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I think Anthropic and OpenAI have found product-market fit

simonwillison.net

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

#601

Post by Gigachad »

mirekrusin wrote: post #279
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…

Now try to take back llms from developers and see what happens.

Limiting token quotas would be fine. Encourage developers to use efficient models, plan the work first, and to not burn thousands of GPU hours on waste.

It's much like when developers would waste tons of money on AWS spinning up massive test VMs and leaving them running without care. Until the finance people cracked down on it.

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

#602

Post by Gigachad »

mirekrusin wrote: post #432
bigfishrunning wrote: post #315

Earlier quoted context omitted.

If, by some miracle, all LLMs ceased working right this second, any developer who would no longer be productive should not have been a developer in the first place.

True, but they will not want to work for you anymore, they'll want to work for company that provides it.

I'd happily work for a company that paid me the money they would have spent on LLMs.

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

#603

Post by overgard »

aenis wrote: post #549

The end game here is going back from a model where a bunch of product and tech management people sit in the U.S. or Europe, and try to manage thousands of mediocre talent sitting somewhere far away. The new model is you give those coding tools to good engineers colocated with your product people, and you ship good stuff much faster. If you can achieve such a setup, the token costs can be $50k per seat per month and y…

Good lord, what company would want to spend 600k per employee just to go maybe %20 faster (what the studies seem to show is a realistic estimate for productivity gains),

I'm building a product right now with some AI coding (despite my negative sentiment about AI in general they are useful). I am both the product person and the engineer, and I'm pretty decent at using it, so according to the hype I should be seeing like a 10x speedup. I am not seeing that. It's definitely faster, but there are also days where I'm stuck cleaning up things after going too fast for too long, or periods where I need to put the software in front of people to get real feedback, or even periods where I just need to use it extensively myself to find the pain points and bugs. I just don't see this "running circles" once you get past an MVP and you actually need to build something secure and not embarassingly broken.

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

#604

Post by decidu0us9034 »

jgbuddy wrote: post #219
specproc wrote: post #124

Earlier quoted context omitted.

I'm sorry, what the feck does "value creation" mean here? I live in a place where people are so, insanely squeezed from every angle. Wages are stagnant, prices rocketing. Where is the money to pay for this value going to come from? No one I know feels richer than they did a decade back. I've not been able to meaningfully put up my prices for a decade. People are tired and stressed and scared, particularly scared of a…

A literal example is that I can use AI to file my taxes instead of spending a weekend and hundreds of dollars to have an accountant do it for me. It costs me like $5. that 245$ delta is the value of that output to me, as long as I am confident it is correct.

This also sounds like rich people problems. Vast majority of people with a W-2 take the standard deduction.

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

#605

Post by Gigachad »

PunchyHamster wrote: post #373
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…

That assuming once they start squeezing people won't just go to deepseek or other cheaper competition > That's a _huge_ shift. Most people I know cite +20%-40% velocity with these tools, against the actual work their company cares about doing. +20% speed for +20% spend isn't going to motivate a trillion dollars a year in spending. And most research shows people far over-estimating their own gains. Once companies star…

There's a lot of workslop pumping the numbers. People can generate a 300 page PDF in a tiny fraction of the time it would have taken, but now the report is full of mistakes and fluff, and the stuff that would have been learned and caught in the process of making the report is now not happening.

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

#606

Post by galaxyLogic »

somewhereoutth wrote: post #597
whatshisface wrote: post #173

Earlier quoted context omitted.

Here are a few thoughts: - The publicly available information about how inference costs compare to training costs is conflicted. EEs involved in datacenters talk about power usage spikes during training runs as if they were a major factor in the designs, but academic papers discussing cost-optimal scaling confidently treat inference-time compute as a major factor. - On the side of the balance indicating that training…

Yes the huge discrete stepwise training spend is critical. Maybe investors will realise that "the only winning move is not to play". And so we are left with (as was) frontier models getting more and more out of date as whoever their post bankruptcy custodians are tries to eek pennies on the dollar for inference on their decaying property. Perhaps along with local and/or highly specialized models still feeding on the…

> frontier models getting more and more out of date

Why are they getting out of date? Is it because we have new content from the internet that the older models did not have? Or are we simply trying to increase the size of the training data? In other words not more up-todate in terms of time the content was created vs. wanting to use bigger training-input-sets?

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

#607

Post by fragmede »

mrandish wrote: post #240
jgbuddy wrote: post #57

Earlier quoted context omitted.

You are making the assumption that the models are only used / paid for by 2.5% of the population (your knowledge workers value). There will be new value created by these models which people are happy to pay for which simply did not exist at all before. It is also naive to say that the hyperscalers are going to be expecting a return on this in 5 years, it will be entirely propped up by investments / IPOs as has been t…

> There will be new value created by these models which people are happy to pay for which simply did not exist at all before. True, but I think the GP's point was that what consumers will pay won't be nearly as profitable as what enterprises will pay to increase the output of their developers and knowledge workers. ChatGPT is currently the overwhelming leader in consumer AI usage but only ~5% pay $20/mo. As a recentl…

What are the non-tech people in your life using AI for? $20/month, next to Starbucks and avocado toast, is discretionary. Maybe the novelty will wear off and non-tech consumers will leave it in droves, but everyone declared they'd leave YouTube if they started playing ads, but YouTube doesn't seem to have noticed.

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

#608

Post by wrsh07 »

jobs_throwaway wrote: post #403
doug_durham wrote: post #356

Earlier quoted context omitted.

Open source models that you can run locally are much more than 3 to 6 months behind. 6 months was the November inflection for Claude. No open source model is as good as Claude Opus 4.6.

It depends what you mean by locally. I don't foresee running a model on my laptop anytime soon to power a coding agent. Far more likely is an infra team at my company operating an open source model on cloud infrastructure. When they're already paying $1000 / month / dev, it starts to pencil pretty quickly.

Is there any open model as good as opus 4.6 at any price?

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

#609

Post by overgard »

simonw wrote: post #510
mbesto wrote: post #499

Earlier quoted context omitted.

> My core point is more that April 2026 was the point when Anthropic and OpenAI finally appeared to have figured out a credible business model. How so? What's specifically changed? We still don't know what their unit economics are and everything you've documented is basically speculation at this point.

> What's specifically changed? 1. Both Anthropic and OpenAI significantly increased the prices of their latest models. They're clearly not trying to offer the lowest-price-possible to drum up demand any more. 2. Both Anthropic and OpenAI no longer let enterprise companies buy discounted almost-all-you-can-eat subscriptions. Those big enterprises are now paying full API prices. 3. According to reasonably well-sourced…

I suspect it might end up being a credible business model for whoever buys the IP eventually (Microsoft, Google?), but I think OpenAI and Anthropic are so far in the hole debt wise that simply having a credible business model won't be enough to save them - it needs to be wildly successful.

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

#610

Post by jeremyjh »

doug_durham wrote: post #374
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…

GLM-5.1 isn't just as good. It is no match for Opus running in Claude Code. Please try it yourself. Open source models are about a year behind at least.

This is profoundly misinformed. I use all three of those models regularly and the difference is just not that big anymore. GLM 5.1 is at least as good as Opus 4.5 - when it’s my dime it’s the primary model I use and switch to GPT 5.5 for planning and review but it’s also very capable at those things. If I had to pay API rates for everything there is no question I would only use GLM 5.1 (and Minimax for exploration tasks).

At work I mostly use Claude Code and a bit of Codex; personal projects are OpenCode and honestly I prefer it.

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