> The fear is that these [AI] tools are allowing companies to create much of the software they need themselves.
AI-generated code still requires software engineers to build, test, debug, deploy, secure, monitor, be on-call, support, handle incidents, and so on. That's very expensive. It is much cheaper to pay a small monthly fee to a SaaS company.
A lot of these companies are not small monthly fees. And if you’ve ever worked with them, you’ll know that many of the tools they sell are an exact match for almost nobody’s needs.
So what happens is a corporation ends up spending a lot of money for a square tool that they have to hammer into a circle hole. They do it because the alternative is worse.
AI coding does not allow you to build anything even mildly complex with no programmers yet. But it does reduced by an order of magnitude the amount of money you need to spend on programming a solution that would work better.
Another thing AI enables is significantly lower switching costs. A friend of mine owned an in person and online retailer that was early to the game, having come online in the late 90s. I remember asking him, sometime around 2010, when his Store had become very difficult to use, why he didn’t switch to a more modern selling platform, and the answer was that it would have taken him years to get his inventory moved from one system to another. Modern AI probably could’ve done almost all of the work for him.
I can’t even imagine what would happen if somebody like Ford wanted to get off of their SAP or Oracle solution. A lot of these products don’t withhold access to your data but they also won’t provide it to you in any format that could be used without a ton of work that until recently would’ve required a large number of man hours
If it is not a small fee, I do wonder - is there still advantage to having a provider which one may take out a lawsuit against if something goes wrong? To what extent might liability and security vetting by scaled usage still hedge against AI, in your view?
Our company just went through an ERP transition and AI of all kinds was 0% helpful for the same reason it’s difficult for humans to execute: little to no documentation and data model mismatches.
Modern AI probably could’ve done almost all of the work for him.
no way. We're not talking a standalone AI created program for a single end-user, but entire integrated e-commerce enterprise system that needs to work at scale and volume. Way harder.
I also have pretty hefty skepticism that AI is going to magically account for the kinds of weird-ass edge cases that one encounters during a large data migration.
Hmm, I wonder if it would be cheaper to hire a couple of software engineers to vibe-code custom SaaS apps on top of the company's existing data layer instead of paying for a hundred different SaaS subscriptions.
Financial considerations aside, one advantage of having in-house engineers is that you can get custom features built on-demand without having to be blocked on the roadmap of a SaaS company juggling feature requests from multiple customers...
I'm at a large company that is building connections between all of its different financial systems. The primary problem being faced is NOT speed to code things, the primary problem at large companies is getting business aligned with tech (communication) and getting alignment across all the different orgs on data ownership, access, and security. AI currently doesn't solve any of this. Throw in needing to deal with regulation/SOX compliance and all the progress you think AI might make, just doesn't align with the problem domains.
Agreed. The SWEs already receive a steady supply of conflicting demands from every possible business unit; the value add for these teams is a working PMO to prioritize the requests coming in.
This is also generally true for all mid to large businesses I've ever worked at.
The code they write is highly domain-specific, implementation speed is not the bottleneck, and their payroll for developers is nothing compared to the rest of the business.
"Small Monthly Fee" is a very loaded term here.
Im in the negotiations for these platforms, the price that many of these companies command for their products will very often pay the salaries of a whole software department.
Add to this the quality of support being the lowest possible option above "nonexistant" and I would say the risk to these SaaS companies is real.
The real benefit of these types of SaaS offerings was their ubiquity across multiple industries and verticals. If a company bought Salesforce, they could very readily find employees that would be able to quickly onboard since they would likley have used it at previous companies.
AI software generation is changing this as more and more software being created is bespoke and increasingly one-of-a-kind with these tools allowing companies to create software that fits their unique and specific needs.
My hot take here is that the moats previously enjoyed by SaaS companies will increasingly vanish as smaller and smaller teams can assemble "good enough" solutions that companies will adopt instead of paying giant chunks of their budget on pre-built SaaS tools that will increasingly demand more training to Onboard.
Saas was always fueled by B2B buying through same investor circle. sequoia companies buying from other sequoia companies, softbank companies buying from other software companies. Without this circular buying and selling of the software, the whole B2B software market crashes.
multiple of what? there is maybe one software company trading above 30x revenue - palantir. many companies growing at 20% trade at single digit revenue multiples.
That's a software engineer that is limited to an mostly untyped macro language, with worse version control and poor tooling. It's not that software can't be written as an Excel spreadsheet, it is that it is just inefficient and failure prune.
Excel spreadsheets have little to no validation logic that you're actually getting a good result, unless you have a secondary check (most spreadsheets are structured as "single entry" accounting, so lack the checks)
A prime example of this was the Reinhart/Rogoff paper advocating austerity that was widely quoted, and then it was discovered that the spreadsheet used had errors that invalidated the conclusions:
The point is not that people will be using specifically Excel, but that most business only pay for software because it is the tool that gives them the most power to automate their processes. They don't need high availablility, they don't need standards compliance, they don't extensive automated tests, they won't need cloud engineeers and SRE... all you need is some tool that can get the results your are looking for right now.
Academia already works like this. Software wrtiten for academic purposes is notoriously "bad" because it is not engineerd, but that doesn't matter because it is good enough to deliver the results that researchers need. Corporate IT will also start looking like this even at mid-sized companies.
I guess that's technically true, because "most businesses" are sole proprietorships without any employees... but they could get by just fine with a checkbook and a note pad.
But the reasons the business software sector grew far beyond Excel of the 1990s is because of the inherent limitations in scaling solutions built by business analysts inside of Excel. There's a vague cutoff somewhere in the middle of the SMB market where software architecture starts to matter and the consequences for fuckup are higher than the cost of paying for professionally made software with, importantly, a vendor on the hook for making sure it doesn't fuck up.
Uh, no. The main reason the software sector grew in the 90s was a particularly potent combination of FOMO, kickbacks, and strategically deployed cocaine.
AI "generated" code requires a large base of training data to draw from. If we all stop writing code then there will no new code written. Just rehashes of stolen ideas. There is no long tail to this industry or ideal.
> That's very expensive.
