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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

#691

Post by tracerbulletx »

slopinthebag wrote: post #272
simonw wrote: post #4

Earlier quoted context omitted.

I think it is applicable to a much wider range of knowledge work, but it's also harder to apply there. Software development has the huge advantage that mistakes and hallucinations are very easy to spot: the software works or it doesn't. Spotting errors in a research report or legal brief is a whole lot harder! But... non-software professionals spend a huge amount of their time on tasks that can be safely automated -…

> Software development has the huge advantage that mistakes and hallucinations are very easy to spot: the software works or it doesn't. Do we not care about code quality, maintainability, performance, extensibility, or understandability anymore? Honest question, not a gotcha, it's just previously getting software to pass all the tests was a small part of what we would consider "working" or perhaps "good" software. Ma…

What code quality even means is different now, but also LLMs are capable of producing better quality code at scale in my companies experience. We are able to in fact sort of propagate best practices and structure via the llm to all of the teams even when they're working under time pressure.

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

#693

Post by plaidfuji »

aspenmartin wrote: post #236
aerhardt wrote: post #132

I find this analysis confusing. PMF for coding was likely reached some time last year. Profitability, which is different, we don’t know. The article kind of confuses both without making a strong economic case or using numbers in a compelling way. I don’t understand what the Uber case has to do with this either. The Uber COO clearly said that at least in terms of ROI he’s not seeing the results either. My take is the…

What I also find confusing though is that folks seem to ignore trajectory which is maybe the biggest lede to bury. As Simon says, we have had "good enough" coding agents for 6 months, that is a blink of an eye, and at my company my job has now completely changed. It's almost like a dream. And that's just one inflection point. We've had several and there are many more on the horizon. So while I could be convinced that…

There may be additional major leaps forward, and there may not. I kind of struggle to imagine what the next step actually is. Certainly there will be improvements in performance (speed) and cost. But at a point you reach a barrier where the limiting factor is the specificity of the human prompt and our ability to manage all the code we’re generating.

Somewhat oversimplifying; writing software and building apps was a bottleneck - now it is not. What is the next bottleneck that LLMs can solve? Is there one? And is there enough publicly available data to solve it repeatably at scale? Or did we just automate stack overflow searches and now we’re stuck again?

Or is the endgame of this innovation cycle the complete removal of interaction with machines through code? Will we simply interact with machine coworkers purely through natural language? Can an LLM make PowerPoint slides and run a meeting? So far not seeing much progress on that.

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

#694

Post by dogwalker5000 »

Figs wrote: post #189
seanp2k2 wrote: post #141

Earlier quoted context omitted.

>The bottleneck has moved from producing a thing that works to knowing that the thing was the right thing to build I would argue that that's been the case for quite some time before AI. As an example, what innovative amazing world-changing products have Google or Meta launched in the past decade with their very high numbers of very talented and highly-compensated engineers? The issue with most big tech companies are…

> AI for product development and management would be far more impactful than automating rote coding tasks [...] Yeah, if this stuff actually worked that well already, OpenAI et al. would just run AI CEOs and engineers. Why get some other company to pay you at all when you can automate every other company out of existence and take all the money they make? The fact of the matter is that while the tech has some uses, it…

> When that changes, it won't just be engineers losing work; there will be no reason to even have a human CEO any more.

The human race isn’t ready for that world IMHO. The only reason there is a middle class is because people have leverage in the form of their labor. When that becomes worthless … the people who own stuff and make their living from doing so won’t hesitate to get rid of everyone else - whom are now worthless to them.

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

#695

Post by twobitshifter »

whatshisface wrote: post #173
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…

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…

We have GPU costs, power costs, and how many token/s models can generate on those GPUs. It’s possible to figure out the marginal cost based on this. The current estimate is about $0.40 per million tokens for gpt4 equivalent model. Sonnet 4 is $15 per million tokens, so they are charging high margins on inference. The issue is how large of a margin is needed to recover their costs before the GPUs age out, and how high of a margin can be charged before it’s not economically viable.

https://www.gpunex.com/blog/ai-inference-economics-2026/

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

#696

Post by jeremyjh »

clhodapp wrote: post #684
doug_durham wrote: post #374

Earlier quoted context omitted.

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.

