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I should? what problems can I solve, that can be only done with an agent? As long as every AI provider is operating at a loss starting a sustainably monetizable
by hoppp 1y ago
I should? what problems can I solve, that can be only done with an agent? As long as every AI provider is operating at a loss starting a sustainably monetizable project doesn't feel that realistic.
- throwaway6977 1y agoYou can be your own AI provider.
- bilbo0s 1y ago>starting a sustainably monetizable project doesn't feel that realistic. and >You can be your own AI provider. Not sure that being your own AI provider is "sustainably monetizable"?
- hoppp 1y agoFor internal software maybe, but for a client facing service the incentives are not right when the norm is to operate at a loss.
- furyofantares 1y ago> As long as every AI provider is operating at a loss None of them are doing that. They need funding because the next model has always been much more expensive to train than the profits of the previous model. And many do offer a lot of free usage which is of course operated at a loss. But I don't think any are operating inference at a loss, I think their margins are actually rather large.
- hoppp 1y agoWhen comparing the cost of an H100 GPU per hour and calculating cost of tokens, it seems the OpenAI offering for the latest model is 5 times cheaper than renting the hardware. OpenAI balance sheet also shows an $11 billion loss . I can't see any profit on anything they create. The product is good but it relies on investors fueling the AI bubble.
- Workaccount2 1y agohttps://martinalderson.com/posts/are-openai-and-anthropic-really-losing-money-on-inference/ https://martinalderson.com/posts/are-openai-and-anthropic-re... All the labs are going hard on training and new GPUs. If we ever level off, they probably will be immensely profitable. Inference is cheap, training is expensive.
- svnt 1y agoTo do this analysis on an hourly retail cost and an open weight model and infer anything about the situation at OpenAI or Anthropic is quite a reach. For one (basic) thing, they buy and own their hardware, and have to size their resources for peak demand. For another, Deepseek R1 does not come close to matching claude performance in many real tasks.
- simonw 1y ago> When comparing the cost of an H100 GPU per hour and calculating cost of tokens, it seems the OpenAI offering for the latest model is 5 times cheaper than renting the hardware. How did you come to that conclusion? That would be a very notable result if it did turn out OpenAI were selling tokens for 5x the cost it took to serve them.
- lmm 1y ago> But I don't think any are operating inference at a loss, I think their margins are actually rather large. Citation needed. I haven't seen any of them claim to have even positive gross margins to shareholders/investors, which surely they would do if they did.
- furyofantares 1y agohttps://officechai.com/ai/each-individual-ai-model-can-already-be-profitable-anthropic-ceo-dario-amodei/ https://officechai.com/ai/each-individual-ai-model-can-alrea...
- svnt 1y ago> “if you consider each model to be a company, the model that was trained in 2023 was profitable. You paid $100 million, and then it made $200 million of revenue. There’s some cost to inference with the model, but let’s just assume, in this cartoonish cartoon example, that even if you add those two up, you’re kind of in a good state. So, if every model was a company, the model, in this example, profitable,” he added. “What’s going on is that while you’re reaping the benefits from one company, you’re founding another company that’s much more expensive and requires much more upfront R&D investment. The way this is going to shake out is that it’s going to keep going up until the numbers get very large, and the models can’t get larger, and then there will be a large, very profitable business. Or at some point, the models will stop getting better, and there will perhaps be some overhang — we spent some money, and we didn’t get anything for it — and then the business returns to whatever scale it’s at,” he said. This take from Amodei is hilarious but explains so much.
- GoatInGrey 1y agoSo AI companies are profitable when you ignore some of the things they have to spend money on to operate? Snark aside, inference is still being done at a loss. Anthropic, the most profitable AI vendor, is operating at a roughly -140% margin. xAI is the worst at somewhere around -3,600% margin.
- fluidcruft 1y agoIf they are not operating inference at a loss and current models remain useful (why would they regress?), they could just stop developing the next model.
- balder1991 1y agoThey could, but that’s a recipe for going out of business in the current environment.
- fluidcruft 1y agoYes, but at the same time it's unlikely for existing models to disappear. You won't get the next model, but there is no choice but to keep inference running to pay off creditors.
- philipwhiuk 1y agoAt minimum they have to incorporate new data every month or the models will fail to know how many Shrek movies there are and become increasingly wrong in a world that isn't static.
- fluidcruft 1y agoThat sort of thing isn't necessary for all use cases. But if you're relying on the system to encode wikipedia or the zeitgeist then sure.
- thunderfork 1y ago
- roadside_picnic 1y agoParent comment never said operating inference at a loss, though it wouldn't surprise me, they just said "operating at a loss" which they most definitely are [0]. However, knowing a few people on teams at inference-only providers, I can promise you some of them absolutely are operating inference at a loss. 0. https://www.theregister.com/2025/10/29/microsoft_earnings_q1_26_openai_loss/ https://www.theregister.com/2025/10/29/microsoft_earnings_q1...
- furyofantares 1y ago> Parent comment never said operating inference at a loss Context. Whether inference is profitable at current prices is what informs how risky it is to build a product that depends on buying inference, which is what the post was about.
