> If token costs converge toward zero for most AI use cases...
In the real world, token costs seem to be going up, as early stage pricing at a loss gives way to pricing that generates revenue.
Compute costs might go down a little over the next five years, but there's nothing coming along in hardware that leads to huge reductions in price. NVidia says don't expect better price/performance before 2030.
The models keep getting bigger, and people put loops around them which iterate, burning tokens.
I've switched to non-SOTA models, which deliver comparable value at a fraction of the cost. A full day of coding with Deepseek is approx $1 in tokens, and at least for my use cases the quality is equivalent to Claude.
Not who you asked, but if you're looking for a rec, I've been using GLM and Deepseek models through Deepinfra because the prices are decent for US-based deployments and there's acceptable throughput and policy/terms. I'd love to find another that lowers prices over time when they roll out e.g. multi-token prediction instead of just taking a larger margin, but I don't know of any today.
Same here - curious which deepseek model and what op was doing.
I suspect it might be a question of conversational loop vs agentic dev - the former uses much less tokens than letting an autonomous agent churn away on your codebase.
I don't expect any of the third party openrouter providers sell tokens at a loss. Agreed that increasing model size could drive token prices up however so far there's been a very strong trend in the opposite direction with smaller models becoming increasingly capable thanks to advances in theory and implementation.
Edit: A glaring omission on my part there is that growth of aggregate industry demand for tokens has the potential to outpace increases in supply provided by new datacenters buildouts. So tokens certainly could go up depending on how things play out.
The following two things can be true at the same time:
- Frontier state-of-the-art performance keeps getting more expensive (and better).
- Any fixed performance level is becoming cheaper.
(And a third: if you still want to see improvements instead of a fixed level, you can trail the frontier a bit and still see price some reductions over time.)
That chart is a blended metric though. I don't think anyone is using the latest and greatest frontier models (which seem to get more expensive with each generation) for mundane tasks that are solvable with existing models. It seems unreasonable to average deepseek v4 flash and fable pricing.
Article is authored by a private credit firm who assigned absurd valuations to AI infra (see below as an even super recent example) - what is their intention by writing this (is it due to the AI fear narratives around software investments they also hold that drive ppl to withdraw their holdings in Apollo?)
One thing I can't square: if the cost to build an application goes to zero, we should see a proliferation of apps, especially from the AI labs.
The fact that we aren't seeing an app explosion (I think) is evidence that building applications people will pay for is significantly more complex than just prompting claude/codex/etc
I am absolutely seeing an explosion in apps. The reason you might not see them is because the app explosion is entirely custom and in house.
I talked with a friend last week, who has never coded before in his life, who built an absolutely incredible fit-for-purpose app for his own job. He gave me a demo and it blew my mind. It will never go beyond his walls, and he will never buy SaaS that only kinda fits what he needs.
I see things like this happening. The proliferation isn't public because why sell it? Just build the thing to make your domain job easier and save thousands per month cancelling SaaS subs.
The ROI of AI is starting to show, but it isn't in terms of growth or selling new things - it's reducing spend across the board on software and tools.
From their profile, this person makes a living selling AI programming products, by the way. Who could have guessed. There's a pattern to be noticed, even.
Whether that person is talking their book or not, there absolutely has been an app explosion. Github & the app stores have all reported as much over the last year.
I also have repeatedly experienced the phenomenon of nontechnical people having built custom software to run their businesses. A lawyer friend was first, sending me a link to his GitHub(!), where he has built a custom client intake/practice-management application to work as the firm works. He's not the only non-technical lawyer I know who has shared vibe coded apps with me.
I personally build many, many single-use apps than I ever would have before. Gnarly debugging sessions can be greatly simplified by inserting a custom piece of disposable tooling/etc. I am not a Mac programmer, but I now have custom Mac apps to solve problems that only I want solved. Do these count?
Honestly, I would be a little surprised if anyone posting on HN did not have some personal exposure to the explosion of apps.
On the Home Assistant and Jellyfin reddits you'll see tons of vibecoded dashboards and plugins people are putting together - and those are just the ones people are sharing.
I personally have been building a bunch of little personal apps for my home that aren't worth the effort of sharing - like a customized dashboard of the Trimet buses closest to my house. The cost to build the initial good-enough version was literally 5 minutes plus another 10 to test and deploy.
I assume the new wave of apps are going to be maintained by LLMs. Maybe one day the LLMs are going to complain about the quality of the code written by previous inferior LLMs?
Yes. Though with Excel for most business users the choice was between
- lobby the IT department for at least a quarter, then wait at least one quarter, and at the end you get a buggy implementation of your idea that doesn't quite work
- or: spend a weekend hacking together a quick and ugly, buggy spreadsheet prototype of your idea that doesn't quite work.
Who’s “this person”…me? I don’t make a living selling AI programming products. I make a living building knowledge systems, mostly around search engines and data wrangling.
