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There’s no way to justify their valuations if they get downgraded to a pair programming tool. They need fully agentic stuff to work and replace human engineers

There’s no way to justify their valuations if they get downgraded to a pair programming tool. They need fully agentic stuff to work and replace human engineers to even come close. Offhand, I’m not even certain whether a model like that could justify the constant retraining we’re doing on the agentic models. It doesn’t make a lot of sense to spend millions or billions on training to reduce hallucinations by 0.3% if your model assumes a human is in the loop to course-correct them.

JumpCrisscross 3mo ago
> no way to justify their valuations if they get downgraded to a pair programming tool I think there is. Pair today doesn’t mean they’re locked into that forever.
- ChrisLTD 3mo ago
  Their valuations don't make sense as just programming tools, period. Forget about if they are still human driven.
  - JumpCrisscross 3mo ago
    > Their valuations don't make sense as just programming tools, period Yup. I think we agree. These valuations aren’t made or unmade by whether their tools are being used as vibe agents or pair programmers.
- 4rf 3mo ago
  you always post about valuations but never share your own. go ahead m8 we are all waiting... the stage is yours. lets see your model.
sanderjd 3mo ago
My two cents is that the way to square this circle is that the valuations should be lower and they should be spending a lot less on constant retraining. Unfortunately (from my perspective) it seems like the US companies are increasingly stuck in their current model. I think it's a competitive disadvantage. But obviously most of the real insiders seem to disagree with me, so I'm probably wrong :)
- wyre 3mo ago
  The insiders disagree because they are benefiting greatly from the insane valuations, right? Chinese models are quickly commodifying frontier inference, the US Gov is preventing domestic SOTA models access to the public and without those models why would consumers still spend $200/month to use the best models? It’s such a mess and isn’t inspiring confidence as a non-investor.
  - sanderjd 3mo ago
    Are they benefiting from the insane valuations though? If the valuations deflate before the insiders are able to exit, I think that would be worse for them than a lower but sustainable valuation. It all comes down to whose prediction of the future is closer to correct. I think the most likely future is commodification of inference and "agent-assisted" rather than "agent-driven" workflows dominating the future of work. But insiders - who both know way more than me, and also have more skin in the game, both for better and worse - seem to really think I'm wrong about that. So I dunno! Could go either way!
    - wyre 3mo ago
      Even if the future is agent-driven workflow, that doesn't stop the commodification of inference. a good agent-driven workflow, in my experience, is a byproduct of the harness and scaffolding around the agent. What insiders are you talking about? They're going to be hot towards the possibilities so they can exit to a massive windfall. I dont know why they would want to be publicly critical of these technologies that could make millions on IPO.
      - sanderjd 3mo ago
        I'm talking about people who work at the frontier labs who talk to the press, and what seems to be the revealed beliefs of those same people from the strategies we see their companies pursuing. My point is that actually it would be worse for these people if the valuations are only high during this period - which will last awhile longer from now! - where their equity is not liquid, but crashes as the market figures out this commoditization thing. But if we're wrong about how that's going to go, then this isn't a concern because there won't be any devaluation. And to me that seems to be what they honestly think is going to happen. And they know more than me (and I think they're a lot smarter than me), so this does temper my confidence in my own predictions.
overgard 3mo ago
That's a really good point. I think if there wasn't the insane amount of money involved and these were treated as tools instead, they would probably be MORE productive. I think a person working hand in hand with an AI instead of delegating is the sweet spot of making things fast while also not losing understanding or control of the system. You are absolutely right that these companies can't justify their valuations if they do that though. I just got a new mac to run models locally, and so far the results have been positive with some small hiccups. I'm thinking the future of this tech will likely be better tooling with better IDE integrations rather than "Claude plz make me a SaaS kthx"
- user43928 3mo ago