As long as you convince someone else to pay the bill who cares? The real problem is are you losing your competitive edge? If everyone else can crank out the same stolen crap you can then there is no reason for you to even exist.
Foundational software requires that, but the foundation is pretty much completely built at this point. The workforce required to keep it running is but a tiny fraction of what was required to build it. The past has shown that innovation in hardware can push for the foundations to be rebuilt, but we've also already got computers basically everywhere now. There may not be some new innovation that requires the foundations to be completely rewritten again.
The little one-off programs that we thought would keep developers busy forevermore don't require engineers. They often don't even require code. LLMs can natively do a lot of things that historically would have required software.
Stock prices are very forward looking, so if half the hype being sold about AI is true I would expect most software-centric companies to be devalued by wall-street (as the test, deploy, support should be automated in the coming years...according to the AI CEO's).
However, if I was a wall street analyst and believed the AI dreams I would further be concerned that software companies aren't taking advantage of the last remnants of value before software (and maybe labor) values go to zero.
If you've got a gold mine and have recently built the most efficient shovels in the world, why are they not bringing in mass amounts of workers to utilize these shovels before all the neighboring mines. Once all that gold is on the market, the price crashes so it's better to be one of the first mines to get in and dig out all possible value first.
I think you either don't believe in the AI hype, which means a lot of silicon valley companies are tremendously overvalued. Or you do, in which case another huge part of silicon valley is overvalued especially when they are not looking to out-innovate their peers (as evidenced by downsizing), but just riding the wave of AI until what they are selling has no marginal value over some guy coding alone in his bedroom. SV is putting itself into a weird position, but still has some time for financial buffoonery before the party stops.
>If you've got a gold mine and have recently built the most efficient shovels in the world, why are they not bringing in mass amounts of workers to utilize these shovels before all the neighboring mines
Because they are completely consumed by the need to increase margins, which they think they will be able to do it with AI by laying off a lot of people. But Saas economy is connected and based on per user pricing, so as layoffs continue, Saas economy is showing its biggest weakness. All of Saas companies also seem to embrace AI so much that they would rather add another summarise button rather than actually making something which cant be copied easily by competitors.
or for a more charitable comment, I think the issue people struggle with right now is how much of non-AI software will be replaced by AI-native versions. and it's not even a 1:1 mapping. we may see 5 different small companies replaced by a single AI interface. all TBD, but there's merit to avoiding that risk right now if you can just allocate to NVDA and GOOG instead
I was one of the nay sayers but right now I am convinced.
That being said, it still requires some engineering background to come up with interesting ideas and solutions with the help of LLMs but even that might be replaced.
The Value of software is going down, this much is clear to most people.
It will continue to demand proper engineering for its creation and operation.
But AI will lead to an increase of unique one-of-a-kind systems created by very small teams. And the world will increasingly rely on these unique systems.
SaaS companies need to start reading the writting on the wall, their massive valuations enjoyed when software was harder to create will need to be justified.
I dont actually think it changes the economics of software as a service much. What's true for the small scale is true for the large scale. Sure, it's easier to build your own HR platform now but it's also easier to write and maintain it at scale with all your domain knowledge, legal infrastructure, etc. This seems true for inventory management, document signing, ecommerce, expensing, crm, training, accounting, etc. Why wouldn't the offerings from services providers get better and cheaper (relatively)?
The stuff you do in-house is probably still going to tied deeply to your internal processes. Admin dashboards, special workflows integrating with different systems, etc.
Consider it in the realm of supply and demand.
The economics of software will change simply because the tool enables more software to be written.
In a way, the barrier of entry into the space of selling software has lowered. It hasnt vanished, but there will be many more entrants and offerings as a result, thus more competition for the existing SaaS companies.
I don't see how the economics of SaaS will remain the same when their value is formed of capital and labor expended, both of which require less now, so please explain how this doesn't lead to an increase in supply and a downward pressure on value?
Everyone says that but I don't see anyone cooking up the next photoshop and selling it at $3/month. Why are we not seeing more options of every tool? Most Saas companies are sales companies at their core rather than software companies. And those sales people are so good that they can sell a todo list for millions.
There are more computers now than there ever have been. More people in more parts of the world have them than ever before. If you have this perspective you may just be locked in a first-world corporate nightmare that has stolen from you all vision and imagination.
Perhaps the it would be better described as "commodification" of software, which still gets my point across.
Software is absolutely more ubiquitous than ever before, this I can agree upon. But now we have the tools to create more of it, and therefore software is less valuable simply as it is less rare.
I dont mean to say that software is valueless, but rather that it enjoyed inflated value as the amount of capital and effort required to build a software product was much greater.
The iShares Expanded Tech-Software Sector ETF (IGV) seems to backup what the article is saying. It is down about 10% last week, and 20% down the past six months. The IT sector as a whole didn't lose much.
No, they dont distrust AI, they now may start to distrust all the big service providers that are likelty to eventually be eradicated by AI now that everyone can prompt a browser. This perhaps will also finally kill Microsoft Access, which is the closest to AI doing the work instead of you for so long. Then all the do-it-yourself enterprise-grade systems became SAAS, so its right for SalesForce and friends to go fck themselves once in a lifetime for standing in the way of actual software ownership.
I know, you are saying - they will adopt. Perhaps, while also cutting 40% (if not more) personnel during the pivot, and perhaps also by facing more challenges by faster moving competition.
Like, look for a second - why didn't Google create what the perplexity newsfeed is, given they actually like did 10 years ago and then close to nobody was using it. The equilibrium seems super unstable. What happens if a smart kid devices way to compress this information 10x times faster. This immediately means neural chips stall.
This volatility is something, not a joke. The second order effects may be unforseeable in an unparalleled way. Besides, the Luddites organize much better in 2026 given reddit etc.
the crash is indiscriminate, which is really disheartening. even infra software is getting demolished, no llm is going to replace something like mongodb, but it's all traded under the same umbrella.
What an odd article that is just designed to hype the software creation aspect, which doesn't really affect MAGAF.
MSFT went down because of overexposure in AI and because it is clear that people do not want it.
