I think Anthropic and OpenAI have found product-market fit • Hacker News Board

Re: I think Anthropic and OpenAI have found product-market fit

#831

Post by [deleted] » Thu, May 28, 2026, 8:19 AM UTC

mesmertech wrote: post #15

binary0010 wrote: post #12

So how do openai and anthropic plan to keep customers when GLM-5.1 is just as good and open source and a lot cheaper? I don't see the business model working. My closest friend actually does automation software for large companies. He does not use Claude or openai at all. He primarily uses gpt 120b on cerebras and glm-5.1 for heavy thinking work. And some other small models for various tasks. All open source. And thes…

For coding you always want to go with the best model in the category, not something that would be the best model if we went 1 year back which GLM 5.1 is, and I'm saying that as a big fan of GLM cause I run a translation site where GLM is good enough for the price. Most of the money right now is in coding. Openai and Anthropic just have to be 6 months ahead of SOTA open source models and they'll capture most of the en…

[deleted]

Re: I think Anthropic and OpenAI have found product-market fit

#832

Post by lelanthran » Thu, May 28, 2026, 8:19 AM UTC

simonw wrote: post #533

noddingham wrote: post #530

I feel like there's a bit of AI psychosis in this particular post. >"These are tools which burn vastly more tokens, but are also quickly becoming daily drivers for the work carried out by extremely well-compensated professionals." >"Somehow this fragment turned into headlines like Uber’s COO says it’s getting harder to justify the money spent on AI tokenmaxxing, because the market for stories about AI failures remain…

What's the psychosis?

Hi Simon; while it's true that the token providers have found that their product is 90% useful to devs and 10% useful to everyone else, this is something they found out in the first quarter of 2025 anyway.

It's not exactly news, is what I'm saying. And even with the PMF they found, the product is still only a commodity i.e `tokens`, which is what every other provider on the planet is also providing.

All their other products boil down to "harnesses", which does not look viable as a product in the sense of PMF - you cannot sell it, you cannot lock it to your own subscription, API, etc. so you can't use it to generate revenue any more than the free harnesses do.

PMF has a specific meaning, and "code harness" or "coding model" does not satisfy the commonly accepted meaning. Maybe Mythos (or similar) will.

Re: I think Anthropic and OpenAI have found product-market fit

#833

Post by AdamN » Thu, May 28, 2026, 8:21 AM UTC

trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

It's worth noting that if each developer is 20% more productive with AI (let's take that as a premise and not dispute it), then it makes sense to go even further and reduce human headcount by more since the communication overhead of having 25% fewer developers is in and of itself a force multiplier.

tldr; 10 developers with 20% more 'productivity' can be replaced by 7.5 ideal developers and more like 6 or 7 developers due to the benefits of simply requiring less organizational communication.

I still think the ideal team size is unchanged however and that's 7-10 people. Note that teams aren't necessarily the same as direct reports. A CEO for instance has a certain number of reports and a leadership 'team' but they're not a team in the traditional sense since they are more about making good decisions and collaborating on specific things but mostly about leading their own orgs that have vastly different skillsets from eachother.

Re: I think Anthropic and OpenAI have found product-market fit

#834

Post by suddenlybananas » Thu, May 28, 2026, 8:23 AM UTC

noname120 wrote: post #824

lunar_mycroft wrote: post #574

Earlier quoted context omitted.

> For coding you always want to go with the best model in the category This is transparently false, because the best "model" is still competent human developers. They're just more expensive. If you're willing to use current LLMs at all, it means you're willing to sacrifice quality for a better price, and your disagreement with the comment you were replying to is entirely about what the optimum tradeoff is.

It was true 6 months ago, not anymore. Frontier models now outperform developers on many tasks, be it on quality/readability/maintainability, and let’s not talk about speed…

Why is anthropic hiring software developers then?

Re: I think Anthropic and OpenAI have found product-market fit

#835

Post by svara » Thu, May 28, 2026, 8:31 AM UTC

simplyluke wrote: post #536

svara wrote: post #382

Earlier quoted context omitted.

There's still a lot of room for the best models to get better at coding . Your argument rests on the "for marginal gains" part but it's really not clear that the gains are marginal in the foreseeable future.