Probably net positive. But just like spreadsheets, it’s likely that having tools created by a layperson that does not properly secure or test the system is probably going to occur, cause some unfortunate issues, and steal the headlines. Similar to when an excel formula error results in a flash crash of financial markets and such. It’s huge and sucks but there’s also countless value being added daily all around the world with little fan fare.
I made an app for myself and the local MTB community for keeping track of rain and soil moisture for nearby trails so it's easier to decide when a trail will likely be open. Much more reliable than waiting for the official (volunteer led) organization to update the status. I never would have made it without an LLM to speed things along.
A good friend of mine helped his mom keep track of Meals On Wheels (or a similar volunteer org) orders, deliveries, cancellations, etc. They were managing all of this via paper before.
I compiled a list of online recipes. Then I had an LLM typeset them for me into a printable PDF and build a companion website with links to the original recipes and complete ingredient lists for shipping. had the LLM encode links for the companion site into QR codes so the printed copy of the cookbook would bring me immediately to a shopping list, making trying a new recipe soooo much less daunting.
There are so many little things like this that you can make that just take too much effort to justify otherwise. I have other ideas for personal projects that I'll probably get to some day.
Anecdotally, Claude Code has prompted an explosion of open source projects and prototypes from self-starters. A lot of these are just hobby projects, but some of them genuinely fill a niche that was previously too complicated or unviable to develop otherwise.
Some of them have half baked financial models, but nobody will invest dollars backing a SaaS offering that could easily be replicated, or that could be made redundant tomorrow.
> [...] but nobody will invest dollars backing a SaaS offering that could easily be replicated, or that could be made redundant tomorrow.
Matt Levine wrote in his newsletter Money Stuff of some investment fund that has their employees vibecode replacements for software of potential investment targets. I guess the theory is exactly what you say: if the internal employees can replace the target's software in a few hours, that's a big signal on whether to invest or not.
(I wouldn't quite say you shouldn't invest at all; but you have to argue that the moat is in eg the sales process or the existing customer base or network effects etc. Even before AI, people famously build Twitter clones over the weekend for fun.)
For a long time nobody knew how to monetize OSS outside of a few Linux vendors.
There's a crapload of new repos and Github and similar things. And a lot of it is "hobby utility" stuff like you'd find everywhere pre-mobile/pre-app-store but kinda dried up a bit with the browserfication+phone-ificiation of everything. Everything had to turn into an app + an online service.
Now, like OSS, freeware, and even most shareware in the 90s, most of these new projects have no path to VC-level interest.
The whole "basic business or business-process BUT ON THE INTERNET with a dash of social/web-2.0/personalization/crypto/fad-of-the-year" that recent VC firms have been pushing for the last 15+ years may be numbered.
But it's also unlikely that growing companies with big ambitions will want to base their business on vibe-coded free software for too long. It opens up too many unknowns/risks ("oh no, the disgruntled employee leveraged a misconfiguration in our in-house accounts payable system!") There will be a new middle ground model to be found.
> But it's also unlikely that growing companies with big ambitions will want to base their business on vibe-coded free software for too long. It opens up too many unknowns/risks ("oh no, the disgruntled employee leveraged a misconfiguration in our in-house accounts payable system!") There will be a new middle ground model to be found.
I agree _iff_ vibecoding stayed roughly at today's level of competence.
If the models keep improving, perhaps you'll just tell them 'eh, and make sure to close all the security holes' and they'll do so.
There are a lot of specialty/niche apps showing up which are vibe coded --- tons of 3D CAD apps which are a variation/extension of OpenSCAD, a fair number of tools which work with G-code in various ways, &c.
On a commercial support forum I moderate we had to ban software announcements there were so many.
I was idly browsing F-Droid yesterday and found a Claude coded B-REP CAD program built on OpenCASCADE, all touch friendly and everything. Definitely something happening.
I think a) the labs are releasing very fast and b) why would they implement the long tail of app features when they can effectively sell tokens to every user to write their own version of the app, which is what is currently happening?
Because, as the gp pointed out, if the cost is least to the labs, then why not reap the benefits too?
Hypothetical. Assume you can in fact point agents at a tool and say "replicate it. Make no mistakes". You then have software being instantly copy-able.
Assume these agents can then be pointed to a customer feedback board in perpetuity and they autonomously upgrade the software over time. They analyze usage patterns and behave like PMs figuring out what to prune and what to build. Then the maintenance part of the stack also goes to zero.
Over time, the highest margin competitiveness will go to the distributor of the tokens. Aka the AI model makers.
In a world like that (which the frontier labs claim is within a year or two of happening) it feels like it's only a matter of time before they opt to own the entire stack down to the consumer apps. Kind of like Amazon deciding they want to knock off products doing well and then favour their own product over the original seller.
My guess is that if the capability arrives the only reason the frontier labs don't move to own the entire stack immediately is because of optics. Boil the frog instead.
There is more to selling software than writing it. You have market, support, and sell. Do you think their resources are well spent doing that across the gamut of software? Of course not; companies specialize.