  I am thinking the opposite. I've been having great results with handing more and more responsibilities to the agent. Contrary to what some people suggest, I have not hit any maintenance or reliability dead ends. If something breaks, the agent fixes it. If it cannot, I have the agent instrument the code and work through the logs to check hypotheses, until the source of the issue is found. If even that would fail, which did not yet happen, I can still do some old fashioned digging and learning, like I always have. This is for native mobile app development, and the code base is around 100k LOC.
- ah1508 3mo ago
  > while also not losing understanding That's a key point. Keeping knowledge and know how inside the company is strategic. For most people GPS did not result in better sense of direction, spellchecking did not help to write without making mistakes, and delegating translation to deepl does help to be better in a foreign languages. I don't see the gain for an individual, a company, a society if a technology reduces the ability to think, do stuff, understand complex problem, working hard at something. Hiring junior also matters, what is boring for a senior dev is useful for a junior, like the "wax on wax off" in Karatekid. Then when the senior dev retired the junior is not junior anymore and the know how is still here. I want to to transfer my knowledge to a junior, not to anthropic or google or openai. Ideally, working hand in hand with an AI could be like driving a motorcycle vs riding a bicycle. Both are fine, but you go much faster with a motorcycle and you don't lose any ability. But prompting a motorcycle auto-pilot by voice sound a bit stupid and boring. Insane use of energy rarely comes into the equation, which is a bit weird. Personally it is why I am never tempted to use AI. However I see value in AI for finding weakness in a code (inverse of flattery), writing tests with all the edge cases based on specs since tests are often sloppy, asking a fresh view on a very difficult problem. I'd love to hear about the equivalent of move#32 in game 2 (AlphaGo vs Lee Sedol) in a difficult programming task. But I think that massive delegation of code writing is how you lose the knowledge and the know how: what keeps us sharp. Final word: I asked once a review to claude, the codes involved a db transaction. Nothing complicated, Claude said everything was fine. However the transaction isolation level was not set (I did it on purpose, like if I did not know about isolation levels). He did not ask me if it was my intention to keep the default level. I would have preferred a challenging feedback: why did you chose the default isolation level ? Is it on purpose ? Do you know that the default depend on the db ? Do you know about isolation ? Tell me about the business use case and I'll explain which one would be the best.
keeda 3mo ago
Some napkin math -- total global labor compensation is about 50% of the GDP, which puts it in the USD 50 - 60 Trillion range: https://ourworldindata.org/grapher/labor-share-of-gdp https://ourworldindata.org/grapher/labor-share-of-gdp This source claims that knowledge workers alone (probably because they are paid much more) account for 35 - 50 Trillion of that: https://github.com/danielmiessler/Substrate/blob/main/Data/Knowledge-Worker-Global-Salaries/SUMMARY.md https://github.com/danielmiessler/Substrate/blob/main/Data/K... If LLMs can boost their productivity even by an average of 5% (studies from ~2024 put it in the ~30% range depending on task) that is ~1.5 - 2.5T in value annually. Even if the AI industry can capture a fraction of that, that is a huuuge monetization opportunity. Note, at 5% productivity boost, humans are not just in the loop, they are the loop. AGI or large-scale replacement of humans is not even needed, but the financial opportunity is already immense, and it scales with how much human productivity can be improved (i.e. how much work can be offloaded to LLMs.) Now, I don't think AGI will happen soon (or has already happened, depending on how you define it) but I do think humans will be a much smaller part of the loop and large-scale job displacement will happen once companies figure out how to properly use AI. At this point, the financial upside for the AI industry is extremely high but will be limited by the social turmoil that will inevitably ensue (which we're already seeing brewing in the data center backlash.)
- e9 3mo ago
  I want to propose alternative reality where 1.5-2.5T in value doesn't go to a handful of companies. Instead it turns out to be like restaurants where this gets distributed to lots and lots of small, local, mostly interchangeable teams. There will of course be some super star "chefs" leading the industry and setting trends and some "restaurant chain" like big businesses and supply chain for all of this.
  - actionfromafar 3mo ago
    Sysco is pretty big.
  - xxpor 3mo ago
    The world is not zero sum. Value is created, not just preserved. Anthropic and OpenAI creating value does not imply that smaller guys can not also create value.
tskj 3mo ago
Dario has publicly claimed each model has been profitable, even accounting for its training costs; it's just that each new model is exponentially more expensive to train than the last, so the income lags and it looks like the company is losing money overall. Now, we can't know if this is true unfortunately, but it's not directly contradicted by anything that's known publicly at least. I thought it was an interesting way to frame it and makes the whole situation look marginally less bad.