AI weariness is a thing, and if people go off the Internet or advertisers question whether humans or AI swarms are "watching" their ads it is over for the big players.
Trying to salvage the situation by hyping the relatively small code generation (theft) aspect is quite a poor analysis.
Yeah the article doesn't make a lot of sense to me. Guess whose writing software with AI? Software companies.
They mention sites like Base44 and Lovable. Sure, if tons of business was rotating out of software into no code AI solutions the article would have a point. But has a large portion of market cap moved out of AI into a few little no-code startups? Is Salesforce, Service Now, and SAP being replaced with no code applications? No. Absolutely not. These are small, niche companies. It does not explain a large downward movement in an entire industry.
Meanwhile, in the real world, as a software developer who uses every possible AI coding agent I can get my hands on, I still have to watch it like a hawk. The problem is one of trust. There are some things it does well, but its often times impossible to tell when it will make some mistake. So you have to treat every piece of code produced as suspect and with skepticism. If I could have automated my job by now and been on a beach, I would have done it. Instead of writing code by hand, I now largely converse with LLMs, but I still have to be present and watching them and verifying their outputs.
Yeah but just look at what happened within the last 2 years. I was not convinced about the AI revolution but I bet in another 2 years, we won't be looking at the output..
Not so sure, there are indiosyncracies now within the various models, I suspect all this is the result of RLHF, and they cause side.effects. I'm not sure that more attention-is-all-you-need is necessarily going to give us another step change, maybe more general intelligence, but not more focus. Possibly also we soon end up with grokked AI's on all side: pushing their agenda whatever you asked... Gemini: "no this won't work with Cloudflare, I created your GCP account, there you go" OpenAI: "I am certain you really wanted me to do all these other tasks and I have done them, you should upgrade your tokens plan" etc (you know how to fill in for DeepSeek and Grok already, right)
I've been coming around to the view that the time spent code-reviewing LLM output is better spent creating evaluation/testing rigs for the product you are building. If you're able to highlight errors in tests (unit, e2e, etc.) and send the detailed error back to the LLM, it will generally do a pretty good job of correcting itself. Its a hill-climbing system, you just have to build the hill.
Some 7-15% down in a trading day is a lot for an established corporation. I consider Salesforce dropping 7% without some obvious trigger to be at least somewhat newsworthy, and from the first sentences in the article I get the impression that The Economist is sitting on more examples like that.
A lot of people are tense about the AI venture ouroboros and what it might mean for future software, especially people with money and little to no experience actually deploying software.
Edit: At the time I saw some memes claiming that roughly 1.5 trillion dollars in market value had evaporated, which if true is not a small sum.
... because they've been driven by years of bad leadership, monopolistic scheming, and investor speculation?
AI is just the latest symptom, IMO.
We normalized growth over revenue. Governments around the world have been pressured by Big Tech to dismantle anti-trust and regulation. We glorified shipping slop, suppressing unions, and pretending like programmers were temporarily embarrassed founders.
The stocks are dropping because our system can't sustain these practices, IMO.
This article crystallizes something I witnessed firsthand last week.
Overheard a guy at a restaurant explaining how he builds phone apps with AI and no coding experience. When asked how he verifies the code works, he said he pastes it into a different AI to explain it.
That's the "slopware" problem in action. The code compiles. It might even work. But there's no understanding of what it's actually doing, no ability to debug when it breaks in production, no awareness of the technical cruft accumulating with every prompt. That's a problem for people creating software for others and is a huge opportunity for software developers to take prototypes and build real stuff.
Does anyone remember the RAD days of the 90s?
On the flip side, for people making software to solve THEIR problems, they don't need to make anything production quality. Its for a single user, themselves! Maybe the LLMs are good enough now that people don't need to buy or subscribe to software that solves trivial problems as they can build their own solutions. Maybe the dream of smalltalk, hypercard, and even early web where anyone can use the computer of what it was meant for is finally here?
AI replacing vendors feels like a strange risk, though I'm not sure if vendors view things through a technical lens. Security concerns and service maintenance alone, IMO, makes writing internal software a large proposition - one that I would want a trusted vendor if it wasn't a hobby project and I could just afford that. Particularly if that data being lost or broken would severely harm a business.
There are also already frameworks in languages like Python that make putting up an internal website very, very simple. If you don't need production grade, you might have already had a pretty low barrier to entry, if you have the skills to figure out how to host the service you just vibe coded, you can probably figure out some basic django to throw data in its ORM, or find libraries that do the work for you.
AI does feel in those technical ways to be an overstated risk, to me at least.
Far more worrying to me is the breakdown of the USA and its role. We are going to have blocs of software and hardware entirely from competing geopolitical regions, which may not be able or authorized to communicate with one another. Any businesses in the USA with significant CA or EU marketshare right now will decline in value to the degree client companies choose, or are told, to stop using USA systems.
(My own governor in California outright antagonized the Europeans at Davos calling them "pathetic" while telling them to get tough on Trump, which means in practice, stop using US, meaning yes California, tech goods and services. A lot of revenue from tech comes from overseas, and we are going to lose at least some portion of that. Particularly in California which already has budget problems with what revenue it's got. Stunning how even The Guardian treated those remarks as "tough" and not insane and self-destructive... sadly it's nothing compared to the worst of the US right now.)
So, where do you throw investment right now? To the US where the marketshares will likely decline, and the political and trade environment is insanely uncertain, but there is momentum on AI and generally decent hardware design, and the existing software companies and knowledge? To the EU or Canada where maybe a nascent software industry will take hold, or perhaps American companies will relocate talent if the USA collapses into civil conflict? To China, if they end up becoming a hegemon, given their strength in hardware and their growing efforts to invest in software alternatives?
I suppose I read markets don't react to "tensions," and maybe it is unprecedented to modern memory, but I think about these things more than AI.
I would add: open source throws additional curveballs. The EU wants to push for open source, and that is admirable, but I wonder what the sustainable funding model would be, and how that could attract attention. I wonder about business models and ability to generate return on investment.