Isn't the promise that LLM can do all this better than any human? Or at least in few short months? Surely marketing, support and selling is just case of right prompt?
I think there is an explosion of new apps, the problem is still distribution in marketing.
If I develop a new vibe coded app, it will still take some time for it to be known. And also get good.
Also, what another commenter said that most of new apps are in-house, fully agree with that.
IMO this is one of the endgame for big ai LABS, they will allow and subsidize users to test and validate on their behalf and once there is a PMF they will step in.
Speaking from my side of the industry (the gaming industry), we are seeing a massive increase in the number of games people are making. Above the growth that was already there.
The distinction is that the games being made are garbage, and I mean worse than shovelware garbage. It's actively made things much harder as someone that fancies himself an indie game curator because you gotta dig through more and more games to find stuff with actual people behind it.
I’ve seen a ton of new open source slop programs. Every day there’s so many “announcing my cool new app” posts. I don’t remember the rate being this high before.
Maybe there's an argument that a lack of rising profit margins in non-tech companies is a bad sign for AI, but this article doesn't make it. Why can't we have a red-queen's race where non-tech companies are implementing AI, but it's not increasing the total profits of those sectors, just meeting rising customer demands/fighting over the share of existing profits? (Never mind that if you look at that chart, profit margins aren't static to begin with, so you can't isolate AI impact from normal fluctuation).
Now, on the first order point, I agree that non-tech companies seem to be taking longer to see results from AI, even if the argument was bad.
I work on SaaS for the logistics space, and I feel like prior to the end of 2025, almost all the discussion about AI for logistics was vaporware, starting this year, companies are actually trying to deploy agents, and we'll start finding out what the ROI is later this year or next.
> Why can't we have a red-queen's race where non-tech companies are implementing AI, but it's not increasing the total profits of those sectors, just meeting rising customer demands/fighting over the share of existing profits?
But then if this happens - all of the stock market has risen in the promise of AI. If AI eats profits instead of grows them, then the economy shrinks right? So maybe that’s worse? That there is no productivity increase?
There is no reason to believe the ROI runway is not long inside the tech sector either. I mean, you cannot base that on claims made by the AI sub-sector of the tech sector; of course they are going to claim nothing other than that eating their dogfood is great ROI with a short runway.
If you need immediate ROI (say, because you just invested a trillion dollars into datacenters) you may be out of luck.
And I don't think this is unusual. It took decades for previous technologies to be fully integrated into existing businesses. In the 80s you could see the IT revolution everywhere... except the productivity statistics, which didn't catch up until the 90s.
LLMs are still very new and have significant limitations (like prompt injection and high token costs) that are very likely solveable but will take time.
This is more marketing hype than substance. Amazon isn’t “building” a team, it’s broadly just taking existing people and now calling them “forward deployment engineering teams.”
Also, adoption isn’t lacking because of lack of awareness. Adoption isn’t happening because the math doesn’t add up and the ROI isn’t there. Consulting pixie dust can’t fix that.
Ah man it’s gonna be hilarious when this comes crashing down -and it will. It’s pretty obvious ‘demand is infinite’ was always a lie - demand is infinite only when price approaches zero lol! Prices are going further away from zero not closer
Feels like a new consulting wave which is implementation-led by AI vendors taking a large share of the services layer. The existing consulting companies (big 4 etc) will have to shift to niche advisory or heavy channel partnerships with way fewer consultants.
"The first chart below shows that so far there are no signs of profit margins rising outside the tech sector. This is ultimately what we are waiting for, because the value of AI companies today rests entirely on the promise that margins in the S&P 493 will eventually climb."
This is absolutely not necessary. The bull case is that AI will bring great efficiencies. The surplus profits from those efficiencies could easily be competed away by firms who have adopted AI. Those firms who do not adopt AI will have their margis crushed.
So then your argument would be that we could see a bifurcation in the SP493 where those who adopt AI see increasing margins and those who do not have their margins crushed. What's funny is that in that scenario, the aggregate market might look zero sum.
Well those efficiency gains have to show up somewhere. It would imply that consumers / customers of these companies are receiving cheaper or higher value services / goods.
Thats at odds with current inflation trends to say the least.
Even aside from inflation, the prospect of efficiency-borne gains meaningfully benefiting the consumer rather than fattening corporate profit margins, frankly, seems like magical thinking. I’ve seen no evidence that our current corporate culture is capable of it (for any longer than it takes to dominate some market.)
What does corporate culture have to do with any of it? The surplus goes to the consumer not because of any benevolent corporate culture, but because of competition.
And (most) efficiency gains have benefited customers in the past.
Just check eg how much you are paying for excellent lighting of your house today vs 200 years ago.
Labor, obviously. That's where all the money in a business goes: paying pesky human employees.
If your employees can suddenly magically do more work with the same pay, that's free money (for you). You can pay fewer employees, or pay them less by threatening to replace them with the magic robot.
The magical thinking version of this is that your productivity gains magically translate into more customers and more sales for the same input cost and labor. The free money is really free because you're a magical special snowflake company and every consumer will want your brand of magic machine outputs and not the other guy's. Where does all this money come from? Do those extra customers even exist? Who cares!