- NorwegianDude 3mo ago
  A common extreme misconception is that inference is expensive and that providers are loosing a lot of money. Inference is extremely lucrative and profitable.
  - drob518 3mo ago
    Inference is the phase where they make money. But the question is whether they can be profitable overall as training continues to balloon.
    - tskj 3mo ago
      I think the case for this is pretty strong actually. Last year my company was maybe willing to pay $100 a month to Anthropic (per developer). Today we're all on the $300 plan without any hesitation. If Fable ever becomes available as the default model, I imagine my company would be willing to pay in the $500-$1000 range per month per developer.
      - drob518 3mo ago
        Okay, but that still has a limit, right? Do training costs have a limit? Everyone is in the frothy stage of this technology wave and they continue to buy more, but training the next model requires exponential increases in model sizes to get the same sorts of model performance increases, which suggests exponential cost increases, too (even ignoring temporary cost factors such as RAM price increases). You say your company will double or triple what they are paying today; how far are they willing to go? At some point they are going to have to cut developers to fund it (e.g., cut half the developers and give the survivors each an AI assistant with $180k in token budget, captured from the salary savings), but that also presupposes the productivity gains are there to support it.
ricardobayes 3mo ago
At some point it's going to plateau, maybe already has. Then they will switch to FPGA/ASIC-based model-specific hardware for lower consumption. I'm pretty sure the "space data centers" won't use GPUs, they are not radiation-tolerant whereas FPGAs can be. https://www.cerebras.ai/blog/gemma-4-on-cerebras-the-fastest-inference-is-now-multimodal https://www.cerebras.ai/blog/gemma-4-on-cerebras-the-fastest...
- quaverquaver 3mo ago
  I would not take "space data centers" as a given! from most to least likely these will be vaporware, vaprorized-ware, rubble-ware, loss leaders.
  - deleted 3mo ago
    [deleted]
EddieRingle 3mo ago
> There’s no way to justify their valuations if they get downgraded to a pair programming tool. Honestly I still don't see how they justify their valuations, period. If anything they're serious liabilities. Open-weight models are improving and reaching "good enough" levels for more and more tasks. They're also known quantities; you know what you're getting with them and don't have to worry about the model silently (or not so silently) being switched out from under you (whether that's because Anthropic/OpenAI decides you're not worthy of their latest and greatest for one reason or another, or they switch you to a quantized model to save on compute, or they simply sunset the specific model you've been relying on). And if the open-weight model doesn't run on your local hardware already, there are any number of hosting providers that will handle that for you (so you're back to just paying for colocation/cloud usage instead of nebulous tokens). Closed models are improving as well, sure, but diminishing returns will eventually kick in (as they already have for various tasks, as I said). So if not their models, where does their value come from? Just simple network effects/lock-in? "Normal" users will drift to other options if they start showing more and more ads, and enterprise customers will surely be looking for opportunities to avoid lock-in and reduce risk. I think the last argument I've heard is that these valuations are basically a bet that Anthropic and/or OpenAI will achieve AGI that can fully replace human labor, so they'll essentially be able to sell that replacement labor to everyone. They haven't managed to pull that off, yet, however. Businesses that have tried to replace humans almost immediately realized either that the AI's capabilities were oversold or that they at least needed a human in the loop still, to some degree. And even if they do achieve AGI, that would surely become an issue of national security (they're already flirting with that today), so who's to say governments won't simply nationalize the best AI labs and either remove them from the economy entirely or perhaps even provide models as a public service to level the playing field? That all sounds like a giant gamble, if anything. And it's incredibly frustrating to watch as someone that's been unemployed for a year because (a) budgets are being burned on tokens and (b) LLM-generated applications are flooding hiring teams and preventing real people from being seen. (Not to mention, as someone that spends a lot of time in gaming circles, the fact that DRAM and flash storage is quickly becoming inaccessible is just an additional frustration that means people can't even find temporary relief in entertainment.) I can only hope this bubble finally implodes before I lose my house.
- 3mo ago