I would think the saner solution is allowing proprietary companies, but imposing technical standards which companies collaborate on, enabling interoperation. Am I mistaken, that the EU is trying to do this with the DMA? I have heard general overtones, but I haven't looked at it very closely, and our media doesn't cover EU tech regulations in much detail in the US, though in a decent world it would, I wish it would.
It always amuses me because the people complaining about stocks going down are always the same people who are causing them to go down. Losing money was a choice that those people collectively made. They could have chosen to act differently, in light of the optimistic long-term future.
No doubt! Collective action is a solved problem! Why do people do things other than the obvious Right Things we can all agree on? Must be some kind of mass psychosis…
Software will be easy to create, which will kill moats and margins on existing products. The game is up for pure saas. Smart money started pricing this in one year ago
For a lot of SaaS firms, a big part of their value is the domain knowledge and best practices encoded in the software.
Current AIs often do a bad job of that. Sure, they know a lot of it. But they also get a lot of it wrong, and can’t tell the difference between genuinely good advice, and advice that sounds good but is practically worthless or even harmful.
(Of course I’m biased since I work for a SaaS firm. But I’m talking about them in general, not just my current employer.)
I'm not sure how realistic it is to expect AIs to get detailed hands-on domain knowledge. A lot of this stuff humans learn by doing and by experience. AI models don't learn anything by doing and experience. A model vendor can't possibly encode all that experience into their training data, and even if they try, the problem is a lot of it will be vertical-specific, country/region-specific, and it is forever changing. SaaS firms have professional services and sales consulting teams who are constantly talking to customers about their actual business problems, and they feed that accumulated wisdom back to product management and data science, who in turn help engineering encode it into the product.
From what I've personally seen in SaaS AI agent development – if you try to build an AI agent to give customers advice in a particular business domain, you need to do a huge amount of work validating the answer quality with actual domain experts, and adjusting the prompts / RAG documents / tool design / etc to make sure it is giving genuinely useful advice. It is really easy to build a system which generates output which sounds superficially good, but an actual domain expert will consider wrong or worthless.
Was the hard part ever really the software, though? It's the Service part of SaaS that seems to provide the moat. Lock-in, habits, workflows, integrations, and trust. And don't discount the appeal of making some part of your operations "someone else's problem." Could you hire engineers or use an LLM to make your own Google Docs? Probably, yeah, but would that be worth the headache of being responsible for a bespoke internal document system?
You might think you can, for a while. Been there, done that. But you probably can not do so sustainably in most cases. Even if you could, would you really be better off building vs. buying? Outsourcing development, operations, and maintenance is almost always the better choice, letting you focus on the things you do uniquely, differentiably, or meaningfully better.
"We have this awesome internal version of Docs that we're responsible for fixing, upgrading, and doing support for" is not the flex "AI can code anything!" aficionados think it is. Especially when you also have similar internal versions of Sheets, Jira, Slack, GitHub, Linux, Postgres, and 100 other tools.
Making your own Google Docs is stupid unless your company's core business is document management.
OTOH Replacing SAP with a bespoke system will make a lot of sense for many companies.
SAP is already the worst of both worlds. It'll have been highly customized for your flow so you've got all of the headaches of bespoke software and all of the headaches of SaaS. And unlike Google Docs, it'll be highly integral to your core business.
Companies pay millions and millions to get away from bespoke software, but not simply because of the costs. Companies want to do their core business, they don't want to also be a software enterprise, and assume all the risks that entails. Even if AI makes creating software 10 times less expensive, that doesn't really change.
Even then, I would expect most orgs would want to contract out to a company that manages an instance of that open source software. That management company could undercut bigger players because they don't need as many engineers working on features. I don't see where the LLM comes in and shifts the calculus here.
the problem is an AI can figure out habits and workflows pretty seamlessly. lock-in is artificial and loses power when it's really easy to make a competing app for large swaths of web apps.
integration is likely the most valuable part of the puzzle, but it's also prone to disruption
I think all that's left are like <50 apps each with their own very bespoke and "power user"-ready interface
Can't wait for every hospital to create their own patient record system, every accounting office to create their own accounting software, every car service to create their own timebooking solution, etc.
https://archive.ph/37Hwn
> The fear is that these [AI] tools are allowing companies to create much of the software they need themselves.
AI-generated code still requires software engineers to build, test, debug, deploy, secure, monitor, be on-call, support, handle incidents, and so on. That's very expensive. It is much cheaper to pay a small monthly fee to a SaaS company.
A lot of these companies are not small monthly fees. And if you’ve ever worked with them, you’ll know that many of the tools they sell are an exact match for almost nobody’s needs.
So what happens is a corporation ends up spending a lot of money for a square tool that they have to hammer into a circle hole. They do it because the alternative is worse.
AI coding does not allow you to build anything even mildly complex with no programmers yet. But it does reduced by an order of magnitude the amount of money you need to spend on programming a solution that would work better.
Another thing AI enables is significantly lower switching costs. A friend of mine owned an in person and online retailer that was early to the game, having come online in the late 90s. I remember asking him, sometime around 2010, when his Store had become very difficult to use, why he didn’t switch to a more modern selling platform, and the answer was that it would have taken him years to get his inventory moved from one system to another. Modern AI probably could’ve done almost all of the work for him.
I can’t even imagine what would happen if somebody like Ford wanted to get off of their SAP or Oracle solution. A lot of these products don’t withhold access to your data but they also won’t provide it to you in any format that could be used without a ton of work that until recently would’ve required a large number of man hours
If it is not a small fee, I do wonder - is there still advantage to having a provider which one may take out a lawsuit against if something goes wrong? To what extent might liability and security vetting by scaled usage still hedge against AI, in your view?
Our company just went through an ERP transition and AI of all kinds was 0% helpful for the same reason it’s difficult for humans to execute: little to no documentation and data model mismatches.
surprising considering you just listed two primary use cases (exploring codebases/data models + creating documentation)
Modern AI probably could’ve done almost all of the work for him.
no way. We're not talking a standalone AI created program for a single end-user, but entire integrated e-commerce enterprise system that needs to work at scale and volume. Way harder.