Pepsi starts using AI in some magical way that allows them to increase their margins. This allows them to reduce prices while increasing profits. Price-sensitive customers switch from Coca Cola products to Pepsi products. Coca Cola loses some market share, reducing economies of scale, and reducing margins, thus reducing profits. As the cycle repeats, Pepsi moves to dominate the market, and Coca Cola is slowly squeezed down.
In a duopoly, probably yes. However in a more competitive environment where several incumbents have achieved a given optimization a race to the bottom is likely to occur because it only takes one of them preferring to increase their relative market share to kick the process off.
Really depends on the concrete numbers and the projections. You could be right, I could be right, I am only saying what I've witnessed historically in general. Greed trumps a lot of other fairly rational courses of action.
Yes: historically this is not what I have observed businesses doing. They'd fight tooth and nail to reduce expenses for the fatter profits; cost savings are seldom if ever passed to consumers.
Obviously they don't voluntarily pass on cost savings to customers. That's why competition is there for.
Btw, check how much RAM costs today per byte than eg 20 years ago. Even including today's AI driven price increases. Or check how much it costs to keep your house light up nice and bright compared to 50 years ago.
How much does a car cost now? Surely with automation, robots and general efficiency gains every where in the production chain they should be lot cheaper than they used to be.
The companies seem to rarely keep the cheaper models around too for something. Surely they could sell them for right price.
I don't understand why anyone insists that this needs more time. None of what we've seen in the past few years is new tech. It's more money and hardware thrown at the problem than ever before for diminishing returns.
The market has clearly spoken. Knowing what you're doing is much more valuable than just the doing. That still requires humans. This AI winter has already begun.
Everyone's arguing the macro (do the margins show up), but the reason non-tech ROI is slow is pretty concrete once you've been close to one of these projects: most of what I've seen bolts a chatbot onto the existing system and stops there, and a chatbot on top of rigid software inherits all the rigidity plus a new way to be wrong.
The value shows up only after the boring part: wiring the model to the real data with real access control, and moving anything that has to be exact or repeatable out of the model and into deterministic tools it calls. That's an integration-and-permissions project, not an "adopt AI" project. It's slow, it's unglamorous, nobody demos it, so pilots skip straight to the chatbot and then report thin ROI. Tech companies see returns faster partly because their data and tooling are already reachable by the thing.
So I'd read the flat margins as "the actual work hasn't been done yet," not "there's no value there." The runway being long and the technology being real aren't in tension. The gap is that the useful version looks like plumbing, and plumbing doesn't get funded on the same timeline as a demo.
The slower adoption in non-tech sectors isn't just cultural lag - the integration surface is genuinely harder. Legacy ERP systems, compliance review cycles for what data the model can touch, and change management overhead all front-load costs before any efficiency shows up in margins.
I've seen this in payment/API systems: the actual model integration takes weeks, but getting legal and security sign-off on the data pipeline takes months. Non-tech companies face the same pattern but with less internal tooling to manage it.
The margin signal might also be appearing at the wrong level. Gains in these sectors often show up first as headcount flatness or throughput improvements before they hit EBITDA. Measuring at the P&L level on a 2-year horizon is probably too early and too coarse - the operational metrics are moving, the accounting just hasn't caught up yet.
> If token costs converge toward zero for most AI use cases...
In the real world, token costs seem to be going up, as early stage pricing at a loss gives way to pricing that generates revenue.
Compute costs might go down a little over the next five years, but there's nothing coming along in hardware that leads to huge reductions in price. NVidia says don't expect better price/performance before 2030.
The models keep getting bigger, and people put loops around them which iterate, burning tokens.
Where is this cost reduction coming from?
Don't index on tokens. Costs for useful unit of work had gone down in my experience, and that's what actually matters.
Counting tokens is like counting lines of code.
I've switched to non-SOTA models, which deliver comparable value at a fraction of the cost. A full day of coding with Deepseek is approx $1 in tokens, and at least for my use cases the quality is equivalent to Claude.
If you don't mind sharing... what's your preferred vendor for Deepseek
Not who you asked, but if you're looking for a rec, I've been using GLM and Deepseek models through Deepinfra because the prices are decent for US-based deployments and there's acceptable throughput and policy/terms. I'd love to find another that lowers prices over time when they roll out e.g. multi-token prediction instead of just taking a larger margin, but I don't know of any today.
Hm. I must be holding it wrong. I hit $20 easily in 5 hours with deepseek in opencode.
Same here - curious which deepseek model and what op was doing.
I suspect it might be a question of conversational loop vs agentic dev - the former uses much less tokens than letting an autonomous agent churn away on your codebase.
Do a through audit of every single token you're sending and receiving. Some harnesses include things you didn't expect.
I don't expect any of the third party openrouter providers sell tokens at a loss. Agreed that increasing model size could drive token prices up however so far there's been a very strong trend in the opposite direction with smaller models becoming increasingly capable thanks to advances in theory and implementation.
