am looking for exponential increases, with quality to back it up.

AI use cases do not appear to be of the type that unlock NEW capabilities.

The main use cases in AI are not about wealth creation but about saving existing wealth (largely through increased automation of human operators).

I do think at this stage the best analogy is the offshore call centres. Yes, the excess in the market is likely because of misunderstanding about what LLMs can actually do and how close AGI is, the short term attraction is the labour cost savings. People may not think wages are high enough etc but the total cost for one hire to companies, particularly outside the US, is nothing to sniff at. And at current pricing of ai services, the maths would make complete sense for the bottom line.

I don't like it, because I ultimately err on the side of even limited but significant changes to people's livelihood will make the world a more hostile place (particularly in the current climate), but that's the society we live in

Either the bubble bursts and everyone's retirement funds take a hit, 2008 style,

Or a decent chunk of the workforce becomes unemployed and unemployable.

(I think a reasonable argument can be made that P/E ratios today should be higher than the historical mean, or rather that they should have trended up over time, based on fundamental changes in how companies compensate their shareholders.)

Before ChatGPT, I'd guess that the amounts of money poured in both of these things were about the same.

Fusion power on the other hand has to work as it doesn't make money until it does. You can't sell futures to people on a fusion technology today that you haven't yet built.

You will get a different result if you revolutionize some related area (like making an extremely capably superconductor), or if you open up some market that can't use the cheapest alternatives (like deep space asteroid mining). But neither of those options can go together with "oh, and we will achieve energy positive fusion" in a startup business plan.

Investment in fusion is huge and rising. ITER's total cost alone will be around $20b. And then there's Commonwealth Fusion, Helion, TAE and about a dozen others. Tens of billions are going into those efforts too.

See, every fab costs double what the previous generation did (current ones run roughly 20 gigadollars per factory). And you need to build a new fab every couple of years. But, if you can keep your order book full, you can make a profit on that fab- you can get good ROI on the investment and pay the money people back nicely. But you need to go to the markets to raise money for that next generation fab because it costs twice what your previous generation did and you didn't get that much free cash from your previous generation. And the money men wouldn't want to give it to you, of course. But thanks to Moore's Law you can pitch it as inevitable, if you don't borrow the money to build the new fab, then your competitors will. And so they would give you the money for the new fab because it says right on this paper that in another two years the transistors will double.

Right now, that "it's inevitable, our competitors will get there if we don't" argument works on VCs if you are pitching LLM's or LLM based things. And it doesn't work as well if you are pitching battery technology, fusion power, or other areas. And that's why the investments are going to AI.

That sounds like a total nightmare

Let's just say the AI bubble started in 2023. We still have about 3 years, more or less, until the AI bubble pops.

I do believe we are in the build out phase of the AI bubble, much like the dotcom bubble, where Cisco routers, Sun Microsystems servers... etc. sold like hotcakes to build up the foundation of the dotcom bubble

We're too easily fooled by our mistaken models of the problem, it's difficulty, and what constitutes progress, so are perpetually fooled by the latest, greatest "ladder to the moon" effort.

Looking at your history it's something like "I tried them and they hallucinate" and, possibly, you've read an article that talks about inevitability of hallucinations. Correct? What's your reason for thinking that hallucination rate can't be lowered to or below the human rate ("Damn! What I was thinking about?").

How about when offices went digital? All the file runners, calculators, switchboard operators, secretaries, transcribers, etc. Where are they now? Probably not working good jobs in IT. Maybe you will find them bagging groceries past retirement age today.

https://news.ycombinator.com/context?id=46136301

I literally just today watched my entire team descend into "Release Hell" where an obscure bug in business logic already delivered to thousands of customers broke right as we were about to ship a release. Obscure bug, huge impact on the customer, as they actually ended up charging people more than they should have. The team-members, and yes, not leads, used AI to write that bug and then tried to prompt their way out of the bug. It turned into a giant game of whack-a-mole as other business logic had errors introduced that thankfully got caught by tests. Then it was discovered that they never understood the code, they could only maintain it with prompts.

Let that sink in. They don't understand what they're doing, they just massage the spec into prompts and when it appears to work and pass tests they call it good.

We looked at the prompts. They were insane. They actually just kept adding more specification to the end, but if you read through it all it had contradictory logic, which I would have hoped the AI would have pointed out, but nope. It was actually just easier for me and another senior to rewrite the logic as pseudo-code, cut the size down by literally 3/4, and eventually got it all working as expected.

So that's the future, girls and boys. People putting together code they don't understand with AI, and can only maintain with AI, and then not being able to fix with AI because they cannot prompt accurately enough because English sucks at being precise.

That doesn't mean there will be a crash, though. Not all bubbles pop.

...it is a bubble and we all know it.

(I know you have RSUs / shares / golden handcuffs waiting to be vested in the next 1 - 4 years which is why you want the bubble to continue to get bigger.)

But one certainty is the crash will be spectacular.

I don't know which "y'all" you're talking about because it's certainly not the HN crowd, who is famously anti-cryptocurrency in general. Perhaps you're thinking of the bros on Twitter back then.

There is literally a section that begins, "What will be the useful life of AI assets?" In bold.

I am not sure why that is interesting. Nobody thinks of these chips as long term assets that they are investing in. Cloud providers have always amortized their computers over ~5 years. It would be very surprising if AI companies were doing much different -- maybe even a shorter time line.