Comment by atleastoptimal | Hacker News Reader

Comment by atleastoptimal | Hacker News Reader

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The article is one person recording their own use of AI, finding no statistical significance but claiming since that the evaluated ratio of AI:human speed in performing various coding tasks resembled the METR study, that AI has no value. People have already talked about issues with the METR study, but importantly with that study and this blog post, it querying a small number of people using AI tools for the first time, working in a code base they already have experience and deep understanding of.

Their claim following that is that because there hasn't been an exponential growth in App store releases, domain name registrations or Steam games, that, beyond just AI producing shoddy code, AI has led to no increase in the amount of software at all, or none that could be called remarkable or even notable in proportion to the claims made by those at AI companies.

I think this ignores the obvious signs of growth in AI companies which providing software engineering and adjacent services via AI. These companies' revenues aren't emerging from nothing. People aren't paying them billions unless there is value in the product.

These trends include

1. The rapid growth of revenue of AI model companies, OpenAI, Anthropic, etc. 2. The massive growth in revenue of companies that use AI including Cursor, replit, loveable etc 3. The massive valuation of these companies

Anecdotally, with AI I can make shovelware apps very easily, spin them up effortlessly and fix issues I don't have the expertise or time to do myself. I don't know why the author of TFA claims that he can't make a bunch of one-off apps with capabilities avaliable today when it's clear that many many people can, have done so, have documented doing so, have made money selling those apps, etc.

> "These companies' revenues aren't emerging from nothing. People aren't paying them billions unless there is value in the product."

Oh, of course not. Just like people weren't paying vast sums of money for beanie babies and dotcoms in the late 1990s and mortgage CDOs in the late 2000s [EDIT] unless there was value in the product.

Those are fundamentally different. If people on this site really can't tell the difference then it makes sense why people on HN assume AI is a bubble.

People paid a lot for beanie babies and various speculative securities on the assumption that they could be sold for more in the future. They were assets people aimed to resell at a profit. They had no value by themselves.

The source of revenue for AI companies has inherent value but is not a resell-able asset. You can't resell API calls you buy from an AI company at some indefinite later date. There is no "market" for reselling anything you purchase from a company that offers use of a web app and API calls.

The central issue here is whether the money pouring into AI companies is producing anything other than more AI companies.

I think the article's premise is basically correct - if we had a 10x explosion of productivity where is the evidence? I would think some is potentially hidden in corporate / internal apps but despite everyone at my current employer using these tools we don't seem to be going any faster.

I will admit that my initial thoughts on Copilot were that "yes this is faster" but that was back when I was only using it for rote / boilerplate work. I've not had a lot of success trying to get it to do higher level work and that's also the experience of my co-workers.

I can certainly see why a particular subset of programmers find the tools particularly compelling, if their job was producing boilerplate then AI is perfect.

Yeah AI code is ideal for boilerplate, converting between languages, basically anything where the success criteria are definite. I don’t think there is a 10x productivity upgrade across the board, but in limited domains, yes, AI can produce human level work 10x faster.

The fundamental difference of opinion people have here though is some people see current AI capabilities as a floor, while others see it as a ceiling. I’d agree with arguments that AI companies are overvalued if current models are as capable as AI will ever be for the rest of time, but clearly that is not the case, and very likely, as they have been every few months over the past few years, they will keep getting better.

Which way is the rate of change going?

Dotcoms and CDOs absolutely had perceived intrinsic value

> The article is one person recording their own use of AI

It's not ONE person. I agree that it's not "every single human being" either, but more of a preliminary result, but I don't understand why you discount results you dislike. I thought you were completely rational?

https://www.theregister.com/2025/07/11/ai_code_tools_slow_do...

> The rapid growth of revenue of AI model companies, OpenAI, Anthropic, etc.

You can't use growth of AI companies as evidence to refute the article. The premise is that it's a bubble. The growth IS the bubble, according to the claim.

> I don't know why the author of TFA claims that he can't make a bunch of one-off apps

I agree... One-off apps seem like a place where AI can do OK. Not that I care about it. I want AI that can build and maintain my enterprise B2B app just as well as I can in a fraction of the time, and that's not what has been delivered.

Bubbles are born out of evaluations, not revenue. Web3 was a bubble because the money its made wasn't real productivity, but hype cycles, pyramid schemes, etc. AI companies are merely selling API calls, there is no financial scheming, it is very simply that the product is worth what it is being sold for.

> I want AI that can build and maintain my enterprise B2B app just as well as I can in a fraction of the time, and that's not what has been delivered.

AI isn't at that level yet but it is making fast strides in subsets of it. I can't imagine systems of models and the models themselves won't reach there in a couple years given how bad AI coding tools were just a couple years ago.

Does the revenue cover the costs?

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