Edit: A glaring omission on my part there is that growth of aggregate industry demand for tokens has the potential to outpace increases in supply provided by new datacenters buildouts. So tokens certainly could go up depending on how things play out.
The following two things can be true at the same time:
- Frontier state-of-the-art performance keeps getting more expensive (and better).
- Any fixed performance level is becoming cheaper.
(And a third: if you still want to see improvements instead of a fixed level, you can trail the frontier a bit and still see price some reductions over time.)
This website https://tokenpriceindex.com/ tracks Token Cost.
You are right - tokens are going up currently.
That chart is a blended metric though. I don't think anyone is using the latest and greatest frontier models (which seem to get more expensive with each generation) for mundane tasks that are solvable with existing models. It seems unreasonable to average deepseek v4 flash and fable pricing.
Article is authored by a private credit firm who assigned absurd valuations to AI infra (see below as an even super recent example) - what is their intention by writing this (is it due to the AI fear narratives around software investments they also hold that drive ppl to withdraw their holdings in Apollo?)
From last month: https://peinsights.substack.com/p/apollo-and-blackstone-clos...
One thing I can't square: if the cost to build an application goes to zero, we should see a proliferation of apps, especially from the AI labs.
The fact that we aren't seeing an app explosion (I think) is evidence that building applications people will pay for is significantly more complex than just prompting claude/codex/etc
I am absolutely seeing an explosion in apps. The reason you might not see them is because the app explosion is entirely custom and in house.
I talked with a friend last week, who has never coded before in his life, who built an absolutely incredible fit-for-purpose app for his own job. He gave me a demo and it blew my mind. It will never go beyond his walls, and he will never buy SaaS that only kinda fits what he needs.
I see things like this happening. The proliferation isn't public because why sell it? Just build the thing to make your domain job easier and save thousands per month cancelling SaaS subs.
The ROI of AI is starting to show, but it isn't in terms of growth or selling new things - it's reducing spend across the board on software and tools.
From their profile, this person makes a living selling AI programming products, by the way. Who could have guessed. There's a pattern to be noticed, even.
Whether that person is talking their book or not, there absolutely has been an app explosion. Github & the app stores have all reported as much over the last year.
I also have repeatedly experienced the phenomenon of nontechnical people having built custom software to run their businesses. A lawyer friend was first, sending me a link to his GitHub(!), where he has built a custom client intake/practice-management application to work as the firm works. He's not the only non-technical lawyer I know who has shared vibe coded apps with me.
I personally build many, many single-use apps than I ever would have before. Gnarly debugging sessions can be greatly simplified by inserting a custom piece of disposable tooling/etc. I am not a Mac programmer, but I now have custom Mac apps to solve problems that only I want solved. Do these count?
Honestly, I would be a little surprised if anyone posting on HN did not have some personal exposure to the explosion of apps.
On the Home Assistant and Jellyfin reddits you'll see tons of vibecoded dashboards and plugins people are putting together - and those are just the ones people are sharing.
I personally have been building a bunch of little personal apps for my home that aren't worth the effort of sharing - like a customized dashboard of the Trimet buses closest to my house. The cost to build the initial good-enough version was literally 5 minutes plus another 10 to test and deploy.
The closest parallel in history I can think of is the proliferation of spreadsheets in the 1980s.
Yeah, this feels like the right comparison. AI, like Excel makes it much easier for people to build useful tools.
And like Excel, software people are gonna end up complaining about the quality and having to maintain these applications.
I assume the new wave of apps are going to be maintained by LLMs. Maybe one day the LLMs are going to complain about the quality of the code written by previous inferior LLMs?
Yes. Though with Excel for most business users the choice was between
- lobby the IT department for at least a quarter, then wait at least one quarter, and at the end you get a buggy implementation of your idea that doesn't quite work
- or: spend a weekend hacking together a quick and ugly, buggy spreadsheet prototype of your idea that doesn't quite work.
> - or: spend a weekend hacking together a quick and ugly, buggy spreadsheet prototype of your idea that doesn't quite work.
I mean, based on my own experience with AI tools, this feels like the standard output.
Who’s “this person”…me? I don’t make a living selling AI programming products. I make a living building knowledge systems, mostly around search engines and data wrangling.
I’m seeing this too. I compare it to spreadsheets in terms of getting broad application building tools to the layperson
It is really the second coming of Excel. And it is a good thing (probably?)
Probably net positive. But just like spreadsheets, it’s likely that having tools created by a layperson that does not properly secure or test the system is probably going to occur, cause some unfortunate issues, and steal the headlines. Similar to when an excel formula error results in a flash crash of financial markets and such. It’s huge and sucks but there’s also countless value being added daily all around the world with little fan fare.
I made an app for myself and the local MTB community for keeping track of rain and soil moisture for nearby trails so it's easier to decide when a trail will likely be open. Much more reliable than waiting for the official (volunteer led) organization to update the status. I never would have made it without an LLM to speed things along.