- roadside_picnic 1y agoSo you're assuming there's a world where these companies exist solely by providing inference? The first obvious limitation of this would be that all models would be frozen in time. These companies are operating at an insane loss and a major part of that loss is required to continue existing. It's not realistic to imagine that there is an "inference" only future for these large AI companies. And again, there are many inference only startups right now, and I know plenty of them are burning cash providing inference. I've done a lot of work fairly close to the inference layer and getting model serving happening with the requirements for regular business use is fairly tricky business and not as cheap as you seem to think.
- furyofantares 1y ago> So you're assuming there's a world where these companies exist solely by providing inference? Yes, obviously? There is no world where the models and hardware just vanish.
- HDThoreaun 1y ago
- throwaway8xak92 1y ago> None of them are doing that. Can you point us to the data?
- necovek 1y agoSounds quite a bit like pyramid scheme "business model": how is it different? If a company stops training new models until they can fund it out of previous profits, do we only slow down or halt altogether? If they all do?
- welcome_dragon 1y agoIsn't that operating at a loss
- johnfn 1y agoThe post is just about playing around with the tech for fun. Why does monetization come into it? It feels like saying you don't want to use Python because Astral, the company that makes uv, is operating at a loss. What?
- hoppp 1y agoAgents use Apis that I will need to pay for and generally software dev is a job for me that needs to generate income. If the Apis I call are not profitable for the provider then they won't be for me either. This post is a fly.io advertisement
- simonw 1y ago"Agents use Apis that I will need to pay for" Not if you run them against local models, which are free to download and free to run. The Qwen 3 4B models only need a couple of GBs of available RAM and will run happily on CPU as opposed to GPU. Cost isn't a reason not to explore this stuff.
- awayto 1y agoGoogle has what I would call a generous free tier, even including Gemini 2.5 Pro (https://ai.google.dev/gemini-api/docs/rate-limits https://ai.google.dev/gemini-api/docs/rate-limits). Just get an API key from AiStudio. Also very easy to just make a switch in your agent so that if you hit up against a rate limit for one model, re-request the query with the next model. With Pro/Flash/Flash-Lite and their previews, you've got 2500+ free requests per day.
- robot-wrangler 1y ago> Not if you run them against local models, which are free to download and free to run .. run happily on CPU .. Cost isn't a reason not to explore this stuff. Let's be realistic and not over-promise. Conversational slop and coding factorial will work. But the local experience for coding agents, tool-calling, and reasoning is still very bad until/unless you have a pretty expensive workstation. CPU and qwen 4b will be disappointing to even try experiments on. The only useful thing most people can realistically do locally is fuzzy search with simple RAG. Besides factorial, maybe some other stuff that's in the training set, like help with simple shell commands. (Great for people who are new to unix, but won't help the veteran dev who is trying to convince themselves AI is real or figuring out how to get it into their workflows) Anyway, admitting that AI is still very much in a "pay to play" phase is actually ok. More measured stances, fewer reflexive detractors or boosters
- paulcole 1y agoI love how programmers generally tout themselves as these tinkerers who love learning about and exploring technology… until it comes to AI and then it’s like “show me the profitable use case.” Just say you don’t like AI!
- seba_dos1 1y agoIt doesn't have to be profitable. Elegant and clever would suffice.
- ilikehurdles 1y agoI don't think hn is reflective of where programmers are today, culturally. 10 years ago, sure, it probably was.
- khimaros 1y agowhat place is more reflective today?
- whatevertrevor 1y agoI don't know about online forums, but all my IRL friends have a lot more balanced takes on AI than this forum. And honestly it extends beyond this forum to the wider internet. Online, the discourse seems extremely polarized: either it's all a pyramid scheme or stories about how development jobs are already defunct and AI can supervise AI etc.
- hoppp 1y agoYeah but fly.io is a cloud provider doing this advertisement with OpenAI Apis. Both cost money, so if it's not free to operate then the developed project should offset the costs. Its about balance. Really its the AI providers that have been promising unreal gains during this hype period, so people are more profit oriented.
- tptacek 1y agoWhat does "cloud provider" even have to do with this post?
- aidenn0 1y agoShow me where TFA even implied that you should start a sustainably monetizable project with agents?
- simonw 1y ago> what problems can I solve, that can be only done with an agent? The problem that you might not intuitively understand how agents work and what they are and aren't capable of - at least not as well as you would understand it if you spent half an hour building one for yourself.
- veryemartguy 1y agoSeems like it would be a lot easier for everyone if we knew the answer to his/her question.
- lelanthran 1y ago>> what problems can I solve, that can be only done with an agent? > The problem that you might not intuitively understand how agents work and what they are and aren't capable of I don't necessarily agree with the GP here, but I also disagree with this sentiment: I don't need to go through the experience of building a piece of software to understand what the capabilities of that class of software is. Fair enough, with most other things (software or otherwise), they're either deterministic or predictably probabilistic, so simply using it or even just reading how it works is sufficient for me to understand what the capabilities are. With LLMs, the lack of determinism coupled with completely opaque inner-workings is a problem when trying to form an intuition, but that problem is not solved by building an agent.
- DANmode 1y ago[flagged]
- jillesvangurp 1y agoYou are asking the wrong questions. You should be asking what the problems are that you can still solve better and cheaper than an agent? Because anything else, you are probably doing it wrong (the slow and expensive way). That's not long term sustainable. It helps if you know how agents work and as the article argues, there isn't a whole lot to that.