I also have pretty hefty skepticism that AI is going to magically account for the kinds of weird-ass edge cases that one encounters during a large data migration.
Hmm, I wonder if it would be cheaper to hire a couple of software engineers to vibe-code custom SaaS apps on top of the company's existing data layer instead of paying for a hundred different SaaS subscriptions.
Financial considerations aside, one advantage of having in-house engineers is that you can get custom features built on-demand without having to be blocked on the roadmap of a SaaS company juggling feature requests from multiple customers...
I'm at a large company that is building connections between all of its different financial systems. The primary problem being faced is NOT speed to code things, the primary problem at large companies is getting business aligned with tech (communication) and getting alignment across all the different orgs on data ownership, access, and security. AI currently doesn't solve any of this. Throw in needing to deal with regulation/SOX compliance and all the progress you think AI might make, just doesn't align with the problem domains.
> getting business aligned with tech (communication) and getting alignment across all the different orgs
This is what a CEO is supposed to do. I wonder if CEOs are the ones OK with their data being used and sent to large corps like MS, Oracle, etc.
Agreed. The SWEs already receive a steady supply of conflicting demands from every possible business unit; the value add for these teams is a working PMO to prioritize the requests coming in.
This is also generally true for all mid to large businesses I've ever worked at.
The code they write is highly domain-specific, implementation speed is not the bottleneck, and their payroll for developers is nothing compared to the rest of the business.
AI would just increase risk for no reward.
"Small Monthly Fee" is a very loaded term here. Im in the negotiations for these platforms, the price that many of these companies command for their products will very often pay the salaries of a whole software department. Add to this the quality of support being the lowest possible option above "nonexistant" and I would say the risk to these SaaS companies is real.
The real benefit of these types of SaaS offerings was their ubiquity across multiple industries and verticals. If a company bought Salesforce, they could very readily find employees that would be able to quickly onboard since they would likley have used it at previous companies. AI software generation is changing this as more and more software being created is bespoke and increasingly one-of-a-kind with these tools allowing companies to create software that fits their unique and specific needs.
My hot take here is that the moats previously enjoyed by SaaS companies will increasingly vanish as smaller and smaller teams can assemble "good enough" solutions that companies will adopt instead of paying giant chunks of their budget on pre-built SaaS tools that will increasingly demand more training to Onboard.
Saas was always fueled by B2B buying through same investor circle. sequoia companies buying from other sequoia companies, softbank companies buying from other software companies. Without this circular buying and selling of the software, the whole B2B software market crashes.
Other reason could be that investors think companies are going to lay off a lot of their staff and then that will decrease Saas revenue anyway.
AI-generated code is not copyrightable and therefore cannot be protected through a conventional licensing scheme.
yes, but this does fit into the head of MBA-bobo-management stylers, who believe ChatGPT will replace everyone :)
Yes, it's just that some companies will fail to adapt, but there will be new jobs.
That would justify a good multiple of 5 to 10. Not 30 or above as for high growth companies.
multiple of what? there is maybe one software company trading above 30x revenue - palantir. many companies growing at 20% trade at single digit revenue multiples.
> AI-generated code still requires software engineers
No, they don't.
A domain expert armed with an Excel spreadsheet and the ability to write VBA macros will be enough for most business.
That's a software engineer that is limited to an mostly untyped macro language, with worse version control and poor tooling. It's not that software can't be written as an Excel spreadsheet, it is that it is just inefficient and failure prune.
Excel spreadsheets have little to no validation logic that you're actually getting a good result, unless you have a secondary check (most spreadsheets are structured as "single entry" accounting, so lack the checks)
A prime example of this was the Reinhart/Rogoff paper advocating austerity that was widely quoted, and then it was discovered that the spreadsheet used had errors that invalidated the conclusions:
https://en.wikipedia.org/wiki/Growth_in_a_Time_of_Debt#Metho...
Just because technology is in use and "works" doesn't mean it's always correct.
You are taking my comment way too literatlly.
The point is not that people will be using specifically Excel, but that most business only pay for software because it is the tool that gives them the most power to automate their processes. They don't need high availablility, they don't need standards compliance, they don't extensive automated tests, they won't need cloud engineeers and SRE... all you need is some tool that can get the results your are looking for right now.
Academia already works like this. Software wrtiten for academic purposes is notoriously "bad" because it is not engineerd, but that doesn't matter because it is good enough to deliver the results that researchers need. Corporate IT will also start looking like this even at mid-sized companies.
I guess that's technically true, because "most businesses" are sole proprietorships without any employees... but they could get by just fine with a checkbook and a note pad.
But the reasons the business software sector grew far beyond Excel of the 1990s is because of the inherent limitations in scaling solutions built by business analysts inside of Excel. There's a vague cutoff somewhere in the middle of the SMB market where software architecture starts to matter and the consequences for fuckup are higher than the cost of paying for professionally made software with, importantly, a vendor on the hook for making sure it doesn't fuck up.
Uh, no. The main reason the software sector grew in the 90s was a particularly potent combination of FOMO, kickbacks, and strategically deployed cocaine.
> AI-generated code
AI "generated" code requires a large base of training data to draw from. If we all stop writing code then there will no new code written. Just rehashes of stolen ideas. There is no long tail to this industry or ideal.
> That's very expensive.
As long as you convince someone else to pay the bill who cares? The real problem is are you losing your competitive edge? If everyone else can crank out the same stolen crap you can then there is no reason for you to even exist.
Foundational software requires that, but the foundation is pretty much completely built at this point. The workforce required to keep it running is but a tiny fraction of what was required to build it. The past has shown that innovation in hardware can push for the foundations to be rebuilt, but we've also already got computers basically everywhere now. There may not be some new innovation that requires the foundations to be completely rewritten again.
The little one-off programs that we thought would keep developers busy forevermore don't require engineers. They often don't even require code. LLMs can natively do a lot of things that historically would have required software.
You can use AI for simple stuff.
For everything else, there’s open source.
Open source doesn't implement, host, and support itself. Some of these software companies stocks are companies selling open source software.