A good friend of mine helped his mom keep track of Meals On Wheels (or a similar volunteer org) orders, deliveries, cancellations, etc. They were managing all of this via paper before.
I compiled a list of online recipes. Then I had an LLM typeset them for me into a printable PDF and build a companion website with links to the original recipes and complete ingredient lists for shipping. had the LLM encode links for the companion site into QR codes so the printed copy of the cookbook would bring me immediately to a shopping list, making trying a new recipe soooo much less daunting.
There are so many little things like this that you can make that just take too much effort to justify otherwise. I have other ideas for personal projects that I'll probably get to some day.
Anecdotally, Claude Code has prompted an explosion of open source projects and prototypes from self-starters. A lot of these are just hobby projects, but some of them genuinely fill a niche that was previously too complicated or unviable to develop otherwise.
Some of them have half baked financial models, but nobody will invest dollars backing a SaaS offering that could easily be replicated, or that could be made redundant tomorrow.
> [...] but nobody will invest dollars backing a SaaS offering that could easily be replicated, or that could be made redundant tomorrow.
Matt Levine wrote in his newsletter Money Stuff of some investment fund that has their employees vibecode replacements for software of potential investment targets. I guess the theory is exactly what you say: if the internal employees can replace the target's software in a few hours, that's a big signal on whether to invest or not.
(I wouldn't quite say you shouldn't invest at all; but you have to argue that the moat is in eg the sales process or the existing customer base or network effects etc. Even before AI, people famously build Twitter clones over the weekend for fun.)
For a long time nobody knew how to monetize OSS outside of a few Linux vendors.
There's a crapload of new repos and Github and similar things. And a lot of it is "hobby utility" stuff like you'd find everywhere pre-mobile/pre-app-store but kinda dried up a bit with the browserfication+phone-ificiation of everything. Everything had to turn into an app + an online service.
Now, like OSS, freeware, and even most shareware in the 90s, most of these new projects have no path to VC-level interest.
The whole "basic business or business-process BUT ON THE INTERNET with a dash of social/web-2.0/personalization/crypto/fad-of-the-year" that recent VC firms have been pushing for the last 15+ years may be numbered.
But it's also unlikely that growing companies with big ambitions will want to base their business on vibe-coded free software for too long. It opens up too many unknowns/risks ("oh no, the disgruntled employee leveraged a misconfiguration in our in-house accounts payable system!") There will be a new middle ground model to be found.
> But it's also unlikely that growing companies with big ambitions will want to base their business on vibe-coded free software for too long. It opens up too many unknowns/risks ("oh no, the disgruntled employee leveraged a misconfiguration in our in-house accounts payable system!") There will be a new middle ground model to be found.
I agree _iff_ vibecoding stayed roughly at today's level of competence.
If the models keep improving, perhaps you'll just tell them 'eh, and make sure to close all the security holes' and they'll do so.
There are a lot of specialty/niche apps showing up which are vibe coded --- tons of 3D CAD apps which are a variation/extension of OpenSCAD, a fair number of tools which work with G-code in various ways, &c.
On a commercial support forum I moderate we had to ban software announcements there were so many.
I was idly browsing F-Droid yesterday and found a Claude coded B-REP CAD program built on OpenCASCADE, all touch friendly and everything. Definitely something happening.
I think we actually are seeing an app explosion, just not a consumer app explosion.
I think a) the labs are releasing very fast and b) why would they implement the long tail of app features when they can effectively sell tokens to every user to write their own version of the app, which is what is currently happening?
Because, as the gp pointed out, if the cost is least to the labs, then why not reap the benefits too?
Hypothetical. Assume you can in fact point agents at a tool and say "replicate it. Make no mistakes". You then have software being instantly copy-able.
Assume these agents can then be pointed to a customer feedback board in perpetuity and they autonomously upgrade the software over time. They analyze usage patterns and behave like PMs figuring out what to prune and what to build. Then the maintenance part of the stack also goes to zero.
Over time, the highest margin competitiveness will go to the distributor of the tokens. Aka the AI model makers.
In a world like that (which the frontier labs claim is within a year or two of happening) it feels like it's only a matter of time before they opt to own the entire stack down to the consumer apps. Kind of like Amazon deciding they want to knock off products doing well and then favour their own product over the original seller.
My guess is that if the capability arrives the only reason the frontier labs don't move to own the entire stack immediately is because of optics. Boil the frog instead.
There is more to selling software than writing it. You have market, support, and sell. Do you think their resources are well spent doing that across the gamut of software? Of course not; companies specialize.
Very similar to how cloud providers love renting servers to you to run your bank or software business; instead of running these businesses themselves.
Isn't the promise that LLM can do all this better than any human? Or at least in few short months? Surely marketing, support and selling is just case of right prompt?
I think there is an explosion of new apps, the problem is still distribution in marketing. If I develop a new vibe coded app, it will still take some time for it to be known. And also get good.