JumpCrisscross 3mo ago

> no way to justify their valuations if they get downgraded to a pair programming tool I think there is. Pair today doesn’t mean they’re locked into that forever.

ChrisLTD 3mo ago
Their valuations don't make sense as just programming tools, period. Forget about if they are still human driven.
- JumpCrisscross 3mo ago
  > Their valuations don't make sense as just programming tools, period Yup. I think we agree. These valuations aren’t made or unmade by whether their tools are being used as vibe agents or pair programmers.
4rf 3mo ago
you always post about valuations but never share your own. go ahead m8 we are all waiting... the stage is yours. lets see your model.

sanderjd 3mo ago

My two cents is that the way to square this circle is that the valuations should be lower and they should be spending a lot less on constant retraining. Unfortunately (from my perspective) it seems like the US companies are increasingly stuck in their current model. I think it's a competitive disadvantage. But obviously most of the real insiders seem to disagree with me, so I'm probably wrong :)

wyre 3mo ago
The insiders disagree because they are benefiting greatly from the insane valuations, right? Chinese models are quickly commodifying frontier inference, the US Gov is preventing domestic SOTA models access to the public and without those models why would consumers still spend $200/month to use the best models? It’s such a mess and isn’t inspiring confidence as a non-investor.
- sanderjd 3mo ago
  Are they benefiting from the insane valuations though? If the valuations deflate before the insiders are able to exit, I think that would be worse for them than a lower but sustainable valuation. It all comes down to whose prediction of the future is closer to correct. I think the most likely future is commodification of inference and "agent-assisted" rather than "agent-driven" workflows dominating the future of work. But insiders - who both know way more than me, and also have more skin in the game, both for better and worse - seem to really think I'm wrong about that. So I dunno! Could go either way!
  - wyre 3mo ago
    Even if the future is agent-driven workflow, that doesn't stop the commodification of inference. a good agent-driven workflow, in my experience, is a byproduct of the harness and scaffolding around the agent. What insiders are you talking about? They're going to be hot towards the possibilities so they can exit to a massive windfall. I dont know why they would want to be publicly critical of these technologies that could make millions on IPO.
    - sanderjd 3mo ago
      I'm talking about people who work at the frontier labs who talk to the press, and what seems to be the revealed beliefs of those same people from the strategies we see their companies pursuing. My point is that actually it would be worse for these people if the valuations are only high during this period - which will last awhile longer from now! - where their equity is not liquid, but crashes as the market figures out this commoditization thing. But if we're wrong about how that's going to go, then this isn't a concern because there won't be any devaluation. And to me that seems to be what they honestly think is going to happen. And they know more than me (and I think they're a lot smarter than me), so this does temper my confidence in my own predictions.

overgard 3mo ago

That's a really good point. I think if there wasn't the insane amount of money involved and these were treated as tools instead, they would probably be MORE productive. I think a person working hand in hand with an AI instead of delegating is the sweet spot of making things fast while also not losing understanding or control of the system. You are absolutely right that these companies can't justify their valuations if they do that though. I just got a new mac to run models locally, and so far the results have been positive with some small hiccups. I'm thinking the future of this tech will likely be better tooling with better IDE integrations rather than "Claude plz make me a SaaS kthx"