This is totally valid and I don't agree with the downvotes you're getting. Someone coming out with a 10x improvement is possible and would change the game immediately. The thing is, we really have been seeing marginal gains with shifting leaders in who's got the "best" since GPT3, and at least as a user of these tools that pace has been slowing, not accelerating. Subjectively it feels like we're in the back half of a…

I agree with most of what you're saying, but I think the point I was trying to make wasn't as high-flying as you and others understood it.

I'd pay a premium for even just a model that's 20% better, no ASI required, and I think a lot of people would. I wouldn't call that marginal, if it means I'm getting frustrated on 20% fewer tasks.

A recurring pattern that I've seen in myself and others is to at first be very impressed by a new model's coding capabilities, and then desensitize quickly and start being frustrated by the shortcomings.

Re: I think Anthropic and OpenAI have found product-market fit

#836

Post by raxxorraxor » Thu, May 28, 2026, 8:35 AM UTC

trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

Plus, at some point there are less tokens because local models being optimised and can work with protected information. For enterprises that want an AI with a knowledge base of internal documents, this becomes more interesting by the day.

Re: I think Anthropic and OpenAI have found product-market fit

#837

Post by WinstonSmith84 » Thu, May 28, 2026, 8:35 AM UTC

an0malous wrote: post #688

simplyluke wrote: post #305

Earlier quoted context omitted.

Yeah, that's the part that just seems to be wildly under-discussed to me. If open source models are ~3-6 months behind SOTA, and ~opus4.6 capabilities are good-enough for product market fit, do the frontier labs have half a decade to catch up on their prior burn? AI cost ballooning faster than companies can afford is becoming a very common topic in my circles right now. The era of "I'll pay infinitely more for margin…

> If open source models are ~3-6 months behind SOTA, and ~opus4.6 capabilities are good-enough for product market fit, do the frontier labs have half a decade to catch up on their prior burn? They know they do not and that’s why they’re all trying to IPO right now, so they can pass the bag to consumer investors

More correlation, if more correlation was needed:

1- SpaceX + Tesla + xAI merger / IPO while Musk was vocal against IPO for about a decade

2- Warren Buffett cash at record highs

Someone got to be exit liquidity

Re: I think Anthropic and OpenAI have found product-market fit

#838

Post by orphea » Thu, May 28, 2026, 8:40 AM UTC

hgoel wrote: post #752

trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

The fuck is going on with HN that a comment making up completely fantastical numbers is on top?

Perhaps it's not only CEOs who are delusional.

Re: I think Anthropic and OpenAI have found product-market fit

#839

Post by skeledrew » Thu, May 28, 2026, 8:40 AM UTC

x187463 wrote: post #5

I wonder how a focus on per-token API profits will impact the incentives to improve token efficiency and drive down costs through optimized compute. I suppose as long as a few leading labs are competing, we'll see progress in this regard, but it's certainly less in their interest than it is with a flat subscription pricing model.

There's also increasing pressure from China: note the massive permanent price reductions DeepSeek and Xiaomi announced in the past few days, with the possibility of more around the corner. And there's also the constant release of increasingly capable open weight models.

Re: I think Anthropic and OpenAI have found product-market fit

#840

Post by skeledrew » Thu, May 28, 2026, 8:49 AM UTC

tredre3 wrote: post #598

sourcecodeplz wrote: post #547

Earlier quoted context omitted.

Deepseek and all the other Chinese models have open-weights. You can host them yourself, no need to send data to China or rely on them.

There is still a risk of supply-chain attack. People give LLMs direct access to their entire infrastructure via tools, and never check the code produced. It's not difficult to steer an LLM during training so that they'd output malware only when prompted a certain way, and that wouldn't come up during the initial evaluation. Personally I see no difference between China and America in terms of risks of them embedding "…

> It's not difficult to steer an LLM during training so that they'd output malware only when prompted a certain way

Perhaps, but that's also a good way to lose users+reputation as there's no way to control when said malware is generated. Once the first instance is discovered cybersec researchers will have a field day reproducing it and showing the world.