In the second half of last year, I found that agentic coding with proprietary models (≈ vibe coding) reached the point where it actually speeds up my ability to deliver useful code at work. Before that, AI-based autocomplete definitely helped, but (despite the claims of the people selling AI coding tools) letting an agent author more than a file or so at a time (often a function or so at a time) required a very intri…

Exactly this. GLM 5.1 is the first open model that I thought "actually worked" for agentic coding, which puts it in the same tier as Opus 4.5 - which was where I flipped.

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

#697

Post by mrandish »

fragmede wrote: post #607
mrandish wrote: post #240

Earlier quoted context omitted.

> 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.

> What are the non-tech people in your life using AI for?

Mostly asking random questions they used to search Google for.

> next to Starbucks and avocado toast, is discretionary.

Sure, but your description implies highly affluent, urban professionals in western nations. I was talking about getting several billion global mass-market consumers to all keep paying ~$20/mo. Mass consumer adoption of mobile phones worldwide is currently >5.8 billion or >70% of humans alive. Only ~50M people are paying $20/mo for an LLM and I suspect many of them are not pure consumers but actually knowledge workers that AI vendors are losing money on and will eventually force into higher tier plans just like the $200/mo developers they're currently losing money on. These heavily subsidized loss-leader offers are all going away post-IPO.

Personally, I know maybe a dozen people who pay $20/mo for an LLM but only two of them are really 'pure consumers' who don't use it for knowledge work. Both of them are multi-millionaires and neither has had a job in ten years. One is retired like me and the other is so wealthy she has a Netjets credit card and has new cars delivered like some people order shoes. Everyone else I know paying $20/mo is a professional who uses the LLM for a lot of office or knowledge work and writes it off as a business expense - examples include a couple of attorneys who are senior partners in a law office they own, a solo architect, and a dentist who owns his own practice.

At $20/mo, AI vendors are probably losing money on most of my professional friends because they use it pretty heavily all day. They're only making money on the two multi-millionaires who both use it so infrequently they could easily be using free chatbots instead but are so rich they could lose $10,000 in their couch cushions and not notice. While they are profitable at $20/mo, they aren't exactly "typical consumers" that there are billion more of. I expect AI vendors will find ways to force my lawyer, architect and dentist friends to switch to higher priced plans soon because they're really knowledge workers abusing a consumer tier plan into unprofitability.

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

#698

Post by dannyw »

sourcecodeplz wrote: post #547
jillesvangurp wrote: post #476

Earlier quoted context omitted.

Most of the corporate world in the EU or North America will be hesitant to rely on Chinese AI providers. There are some very real blockers for that for things like data security, compliance, etc. And recent geopolitics don't help. Legalities aside, you need to look not at the model quality but at the infrastructure needed to scale these models from tens (now) to hundreds (soon) of millions of users. Only a handful of…

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.

It is not a trivial challenge setting up model serving infra for ~1T or larger models, especially in a high reliability environment (e.g. your team is using it for work, or you're using it to power production apps). Sure, there are third party providers, although the quality and reliability of their inference varies.

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

#699

Post by notepad0x90 »

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…

consider cloud spending vs on-prem before the great cloud migrations. people are spending a lot more for cloud services now.

I hear conflicting things about finances, some have a different opinion, that it won't be written down so long as more funding comes in and revenue keeps increasing. it isn't like how you take mortgage or business loan, it isn't even a loan it's an investment funded by loans. So long as the investment is still promising, what are they going to do? destroy its value by calling in trillion dollar loans?

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

#700

Post by rohansood15 »

woah wrote: post #421
prepend wrote: post #14

> $2,180.16 worth of tokens for $200 “Tokens” don’t have an intrisic cost or value. Saying that I used $2,180.16 worth of tokens is like relying on the salesperson to convince me I’m getting a billion dollars worth of pots and pans for $19.99. I think it’s funny how we are throwing critical thinking out the window when it comes to evaluating biased sources of info.

From my back of the envelope analysis for my own projects, paying per token on OpenRouter is competitive if not cheaper than running the same open weight model on a rented GPU. Per-token pricing is in the same ballpark (although more expensive) for closed frontier models and open weight models (cents to dollars per million). To me this says that the pricing is somewhat grounded in reality.

Are you comparing single-user requests or multiple concurrent requests when you say comparable to rented GPU? Most of the cost efficiencies kick in with concurrent/batch requests. A single H100 node can provide like 5k input + 2k output tok/s on a model like Qwen 3.6 35B-A3B with 30+ concurrent requests.
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