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(Author here). Yes I am aware of that and did mention it. However - what I wanted to push back in this article was that claude code was completely unsustainable

(Author here). Yes I am aware of that and did mention it. However - what I wanted to push back in this article was that claude code was completely unsustainable and therefore a flash in the pan and devs aren't at risk (I know you are not saying this). The models as is are still hugely useful, even if no further training was done.

Aurornis 1y ago
> The models as is are still hugely useful, even if no further training was done. Exactly. The parent comment has an incorrect understanding of what unit economics means. The cost of training is not a factor in the marginal cost of each inference or each new customer. It’s unfortunate this comment thread is the highest upvoted right now when it’s based on a basic misunderstanding of unit economics.
- esafak 1y ago
  The marginal cost is not the salient factor when the model has to be frequently retrained at great cost. Even if the marginal cost was driven to zero, would they profit?
  - Aurornis 1y ago
    Unit economics are the salient factor of inference costs, which this article is about.
    - deleted 1y ago
      [deleted]
  - wongarsu 1y ago
    But they don't have to be retained frequently at great cost. Right now they are retrained frequently because everyone is frequently coming out with new models and nobody wants to fall behind. But if investment for AI were to dry up everyone would stop throwing so much money at R&D, and if everyone else isn't investing in new models you don't have to either. The models are powerful as they are, most of the knowledge in them isn't going to rapidly obsolete, and where that is a concern you can paper over it with RAG or MCP servers. If everyone runs out of money for R&D at the same time we could easily cut back to a situation where we get an updated version of the same model every 3 years instead of a bigger/better model twice a year. And whether companies can survive in that scenario depends almost entirely on their unit economics of inference, ignoring current R&D costs
    - churchill 1y ago
      Like we've seen with Karparthy & Murati starting their own labs, it's to be expected that over the next 5 years, hundreds of engineers & researchers at the bleeding edge will quit and start competing products. They'll reliably raise $1b to $5b in weeks, too. And it's logical: for an investor, a startup founded by a Tier 1 researcher will more reliably 10-100x your capital, vs. Anthropic & OpenAI that are already at >$250b+. This talent diffusion guarantees that OpenAI and Anthropic will have to keep sinking in ever more money to stay at the bleeding edge, or upstarts like DeepSeek and incumbents like Meta will simply outspend you/hire away all the Tier 1 talent to upstage you. The only companies that'll reliably print money off AI are TSMC and NVIDIA because they'll get paid either way. They're selling shovels and even if the gold rush ends up being a bust, they'll still do very well.
      - JSR_FDED 1y ago
        True. But at some point the fact that there are many many players in the market will start to diminish the valuation of each of those players, don’t you think? I wonder what that point would be.
    - re-thc 1y ago
      > But if investment for AI were to dry up everyone would stop throwing so much money at R&D, and if everyone else isn't investing in new models you don't have to either IF. If you do stagnate for years someone will eventually decide to invest and beat you. Intel has proven so.
      - simianwords 1y ago
        Yeah so? How does that change anything?
- ninetyninenine 1y ago
  I upvoted it because it aligns most closely with my own perspective. I have a strong dislike for AI and everything associated with it, so my judgment is shaped by that bias. If a post sounds realistic or complex, I have no interest in examining its nuance. I am not concerned with practical reality and prefer to accept it without thinking, so I support ideas that match my personal viewpoint. I don’t understand why people like you have to call this stuff out? Like most of HN thinks the way I do and that’s why the post was upvoted. Why be a contrarian? There’s really no point.
  - SubiculumCode 1y ago
    Is this written by a sarcastic AI?
scrollaway 1y ago
> claude code was completely unsustainable and therefore a flash in the pan and devs aren't at risk How can you possibly say this if you know anything about the evolution of costs in the past year? Inference costs are going down constantly, and as models get better they make less mistakes which means less cycles = less inference to actually subsidize. This is without even looking at potential fundamental improvements in LLMs and AI in general. And with all the trillions in funding going into this sector, you can't possibly think we're anywhere near the technological peak. Speaking as a founder managing multiple companies: Claude Code's value is in the thousands per month /per person/ (with the proper training). This isn't a flash in the pan, this isn't even a "prediction" - the game HAS changed and anyone telling you it hasn't is trying to cover their head with highly volatile sand.
- martinald 1y ago
  I totally agree with you! I have heard others saying this though. But I don't think it's true.
  - scrollaway 1y ago
    Got it — I got confused by your wording in the post but it’s clear now.