Also, what another commenter said that most of new apps are in-house, fully agree with that.
> especially from the AI labs
IMO this is one of the endgame for big ai LABS, they will allow and subsidize users to test and validate on their behalf and once there is a PMF they will step in.
Speaking from my side of the industry (the gaming industry), we are seeing a massive increase in the number of games people are making. Above the growth that was already there.
The distinction is that the games being made are garbage, and I mean worse than shovelware garbage. It's actively made things much harder as someone that fancies himself an indie game curator because you gotta dig through more and more games to find stuff with actual people behind it.
I’ve seen a ton of new open source slop programs. Every day there’s so many “announcing my cool new app” posts. I don’t remember the rate being this high before.
Maybe there's an argument that a lack of rising profit margins in non-tech companies is a bad sign for AI, but this article doesn't make it. Why can't we have a red-queen's race where non-tech companies are implementing AI, but it's not increasing the total profits of those sectors, just meeting rising customer demands/fighting over the share of existing profits? (Never mind that if you look at that chart, profit margins aren't static to begin with, so you can't isolate AI impact from normal fluctuation).
Now, on the first order point, I agree that non-tech companies seem to be taking longer to see results from AI, even if the argument was bad.
I work on SaaS for the logistics space, and I feel like prior to the end of 2025, almost all the discussion about AI for logistics was vaporware, starting this year, companies are actually trying to deploy agents, and we'll start finding out what the ROI is later this year or next.
> Why can't we have a red-queen's race where non-tech companies are implementing AI, but it's not increasing the total profits of those sectors, just meeting rising customer demands/fighting over the share of existing profits?
But then if this happens - all of the stock market has risen in the promise of AI. If AI eats profits instead of grows them, then the economy shrinks right? So maybe that’s worse? That there is no productivity increase?
> If AI eats profits instead of grows them, then the economy shrinks right?
No, why? The economy is bigger than company profits. Eg there's workers' wages and customer surplus and investments etc.
Because companies need earnings growth and they’ll fire workers to meet those targets
> I agree that non-tech companies seem to be taking longer to see results from AI
Rewriting your app in rust won't increase your revenue, it will cost you more in terms of tokens and risk increasing.
There is no reason to believe the ROI runway is not long inside the tech sector either. I mean, you cannot base that on claims made by the AI sub-sector of the tech sector; of course they are going to claim nothing other than that eating their dogfood is great ROI with a short runway.
If you need immediate ROI (say, because you just invested a trillion dollars into datacenters) you may be out of luck.
And I don't think this is unusual. It took decades for previous technologies to be fully integrated into existing businesses. In the 80s you could see the IT revolution everywhere... except the productivity statistics, which didn't catch up until the 90s.
LLMs are still very new and have significant limitations (like prompt injection and high token costs) that are very likely solveable but will take time.
Microsoft, Amazon are all building forward deployment engineering teams - to increase AI adoption. It will take time, but it will happen.
This is more marketing hype than substance. Amazon isn’t “building” a team, it’s broadly just taking existing people and now calling them “forward deployment engineering teams.”
Also, adoption isn’t lacking because of lack of awareness. Adoption isn’t happening because the math doesn’t add up and the ROI isn’t there. Consulting pixie dust can’t fix that.
Ah man it’s gonna be hilarious when this comes crashing down -and it will. It’s pretty obvious ‘demand is infinite’ was always a lie - demand is infinite only when price approaches zero lol! Prices are going further away from zero not closer
Feels like a new consulting wave which is implementation-led by AI vendors taking a large share of the services layer. The existing consulting companies (big 4 etc) will have to shift to niche advisory or heavy channel partnerships with way fewer consultants.
The premise is flawed.
"The first chart below shows that so far there are no signs of profit margins rising outside the tech sector. This is ultimately what we are waiting for, because the value of AI companies today rests entirely on the promise that margins in the S&P 493 will eventually climb."
This is absolutely not necessary. The bull case is that AI will bring great efficiencies. The surplus profits from those efficiencies could easily be competed away by firms who have adopted AI. Those firms who do not adopt AI will have their margis crushed.
> The surplus profits from those efficiencies could easily be …
… usurped by the tech companies?
So then your argument would be that we could see a bifurcation in the SP493 where those who adopt AI see increasing margins and those who do not have their margins crushed. What's funny is that in that scenario, the aggregate market might look zero sum.
With enough competition, the surplus will go to consumers (and workers).
Well those efficiency gains have to show up somewhere. It would imply that consumers / customers of these companies are receiving cheaper or higher value services / goods.
Thats at odds with current inflation trends to say the least.
Even aside from inflation, the prospect of efficiency-borne gains meaningfully benefiting the consumer rather than fattening corporate profit margins, frankly, seems like magical thinking. I’ve seen no evidence that our current corporate culture is capable of it (for any longer than it takes to dominate some market.)
What does corporate culture have to do with any of it? The surplus goes to the consumer not because of any benevolent corporate culture, but because of competition.
And (most) efficiency gains have benefited customers in the past.