Stock prices are very forward looking, so if half the hype being sold about AI is true I would expect most software-centric companies to be devalued by wall-street (as the test, deploy, support should be automated in the coming years...according to the AI CEO's).
However, if I was a wall street analyst and believed the AI dreams I would further be concerned that software companies aren't taking advantage of the last remnants of value before software (and maybe labor) values go to zero.
If you've got a gold mine and have recently built the most efficient shovels in the world, why are they not bringing in mass amounts of workers to utilize these shovels before all the neighboring mines. Once all that gold is on the market, the price crashes so it's better to be one of the first mines to get in and dig out all possible value first.
I think you either don't believe in the AI hype, which means a lot of silicon valley companies are tremendously overvalued. Or you do, in which case another huge part of silicon valley is overvalued especially when they are not looking to out-innovate their peers (as evidenced by downsizing), but just riding the wave of AI until what they are selling has no marginal value over some guy coding alone in his bedroom. SV is putting itself into a weird position, but still has some time for financial buffoonery before the party stops.
>If you've got a gold mine and have recently built the most efficient shovels in the world, why are they not bringing in mass amounts of workers to utilize these shovels before all the neighboring mines
Because they are completely consumed by the need to increase margins, which they think they will be able to do it with AI by laying off a lot of people. But Saas economy is connected and based on per user pricing, so as layoffs continue, Saas economy is showing its biggest weakness. All of Saas companies also seem to embrace AI so much that they would rather add another summarise button rather than actually making something which cant be copied easily by competitors.
cost will go down 70-90%
SaaS margins too.
yes but investors don't know that
or for a more charitable comment, I think the issue people struggle with right now is how much of non-AI software will be replaced by AI-native versions. and it's not even a 1:1 mapping. we may see 5 different small companies replaced by a single AI interface. all TBD, but there's merit to avoiding that risk right now if you can just allocate to NVDA and GOOG instead
Maybe just maybe, the markets are not as rational as these people think they are
I was one of the nay sayers but right now I am convinced.
That being said, it still requires some engineering background to come up with interesting ideas and solutions with the help of LLMs but even that might be replaced.
So you disagree with the article? Could you explain your reasoning?
The Value of software is going down, this much is clear to most people. It will continue to demand proper engineering for its creation and operation. But AI will lead to an increase of unique one-of-a-kind systems created by very small teams. And the world will increasingly rely on these unique systems.
SaaS companies need to start reading the writting on the wall, their massive valuations enjoyed when software was harder to create will need to be justified.
I dont actually think it changes the economics of software as a service much. What's true for the small scale is true for the large scale. Sure, it's easier to build your own HR platform now but it's also easier to write and maintain it at scale with all your domain knowledge, legal infrastructure, etc. This seems true for inventory management, document signing, ecommerce, expensing, crm, training, accounting, etc. Why wouldn't the offerings from services providers get better and cheaper (relatively)?
The stuff you do in-house is probably still going to tied deeply to your internal processes. Admin dashboards, special workflows integrating with different systems, etc.
Consider it in the realm of supply and demand. The economics of software will change simply because the tool enables more software to be written. In a way, the barrier of entry into the space of selling software has lowered. It hasnt vanished, but there will be many more entrants and offerings as a result, thus more competition for the existing SaaS companies.
I don't see how the economics of SaaS will remain the same when their value is formed of capital and labor expended, both of which require less now, so please explain how this doesn't lead to an increase in supply and a downward pressure on value?
Everyone says that but I don't see anyone cooking up the next photoshop and selling it at $3/month. Why are we not seeing more options of every tool? Most Saas companies are sales companies at their core rather than software companies. And those sales people are so good that they can sell a todo list for millions.
> this much is clear to most people.
There are more computers now than there ever have been. More people in more parts of the world have them than ever before. If you have this perspective you may just be locked in a first-world corporate nightmare that has stolen from you all vision and imagination.
Perhaps the it would be better described as "commodification" of software, which still gets my point across. Software is absolutely more ubiquitous than ever before, this I can agree upon. But now we have the tools to create more of it, and therefore software is less valuable simply as it is less rare. I dont mean to say that software is valueless, but rather that it enjoyed inflated value as the amount of capital and effort required to build a software product was much greater.
TRUE! Actually the world around is controlled already by computers ~ chips: Your car, your dishwasher, your metro, your holidayjettravel etc.
And it becomes "worse": Billions and billions of chips ~ compusters are produced every year, the number is increasing.
Billions of people will get access to the stuff that was around for us "since ever" for the first time in their whole life.
The iShares Expanded Tech-Software Sector ETF (IGV) seems to backup what the article is saying. It is down about 10% last week, and 20% down the past six months. The IT sector as a whole didn't lose much.
Is the pummeling in the room with us right now? YoY looks phenomenal in my portfolio.
No, they dont distrust AI, they now may start to distrust all the big service providers that are likelty to eventually be eradicated by AI now that everyone can prompt a browser. This perhaps will also finally kill Microsoft Access, which is the closest to AI doing the work instead of you for so long. Then all the do-it-yourself enterprise-grade systems became SAAS, so its right for SalesForce and friends to go fck themselves once in a lifetime for standing in the way of actual software ownership.
I know, you are saying - they will adopt. Perhaps, while also cutting 40% (if not more) personnel during the pivot, and perhaps also by facing more challenges by faster moving competition.
Like, look for a second - why didn't Google create what the perplexity newsfeed is, given they actually like did 10 years ago and then close to nobody was using it. The equilibrium seems super unstable. What happens if a smart kid devices way to compress this information 10x times faster. This immediately means neural chips stall.
This volatility is something, not a joke. The second order effects may be unforseeable in an unparalleled way. Besides, the Luddites organize much better in 2026 given reddit etc.
take a look at 5-year trend
It's just correction.
But it is not THE correction.
the crash is indiscriminate, which is really disheartening. even infra software is getting demolished, no llm is going to replace something like mongodb, but it's all traded under the same umbrella.
What an odd article that is just designed to hype the software creation aspect, which doesn't really affect MAGAF.