Aurornis 1y ago

> The models as is are still hugely useful, even if no further training was done. Exactly. The parent comment has an incorrect understanding of what unit economics means. The cost of training is not a factor in the marginal cost of each inference or each new customer. It’s unfortunate this comment thread is the highest upvoted right now when it’s based on a basic misunderstanding of unit economics.

esafak 1y ago
The marginal cost is not the salient factor when the model has to be frequently retrained at great cost. Even if the marginal cost was driven to zero, would they profit?
- Aurornis 1y ago
  Unit economics are the salient factor of inference costs, which this article is about.
  - deleted 1y ago
    [deleted]
- wongarsu 1y ago
  But they don't have to be retained frequently at great cost. Right now they are retrained frequently because everyone is frequently coming out with new models and nobody wants to fall behind. But if investment for AI were to dry up everyone would stop throwing so much money at R&D, and if everyone else isn't investing in new models you don't have to either. The models are powerful as they are, most of the knowledge in them isn't going to rapidly obsolete, and where that is a concern you can paper over it with RAG or MCP servers. If everyone runs out of money for R&D at the same time we could easily cut back to a situation where we get an updated version of the same model every 3 years instead of a bigger/better model twice a year. And whether companies can survive in that scenario depends almost entirely on their unit economics of inference, ignoring current R&D costs
  - churchill 1y ago
    Like we've seen with Karparthy & Murati starting their own labs, it's to be expected that over the next 5 years, hundreds of engineers & researchers at the bleeding edge will quit and start competing products. They'll reliably raise $1b to $5b in weeks, too. And it's logical: for an investor, a startup founded by a Tier 1 researcher will more reliably 10-100x your capital, vs. Anthropic & OpenAI that are already at >$250b+. This talent diffusion guarantees that OpenAI and Anthropic will have to keep sinking in ever more money to stay at the bleeding edge, or upstarts like DeepSeek and incumbents like Meta will simply outspend you/hire away all the Tier 1 talent to upstage you. The only companies that'll reliably print money off AI are TSMC and NVIDIA because they'll get paid either way. They're selling shovels and even if the gold rush ends up being a bust, they'll still do very well.
    - JSR_FDED 1y ago
      True. But at some point the fact that there are many many players in the market will start to diminish the valuation of each of those players, don’t you think? I wonder what that point would be.
  - re-thc 1y ago
    > But if investment for AI were to dry up everyone would stop throwing so much money at R&D, and if everyone else isn't investing in new models you don't have to either IF. If you do stagnate for years someone will eventually decide to invest and beat you. Intel has proven so.
    - simianwords 1y ago
      Yeah so? How does that change anything?
ninetyninenine 1y ago
I upvoted it because it aligns most closely with my own perspective. I have a strong dislike for AI and everything associated with it, so my judgment is shaped by that bias. If a post sounds realistic or complex, I have no interest in examining its nuance. I am not concerned with practical reality and prefer to accept it without thinking, so I support ideas that match my personal viewpoint. I don’t understand why people like you have to call this stuff out? Like most of HN thinks the way I do and that’s why the post was upvoted. Why be a contrarian? There’s really no point.
- SubiculumCode 1y ago
  Is this written by a sarcastic AI?

scrollaway 1y ago

> claude code was completely unsustainable and therefore a flash in the pan and devs aren't at risk How can you possibly say this if you know anything about the evolution of costs in the past year? Inference costs are going down constantly, and as models get better they make less mistakes which means less cycles = less inference to actually subsidize. This is without even looking at potential fundamental improvements in LLMs and AI in general. And with all the trillions in funding going into this sector, you can't possibly think we're anywhere near the technological peak. Speaking as a founder managing multiple companies: Claude Code's value is in the thousands per month /per person/ (with the proper training). This isn't a flash in the pan, this isn't even a "prediction" - the game HAS changed and anyone telling you it hasn't is trying to cover their head with highly volatile sand.

martinald 1y ago
I totally agree with you! I have heard others saying this though. But I don't think it's true.
- scrollaway 1y ago
  Got it — I got confused by your wording in the post but it’s clear now.