Just check eg how much you are paying for excellent lighting of your house today vs 200 years ago.
Yeah that’s why health care and credit are so cheap!
How about literally anything run by private equity?
I imagine this would come from outside the US.
What does this look like for any given company? Which margins will you be crushed by for not adopting?
Labor, obviously. That's where all the money in a business goes: paying pesky human employees.
If your employees can suddenly magically do more work with the same pay, that's free money (for you). You can pay fewer employees, or pay them less by threatening to replace them with the magic robot.
The magical thinking version of this is that your productivity gains magically translate into more customers and more sales for the same input cost and labor. The free money is really free because you're a magical special snowflake company and every consumer will want your brand of magic machine outputs and not the other guy's. Where does all this money come from? Do those extra customers even exist? Who cares!
Hypothetical:
Pepsi starts using AI in some magical way that allows them to increase their margins. This allows them to reduce prices while increasing profits. Price-sensitive customers switch from Coca Cola products to Pepsi products. Coca Cola loses some market share, reducing economies of scale, and reducing margins, thus reducing profits. As the cycle repeats, Pepsi moves to dominate the market, and Coca Cola is slowly squeezed down.
Realistic and historically accurate:
Pepsi starts collecting the extra profits with zero price reductions.
In a duopoly, probably yes. However in a more competitive environment where several incumbents have achieved a given optimization a race to the bottom is likely to occur because it only takes one of them preferring to increase their relative market share to kick the process off.
The cola market is effectively a duopoly.
Barriers to entry ain't exactly high.
sacrificing even more profits that may be had by undercutting coca-cola's price? The CEO would be fired.
Markets generally don't follow Econ 101. There are effects beyond first order when it comes to pricing.
Really depends on the concrete numbers and the projections. You could be right, I could be right, I am only saying what I've witnessed historically in general. Greed trumps a lot of other fairly rational courses of action.
Ah yes, magical hypotheticals
Do you have a constructive objection to the described market dynamic?
Yes: historically this is not what I have observed businesses doing. They'd fight tooth and nail to reduce expenses for the fatter profits; cost savings are seldom if ever passed to consumers.
Obviously they don't voluntarily pass on cost savings to customers. That's why competition is there for.
Btw, check how much RAM costs today per byte than eg 20 years ago. Even including today's AI driven price increases. Or check how much it costs to keep your house light up nice and bright compared to 50 years ago.
How much does a car cost now? Surely with automation, robots and general efficiency gains every where in the production chain they should be lot cheaper than they used to be.
The companies seem to rarely keep the cheaper models around too for something. Surely they could sell them for right price.
I don't understand why anyone insists that this needs more time. None of what we've seen in the past few years is new tech. It's more money and hardware thrown at the problem than ever before for diminishing returns.
The market has clearly spoken. Knowing what you're doing is much more valuable than just the doing. That still requires humans. This AI winter has already begun.
>None of what we've seen in the past few years is new tech.
Well that's just wrong. Reasoning models are new and very powerful. LLMs can complete open-ended tasks that require many complex steps.
We're just beginning. The bubble will pop and investors will lose a lot of money, but we're not going back into a winter. It actually works this time.
I don't think there's any bubble to pop.
However, yes, market asset prices can go up as well as down. (If they could only go up, there would be free money to be made.)
Ehh, it’s a late AI summer at best. You still need the economic leaves to finish falling off the trees before you can get to the true start of winter.
Everyone's arguing the macro (do the margins show up), but the reason non-tech ROI is slow is pretty concrete once you've been close to one of these projects: most of what I've seen bolts a chatbot onto the existing system and stops there, and a chatbot on top of rigid software inherits all the rigidity plus a new way to be wrong.
The value shows up only after the boring part: wiring the model to the real data with real access control, and moving anything that has to be exact or repeatable out of the model and into deterministic tools it calls. That's an integration-and-permissions project, not an "adopt AI" project. It's slow, it's unglamorous, nobody demos it, so pilots skip straight to the chatbot and then report thin ROI. Tech companies see returns faster partly because their data and tooling are already reachable by the thing.
So I'd read the flat margins as "the actual work hasn't been done yet," not "there's no value there." The runway being long and the technology being real aren't in tension. The gap is that the useful version looks like plumbing, and plumbing doesn't get funded on the same timeline as a demo.
The slower adoption in non-tech sectors isn't just cultural lag - the integration surface is genuinely harder. Legacy ERP systems, compliance review cycles for what data the model can touch, and change management overhead all front-load costs before any efficiency shows up in margins.
I've seen this in payment/API systems: the actual model integration takes weeks, but getting legal and security sign-off on the data pipeline takes months. Non-tech companies face the same pattern but with less internal tooling to manage it.
The margin signal might also be appearing at the wrong level. Gains in these sectors often show up first as headcount flatness or throughput improvements before they hit EBITDA. Measuring at the P&L level on a 2-year horizon is probably too early and too coarse - the operational metrics are moving, the accounting just hasn't caught up yet.