MSFT went down because of overexposure in AI and because it is clear that people do not want it.
AI weariness is a thing, and if people go off the Internet or advertisers question whether humans or AI swarms are "watching" their ads it is over for the big players.
Trying to salvage the situation by hyping the relatively small code generation (theft) aspect is quite a poor analysis.
Yeah the article doesn't make a lot of sense to me. Guess whose writing software with AI? Software companies.
They mention sites like Base44 and Lovable. Sure, if tons of business was rotating out of software into no code AI solutions the article would have a point. But has a large portion of market cap moved out of AI into a few little no-code startups? Is Salesforce, Service Now, and SAP being replaced with no code applications? No. Absolutely not. These are small, niche companies. It does not explain a large downward movement in an entire industry.
HN crowd did not like AI coding until it got better. How much of the AI hate is because of poor implementation?
I guess you can classify over-implementation as poor implementation.
Meanwhile, in the real world, as a software developer who uses every possible AI coding agent I can get my hands on, I still have to watch it like a hawk. The problem is one of trust. There are some things it does well, but its often times impossible to tell when it will make some mistake. So you have to treat every piece of code produced as suspect and with skepticism. If I could have automated my job by now and been on a beach, I would have done it. Instead of writing code by hand, I now largely converse with LLMs, but I still have to be present and watching them and verifying their outputs.
Yeah but just look at what happened within the last 2 years. I was not convinced about the AI revolution but I bet in another 2 years, we won't be looking at the output..
Not so sure, there are indiosyncracies now within the various models, I suspect all this is the result of RLHF, and they cause side.effects. I'm not sure that more attention-is-all-you-need is necessarily going to give us another step change, maybe more general intelligence, but not more focus. Possibly also we soon end up with grokked AI's on all side: pushing their agenda whatever you asked... Gemini: "no this won't work with Cloudflare, I created your GCP account, there you go" OpenAI: "I am certain you really wanted me to do all these other tasks and I have done them, you should upgrade your tokens plan" etc (you know how to fill in for DeepSeek and Grok already, right)
Tech can always hit a plateau, here to hoping anthropic & openAI run out of money.
I've been coming around to the view that the time spent code-reviewing LLM output is better spent creating evaluation/testing rigs for the product you are building. If you're able to highlight errors in tests (unit, e2e, etc.) and send the detailed error back to the LLM, it will generally do a pretty good job of correcting itself. Its a hill-climbing system, you just have to build the hill.
QQQ is up 20% over the last year.
GOOG is up 70% over the last year.
"Pummelled" seems extremely sensational...
GOOG is now also an AI company, so not exactly a fair comp as it doesn't fit neatly into the "software" bucket
MSFT is only up 3% over the last year
Some 7-15% down in a trading day is a lot for an established corporation. I consider Salesforce dropping 7% without some obvious trigger to be at least somewhat newsworthy, and from the first sentences in the article I get the impression that The Economist is sitting on more examples like that.
A lot of people are tense about the AI venture ouroboros and what it might mean for future software, especially people with money and little to no experience actually deploying software.
Edit: At the time I saw some memes claiming that roughly 1.5 trillion dollars in market value had evaporated, which if true is not a small sum.
You didn't read the article. The first graph plots Workday, Salesforce, SAP, and ServiceNow. Google isn't mentioned.
Maybe they shouldve said ERP stocks are getting "pummelled"
... because they've been driven by years of bad leadership, monopolistic scheming, and investor speculation?
AI is just the latest symptom, IMO.
We normalized growth over revenue. Governments around the world have been pressured by Big Tech to dismantle anti-trust and regulation. We glorified shipping slop, suppressing unions, and pretending like programmers were temporarily embarrassed founders.
The stocks are dropping because our system can't sustain these practices, IMO.
The cleanup needed after this by senior developers will be epic.
Most of the these companies wont survive because of thier stupidity anyway.
This article crystallizes something I witnessed firsthand last week.
Overheard a guy at a restaurant explaining how he builds phone apps with AI and no coding experience. When asked how he verifies the code works, he said he pastes it into a different AI to explain it.
That's the "slopware" problem in action. The code compiles. It might even work. But there's no understanding of what it's actually doing, no ability to debug when it breaks in production, no awareness of the technical cruft accumulating with every prompt. That's a problem for people creating software for others and is a huge opportunity for software developers to take prototypes and build real stuff.
Does anyone remember the RAD days of the 90s?
On the flip side, for people making software to solve THEIR problems, they don't need to make anything production quality. Its for a single user, themselves! Maybe the LLMs are good enough now that people don't need to buy or subscribe to software that solves trivial problems as they can build their own solutions. Maybe the dream of smalltalk, hypercard, and even early web where anyone can use the computer of what it was meant for is finally here?
Thats fine Ill charge him 500 bucks an hour to fix it if it has success and he runs into not being able to maintain it
Because the bubble has began to burst.
Certainly no investor, but my own feelings:
AI replacing vendors feels like a strange risk, though I'm not sure if vendors view things through a technical lens. Security concerns and service maintenance alone, IMO, makes writing internal software a large proposition - one that I would want a trusted vendor if it wasn't a hobby project and I could just afford that. Particularly if that data being lost or broken would severely harm a business.
There are also already frameworks in languages like Python that make putting up an internal website very, very simple. If you don't need production grade, you might have already had a pretty low barrier to entry, if you have the skills to figure out how to host the service you just vibe coded, you can probably figure out some basic django to throw data in its ORM, or find libraries that do the work for you.
AI does feel in those technical ways to be an overstated risk, to me at least.
Far more worrying to me is the breakdown of the USA and its role. We are going to have blocs of software and hardware entirely from competing geopolitical regions, which may not be able or authorized to communicate with one another. Any businesses in the USA with significant CA or EU marketshare right now will decline in value to the degree client companies choose, or are told, to stop using USA systems.
(My own governor in California outright antagonized the Europeans at Davos calling them "pathetic" while telling them to get tough on Trump, which means in practice, stop using US, meaning yes California, tech goods and services. A lot of revenue from tech comes from overseas, and we are going to lose at least some portion of that. Particularly in California which already has budget problems with what revenue it's got. Stunning how even The Guardian treated those remarks as "tough" and not insane and self-destructive... sadly it's nothing compared to the worst of the US right now.)
