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.
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
You are assuming that corporations have the capability to design the software they need.
There are many benefits to SaaS software, and some significant costs (e.g. integration).
One major benefit of SaaS is domain knowledge and most people underestimate the complexity of even well known domains (e.g. accounts).
Companies also underestimate the difficulty of aligning diverging political needs within the business, and they underestimate the expense of distraction on a non-core area that there is no business advantage to becoming competent at. As a vendor sometimes our job was simply to be the least worst solution.
At least that's what I saw.
There is only one program that offers this ability, but you need to pay for the entire software suite, and the process is painfully convoluted anyway. We went from doing maybe 2-3 files a day to do doing 2-3 files an hour.
I have repeated ad-nausea that the magic of LLMs is the ability to built the exact tool you need for the exact job you are doing. No need for the expensive and complex 750k LOC full tool shed software suite.
is this like a meta-joke?
> I have a prime example of this were my company was able to save $250/usr/mo for 3 users by having Claude build a custom tool for updating ancient (80's era) proprietary manufacturing files to modern ones.
The funny thing about examples like this is that they mostly show how dumb and inefficient the market is with many things. This has been possible for a long time with, you know, people, just a little more expensive than a Claude subscription, but would have paid for itself many times over through the years.
Now with Claude, it's easy to make a quick and dirty tool to do this without derailing other efforts, so it gets done.
However possible it was to do this work in the past, it is now much easier to do it. When something is easier it happens more often.
No one is arguing it was impossible to do before. There's a lot of complexity and management attention and testing and programmer costs involved in building something in house such that you need a very obvious ROI before you attempt it especially since in house efforts can fail.
I wonder how much of the benefit of AI is just companies permitting it to bypass their process overhead. (And how many will soon be discovering why that process overhead was there)
Same story with data models, let's say you have the same data (customer contact details) in slightly different formats in 5 different data models. Which one is correct? Why are the others different?
Ultimately someone has to solve this mystery and that often means pulling people together from different parts of the business, so they can eventually reach consensus on how to move forward.
How is an AI supposed to create documentation, except the most useless box-ticking kind? It only sees the existing implementation, so the best it can do is describe what you can already see (maybe with some stupid guesses added in).
IMHO, if you're going to use AI to "write documentation," that's disposable text and not for distribution. Let the next guy generate his own, and he'll be under no illusions about where the text he's reading came from.
If you're going to write documentation to distribute, you had better type out words from your own damn mind based on your own damn understanding with your own damn hands. Sure, use an LLM to help understand something, but if you personally don't understand, you're in no position to document anything.
When an AI can email/message all the key people that have the institutional knowledge, ask them the right discovery questions (probably in a few rounds and working out which bits are human "hallucinations" that don't make sense). Collect that information and use it to create a solution. Then human jobs are in real trouble.
Until that AI is just a productivity boost for us.
One thing that's interesting is that their original Salesforce implementations were so badly done that I could imagine them being done with an LLM. The evergreen stream of work that requires human precision (so far, anyway) is all of the integration work that comes afterwards.
Could you share any data on this? Are there any case studies you could reference or at least personal experience? One order of magnitude is 10x improvement in cost, right?
We are currently sunsetting our use of Webflow for content management and hosting, and are replacing it with our own solution which Cursor & Claude Opus helped us build in around 10 days:
So, basically you made a replacement for webflow for your use case in 10 days, right?
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.
Their initial answer/efforts seem to be a qualified but very qualified "Possibly" (hah).
They talked of pattern matching and recognition being a very strong point, but yeah, the edge cases tripping things up, whether corrupt data or something very obscure.
Somewhat like the study of MRIs and CTs of people who had no cancer diagnosis but would later go on to develop cancer (i.e. they were sick enough that imaging and testing was being ordered but there were no/insufficient markers for a radiologist/oncologist to make the diagnosis, but in short order they did develop those markers). AI was very good at analyzing the data set and with high accuracy saying "this person likely went on to have cancer", but couldn't tell you why or what it found.
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...
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.
I think I saw it asserted that its easier for a new company, which definitely makes sense as you don't carry along all the baggage.
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.
Many larger enterprises do both – buy multiple SaaS products, and then have an engineering team to integrate all those SaaS products together by calling their APIs, and build custom apps on the side for more bespoke requirements.
To give a real world example: the Australian government has all these complex APIs and file formats defined to integrate with enterprises for various purposes (educational institutions submitting statistics, medical records and billing, taxation, anti-money laundering for banks, etc). You can't just vibe code a client for them – the amount of testing and validation you have to do with your implementation is huge–and if you get it wrong, you are sending the government wrong data, which is a massive legal risk. And then, for some of them, the government won't let you even talk to the API unless you get your product certified through a compliance process which costs $$$. Or, you could just buy some off-the-shelf product which has already implemented all of that, and focus your internal engineering efforts on other stuff. And consider this is just one country, and dozens of other countries worldwide do the same thing in slightly different ways. But big SaaS vendors are used to doing all that, they'll have modules for dealing with umpteen different countries' specific regulations and associated government APIs/file formats, and they'll keep them updated since they are forever changing due to new regulations and government policies. And big vendors will often skip some of the smaller countries, but then you'll get local vendors who cover them instead.