user43928 3mo ago
I am thinking the opposite. I've been having great results with handing more and more responsibilities to the agent. Contrary to what some people suggest, I have not hit any maintenance or reliability dead ends. If something breaks, the agent fixes it. If it cannot, I have the agent instrument the code and work through the logs to check hypotheses, until the source of the issue is found. If even that would fail, which did not yet happen, I can still do some old fashioned digging and learning, like I always have. This is for native mobile app development, and the code base is around 100k LOC.
ah1508 3mo ago
> while also not losing understanding That's a key point. Keeping knowledge and know how inside the company is strategic. For most people GPS did not result in better sense of direction, spellchecking did not help to write without making mistakes, and delegating translation to deepl does help to be better in a foreign languages. I don't see the gain for an individual, a company, a society if a technology reduces the ability to think, do stuff, understand complex problem, working hard at something. Hiring junior also matters, what is boring for a senior dev is useful for a junior, like the "wax on wax off" in Karatekid. Then when the senior dev retired the junior is not junior anymore and the know how is still here. I want to to transfer my knowledge to a junior, not to anthropic or google or openai. Ideally, working hand in hand with an AI could be like driving a motorcycle vs riding a bicycle. Both are fine, but you go much faster with a motorcycle and you don't lose any ability. But prompting a motorcycle auto-pilot by voice sound a bit stupid and boring. Insane use of energy rarely comes into the equation, which is a bit weird. Personally it is why I am never tempted to use AI. However I see value in AI for finding weakness in a code (inverse of flattery), writing tests with all the edge cases based on specs since tests are often sloppy, asking a fresh view on a very difficult problem. I'd love to hear about the equivalent of move#32 in game 2 (AlphaGo vs Lee Sedol) in a difficult programming task. But I think that massive delegation of code writing is how you lose the knowledge and the know how: what keeps us sharp. Final word: I asked once a review to claude, the codes involved a db transaction. Nothing complicated, Claude said everything was fine. However the transaction isolation level was not set (I did it on purpose, like if I did not know about isolation levels). He did not ask me if it was my intention to keep the default level. I would have preferred a challenging feedback: why did you chose the default isolation level ? Is it on purpose ? Do you know that the default depend on the db ? Do you know about isolation ? Tell me about the business use case and I'll explain which one would be the best.

keeda 3mo ago

Some napkin math -- total global labor compensation is about 50% of the GDP, which puts it in the USD 50 - 60 Trillion range: https://ourworldindata.org/grapher/labor-share-of-gdp https://ourworldindata.org/grapher/labor-share-of-gdp This source claims that knowledge workers alone (probably because they are paid much more) account for 35 - 50 Trillion of that: https://github.com/danielmiessler/Substrate/blob/main/Data/Knowledge-Worker-Global-Salaries/SUMMARY.md https://github.com/danielmiessler/Substrate/blob/main/Data/K... If LLMs can boost their productivity even by an average of 5% (studies from ~2024 put it in the ~30% range depending on task) that is ~1.5 - 2.5T in value annually. Even if the AI industry can capture a fraction of that, that is a huuuge monetization opportunity. Note, at 5% productivity boost, humans are not just in the loop, they are the loop. AGI or large-scale replacement of humans is not even needed, but the financial opportunity is already immense, and it scales with how much human productivity can be improved (i.e. how much work can be offloaded to LLMs.) Now, I don't think AGI will happen soon (or has already happened, depending on how you define it) but I do think humans will be a much smaller part of the loop and large-scale job displacement will happen once companies figure out how to properly use AI. At this point, the financial upside for the AI industry is extremely high but will be limited by the social turmoil that will inevitably ensue (which we're already seeing brewing in the data center backlash.)

e9 3mo ago
I want to propose alternative reality where 1.5-2.5T in value doesn't go to a handful of companies. Instead it turns out to be like restaurants where this gets distributed to lots and lots of small, local, mostly interchangeable teams. There will of course be some super star "chefs" leading the industry and setting trends and some "restaurant chain" like big businesses and supply chain for all of this.
- actionfromafar 3mo ago
  Sysco is pretty big.
- xxpor 3mo ago
  The world is not zero sum. Value is created, not just preserved. Anthropic and OpenAI creating value does not imply that smaller guys can not also create value.

tskj 3mo ago

Dario has publicly claimed each model has been profitable, even accounting for its training costs; it's just that each new model is exponentially more expensive to train than the last, so the income lags and it looks like the company is losing money overall. Now, we can't know if this is true unfortunately, but it's not directly contradicted by anything that's known publicly at least. I thought it was an interesting way to frame it and makes the whole situation look marginally less bad.