So, where do you throw investment right now? To the US where the marketshares will likely decline, and the political and trade environment is insanely uncertain, but there is momentum on AI and generally decent hardware design, and the existing software companies and knowledge? To the EU or Canada where maybe a nascent software industry will take hold, or perhaps American companies will relocate talent if the USA collapses into civil conflict? To China, if they end up becoming a hegemon, given their strength in hardware and their growing efforts to invest in software alternatives?
I suppose I read markets don't react to "tensions," and maybe it is unprecedented to modern memory, but I think about these things more than AI.
I would add: open source throws additional curveballs. The EU wants to push for open source, and that is admirable, but I wonder what the sustainable funding model would be, and how that could attract attention. I wonder about business models and ability to generate return on investment.
I would think the saner solution is allowing proprietary companies, but imposing technical standards which companies collaborate on, enabling interoperation. Am I mistaken, that the EU is trying to do this with the DMA? I have heard general overtones, but I haven't looked at it very closely, and our media doesn't cover EU tech regulations in much detail in the US, though in a decent world it would, I wish it would.
It always amuses me because the people complaining about stocks going down are always the same people who are causing them to go down. Losing money was a choice that those people collectively made. They could have chosen to act differently, in light of the optimistic long-term future.
No doubt! Collective action is a solved problem! Why do people do things other than the obvious Right Things we can all agree on? Must be some kind of mass psychosis…
Software will be easy to create, which will kill moats and margins on existing products. The game is up for pure saas. Smart money started pricing this in one year ago
For a lot of SaaS firms, a big part of their value is the domain knowledge and best practices encoded in the software.
Current AIs often do a bad job of that. Sure, they know a lot of it. But they also get a lot of it wrong, and can’t tell the difference between genuinely good advice, and advice that sounds good but is practically worthless or even harmful.
(Of course I’m biased since I work for a SaaS firm. But I’m talking about them in general, not just my current employer.)
ai will know the domain knowledge
I'm not sure how realistic it is to expect AIs to get detailed hands-on domain knowledge. A lot of this stuff humans learn by doing and by experience. AI models don't learn anything by doing and experience. A model vendor can't possibly encode all that experience into their training data, and even if they try, the problem is a lot of it will be vertical-specific, country/region-specific, and it is forever changing. SaaS firms have professional services and sales consulting teams who are constantly talking to customers about their actual business problems, and they feed that accumulated wisdom back to product management and data science, who in turn help engineering encode it into the product.
From what I've personally seen in SaaS AI agent development – if you try to build an AI agent to give customers advice in a particular business domain, you need to do a huge amount of work validating the answer quality with actual domain experts, and adjusting the prompts / RAG documents / tool design / etc to make sure it is giving genuinely useful advice. It is really easy to build a system which generates output which sounds superficially good, but an actual domain expert will consider wrong or worthless.
Was the hard part ever really the software, though? It's the Service part of SaaS that seems to provide the moat. Lock-in, habits, workflows, integrations, and trust. And don't discount the appeal of making some part of your operations "someone else's problem." Could you hire engineers or use an LLM to make your own Google Docs? Probably, yeah, but would that be worth the headache of being responsible for a bespoke internal document system?
You might think you can, for a while. Been there, done that. But you probably can not do so sustainably in most cases. Even if you could, would you really be better off building vs. buying? Outsourcing development, operations, and maintenance is almost always the better choice, letting you focus on the things you do uniquely, differentiably, or meaningfully better.
"We have this awesome internal version of Docs that we're responsible for fixing, upgrading, and doing support for" is not the flex "AI can code anything!" aficionados think it is. Especially when you also have similar internal versions of Sheets, Jira, Slack, GitHub, Linux, Postgres, and 100 other tools.
The article is about SAP, Salesforce, etc.
Making your own Google Docs is stupid unless your company's core business is document management.
OTOH Replacing SAP with a bespoke system will make a lot of sense for many companies.
SAP is already the worst of both worlds. It'll have been highly customized for your flow so you've got all of the headaches of bespoke software and all of the headaches of SaaS. And unlike Google Docs, it'll be highly integral to your core business.
Companies pay millions and millions to get away from bespoke software, but not simply because of the costs. Companies want to do their core business, they don't want to also be a software enterprise, and assume all the risks that entails. Even if AI makes creating software 10 times less expensive, that doesn't really change.
SAP is bespoke software.
what do you mean SAP? like the ERP system?
I would absolutely NEVER steal or rewrite that. So much finanical stuff is baked into the business logic that impacts finance, regulations, hr, etc.
No do not roll your own ERP core.
Roll everything else
> Could you hire engineers or use an LLM to make your own Google Docs
Or you can just ask your LLM to install https://github.com/CollaboraOnline/online
Between open source, LLMs, and SaaS vendors getting greedy and privacy invasive, the total pain minimization calc might shift for some orgs.
Even then, I would expect most orgs would want to contract out to a company that manages an instance of that open source software. That management company could undercut bigger players because they don't need as many engineers working on features. I don't see where the LLM comes in and shifts the calculus here.
the problem is an AI can figure out habits and workflows pretty seamlessly. lock-in is artificial and loses power when it's really easy to make a competing app for large swaths of web apps.
integration is likely the most valuable part of the puzzle, but it's also prone to disruption
I think all that's left are like <50 apps each with their own very bespoke and "power user"-ready interface
yes, if it takes one month to build something that took 9 months previously, it completely changes your go to market strategy
What would be some examples of some current software products for which you expect the game is up?
Are there any software products that you think will survive?
Can't wait for every hospital to create their own patient record system, every accounting office to create their own accounting software, every car service to create their own timebooking solution, etc.
> Can't wait for every hospital to create their own patient record system
Having worked in healthcare, this is the current state (per provider, not physical building).
We go from left-pad to everything vibe coded. No one vets deps, no one vets vibes. Zero common sense.