And that's just atlassian.
Start adding stuff that costs many many many yearly salaries (special software for managing inventories and warehouses) it starts making sense to prototype alternatives internally.
I came to the conclusion that if it's not Teams/SharePoint or the moat is on the extreme legal complexity side (e.g. payrolls), you can at least think of building an alternative that is good enough without needing to be perfect.
You also know how neglected those on-perm instances were?
No one updated those, no one wanted to pay for more CPU/RAM. File storage, I know people who had some random requests to cleanup files from projects because company wouldn’t buy more hard drives. Everyone was nagging at sys admins that they do bad job and at Atlassian that JIRA sucks.
That is mostly why Atlassian pulled off on premise because companies would not update at all, would like to have all new features and also not pay for file storage,RAM, CPU to make it work well.
Don’t forget you still will need to have dedicated employees to deal with AI built solution - because existing employees have work to do.
What we pay for JIRA and Confluence would never offset fact that we pay and it works, NOT A SINGLE EMPLOYEE CARES as they have their job to do.
Where would we be without them!?
All instances I remember seeing were neglected, not updated running on lowest amount of resources. Everyone in company nagging how slo it is but no one wanted to share budget to improve it.
So for me that experiment „it will be better and cheaper building our own JIRA” was already done. It is going to be cost center that no one will want to throw money at.
It would be hard to do worse. A packet of crayons and a scrap of paper is better than JIRA.
Pretty soon you're just re-implementing Jira while your users wait and get pissed because they could have just been using Jira all along. It's just like turning a spreadsheet into a webapp, inevitably you just end up trying to re-implement Excel.
> "...but in jira that was already there"
Must be a different Jira from the one I'm used to, where obvious features are never there and even if you can find the button it doesn't work.
Also, it allows you to pick and choose what you want from where.
We’ve just completed the first month of our internal CRM that has replaced about 500$ a month in subs with something that flows much better and enforces our own internal processes.
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.
why do people pay red hat/ibm for rhel? they earn pretty good margins too. to parent's point on software/=code
Because the guy who signed the purchase order had a good time golfing?
My buddy works for a company like these. He landed a $5M contract last year, which netted him almost $800k. There's alot of fat to be cooked out of this stuff, and AI will help smaller entrants attack those margins.
AI-based startups like Vanta make it much easier for companies to meet the compliance bullshit the large companies require. Again, it will drive more competition == better values for customers.
truer words have never been spoken. I work in some of these platforms and lead teams of developers who write customizations. These customizations are not rocket surgery, basic CRUD with some logic requirements that can't be met ootb. It's very time consuming and therefore expensive to clients. The significant moat incumbents have is brand recognition and trust. On the other hand, a hot new "Agent First" consulting firm at 1/3 the price would be hard for a director to not at least experiment with.
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
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.
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.
In the olden days it would have taken considerable engineering effort to produce a comparable tool. That is no longer the case.
For everything else, there’s open source.
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.
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.
If that's their fear they don't know much how your typical big businesses functions.
You've dealt with a large, consumer bank? Many of them still run on IBM mainframes. The web front end is driven by pushing buttons and screen scraping 3270 terminal emulators. You would think a bank with all it's resources could easily build it's IT infrastructure and then manage all the technology transitions we've gone through over the past few decades. Clearly, they don't and can't. What they actually do is notice they have to adapt to the newfangled IT threat, hired hordes of contractors to do the work, then fire them when done. After it's done they go back to banking and forget all the lessons they've learnt about building and managing IT infrastructure.
If you want to see how banking and computers should be combined, look at the Fintech's, not banks. But for some reason I don't understand traditional banks still out compete Fintech's. Maybe it's getting your head around both banking and running an IT business it too much for one human mind?
That same pattern is repeated everywhere. Why was everyone so scared of Huawei? It wasn't because they built the gear. It's because the phone telco's have devolved into marketing and finance companies who purchase in the gear from companies like Huawei and rent it out. Amazingly they don't know how to run the gear they purchased, instead get the supplier to install it and maintain it. But that meant what some eyes viewed as an organ of the Chinese communist party was running the countries phones with full access to every SMS and voice call. (Interestingly, IBM pulled the same stunt with the banks back in the day: you didn't buy an mainframe, you leased / rented it from IBM, and they maintained it.)
It's the same story everywhere I look. These big firms stick to the knitting. If you want to see total, utter incompetence in IT go work whose core business doesn't revolve around IT for a while. These are the firms that still choose Microsoft, despite the fact they've seen Sony's Microsoft based IT infrastructure torn apart so badly by North Korea they didn't know who their employees were, how much they owed creditors or how much debtors owned them for a while. Why do they choose Microsoft? Look around - who else allows you to outsource the know how about connecting millions of computing devices in 1000's of offices to a redundant cloud infrastructure that allows them to share data while providing a centralised authentication / authorisation infrastructure. There is only one choice, apart from developing it themselves which is out of the question.