NorwegianDude 3mo ago
A common extreme misconception is that inference is expensive and that providers are loosing a lot of money. Inference is extremely lucrative and profitable.
- drob518 3mo ago
  Inference is the phase where they make money. But the question is whether they can be profitable overall as training continues to balloon.
  - tskj 3mo ago
    I think the case for this is pretty strong actually. Last year my company was maybe willing to pay $100 a month to Anthropic (per developer). Today we're all on the $300 plan without any hesitation. If Fable ever becomes available as the default model, I imagine my company would be willing to pay in the $500-$1000 range per month per developer.
    - drob518 3mo ago
      Okay, but that still has a limit, right? Do training costs have a limit? Everyone is in the frothy stage of this technology wave and they continue to buy more, but training the next model requires exponential increases in model sizes to get the same sorts of model performance increases, which suggests exponential cost increases, too (even ignoring temporary cost factors such as RAM price increases). You say your company will double or triple what they are paying today; how far are they willing to go? At some point they are going to have to cut developers to fund it (e.g., cut half the developers and give the survivors each an AI assistant with $180k in token budget, captured from the salary savings), but that also presupposes the productivity gains are there to support it.

ricardobayes 3mo ago

At some point it's going to plateau, maybe already has. Then they will switch to FPGA/ASIC-based model-specific hardware for lower consumption. I'm pretty sure the "space data centers" won't use GPUs, they are not radiation-tolerant whereas FPGAs can be. https://www.cerebras.ai/blog/gemma-4-on-cerebras-the-fastest-inference-is-now-multimodal https://www.cerebras.ai/blog/gemma-4-on-cerebras-the-fastest...

quaverquaver 3mo ago
I would not take "space data centers" as a given! from most to least likely these will be vaporware, vaprorized-ware, rubble-ware, loss leaders.
- deleted 3mo ago
  [deleted]

EddieRingle 3mo ago

> There’s no way to justify their valuations if they get downgraded to a pair programming tool. Honestly I still don't see how they justify their valuations, period. If anything they're serious liabilities. Open-weight models are improving and reaching "good enough" levels for more and more tasks. They're also known quantities; you know what you're getting with them and don't have to worry about the model silently (or not so silently) being switched out from under you (whether that's because Anthropic/OpenAI decides you're not worthy of their latest and greatest for one reason or another, or they switch you to a quantized model to save on compute, or they simply sunset the specific model you've been relying on). And if the open-weight model doesn't run on your local hardware already, there are any number of hosting providers that will handle that for you (so you're back to just paying for colocation/cloud usage instead of nebulous tokens). Closed models are improving as well, sure, but diminishing returns will eventually kick in (as they already have for various tasks, as I said). So if not their models, where does their value come from? Just simple network effects/lock-in? "Normal" users will drift to other options if they start showing more and more ads, and enterprise customers will surely be looking for opportunities to avoid lock-in and reduce risk. I think the last argument I've heard is that these valuations are basically a bet that Anthropic and/or OpenAI will achieve AGI that can fully replace human labor, so they'll essentially be able to sell that replacement labor to everyone. They haven't managed to pull that off, yet, however. Businesses that have tried to replace humans almost immediately realized either that the AI's capabilities were oversold or that they at least needed a human in the loop still, to some degree. And even if they do achieve AGI, that would surely become an issue of national security (they're already flirting with that today), so who's to say governments won't simply nationalize the best AI labs and either remove them from the economy entirely or perhaps even provide models as a public service to level the playing field? That all sounds like a giant gamble, if anything. And it's incredibly frustrating to watch as someone that's been unemployed for a year because (a) budgets are being burned on tokens and (b) LLM-generated applications are flooding hiring teams and preventing real people from being seen. (Not to mention, as someone that spends a lot of time in gaming circles, the fact that DRAM and flash storage is quickly becoming inaccessible is just an additional frustration that means people can't even find temporary relief in entertainment.) I can only hope this bubble finally implodes before I lose my house.

3mo ago