If those businesses did start using what passes for AI today to manage and develop their own IT infrastructure, the result would not be pretty. But for all the shit I'm throwing at them here, I'm confident they are smarter than that. They know their limitations, they haven't done it before, and they won't start doing it now.
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.
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.
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.
Some stuff in companies might be similar, but there's a lot of things that people use every day, in a lot of different ways, and the software needs to work correctly regardless. You can't just drop it like a hot potato once you've built processes around it.
As always, the first 80% takes 20% of the time/effort, the last 20% takes the other 80%.
I've been in ops for a long time and have encountered far too many "our IP addressing plan is just a spreadsheet with manual reconciliation".
I truly wonder if Excel and all it's predecessors and direct clones (Google Sheets, etc.) are holding back industry from making something truly better and more reliable.
What "industry"?
If you are talking about the software industry, then I'd say you are creating a circular reasoning. If you are talking about all the other things that we actually need to do and which only incidentally have become too reliant on software to do it, then see back my original point: people don't need "better and more reliable" software to keep running their businesses.
But if the competitors have real software engineers and have used them to actually improve reliability, you'll be left behind.
- A facilities management company
- A bar/restaurant with a staff of 8
- An Architecture office
- A Law Firm with 10 associates
- A day care
- A car repair shop
- A cement factory
- A family-owned hotel
- A conference/event organizer
- A video production crew
- A roofing companyBut 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.
Here are the p/e ratios of companies mentioned in the article, after the said "pummeling":
* ServiceNow - 70.66
* SAP - 28.70
* Salesforce - 28.15
* Workday - 73.16
* Microsoft - 26.53
So they range from "a bit high" to "still completely bonkers".
You can't realistically replace that with some LLM solution (in the near-term at least) and they can use the AIs to reduce their costs which is mostly people.
Windows 11 though...
At the very least, the stock looks to have shot up for most of the launch month with the peak not occuring until July 18th and the stock still being significantly higher at the end of the month https://finance.yahoo.com/quote/NTDOY/history/?period1=14673...
I think the funniest bit of pure confusions was "Zoom Technologies (ZOOM)" being mistaken for "Zoom Video (ZM)" at the start of the pandemic to the point the SEC halted its trading on concerns around the confusion being the only reasonable driver. https://markets.businessinsider.com/news/stocks/zoom-technol...
What has changed most dramatically is the "fixed" cost of writing the software to begin with. Given that the costs were being spread out over so many units beforehand, it's not entirely clear to me how that changes a lot of the economics.
For the comments about the "SaaS vs build your own", we can use a home services metaphor. Sure, I can do a lot of what my plumber does. But they do it faster, know all of the issues that go wrong with the work and I can pay them a yearly fee to check my boiler to make sure it doesn't fail etc. The time saved by calling the plumber can then be spent with kids, more work or a combo of the two.
Their lead has shrunk, and thus so has their value.
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.
That's not the situation we're talking about though. It's someone saying "hmm, I need to edit this picture. Can I get ChatGPT to do it?" where 3 years ago they would have had to buy Photoshop and learn how to use it.
Similarly, if they need a tool to batch-convert a thousand images, they're getting an LLM to construct the specific tool they need in a couple of hours and then running that, rather than buying a software product that can do it.
You don't need a whole dev team to build a one-off tool for a specific job, which is probably 90% of the demand for those software products. LLMs are becoming the general-purpose tool for a lot of use cases.
Yup, same reason you can't throw manpower at a software project and expect a proportional outcome (Brooks's Law). AI amplifies what's already there; it doesn't conjure taste or product vision out of thin air.
I expect the markets are reflecting that soon there will be more competition.
It'll take time, and as LLMs improve, it'll take even less time.
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.
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?
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.
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.
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.
Market Cap over doubled between 2021 and 2025.
But since the start of 2025, it has lost all of that.
13% in the last week. 20% in the last month. Six months is definitely bleaker than those numbers, 37% down.
The interesting thing I've noticed is software library authors could take a beating though. Quite a few libs in the .NET world have gone down the monetized paths, for all of the ones I've been using, I've just got AI to remove them and implement native solutions. But none of these are large listed companies.
Take Adobe for example: they're getting pummeled and there's no way it's due to AI
No-one's building an in-house Photoshop clone to replace them
AI also isn't letting any competitors in. Geez if it were as easy as cloning their product you'd have a mile high mountain of VC money to fund it even pre-AI
Code has never been much of a barrier to entry
If you're holding say a total market index fund, or s&p500, or even qqq or many tech index funds, this would get hidden by the so-far very good growth on other tech stocks.
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.
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.
Where have I seen this before? Oh right, the entire site, for months now. Nothing suspicious about that at all, I'm sure a swarm of other brand new accounts will reassure me 0.1 microseconds after being created. You guys sure do type fast!
GOOG is up 70% over the last year.
"Pummelled" seems extremely sensational...
MSFT is only up 3% over the last year
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.
> The value of listed American enterprise-software companies is down by 10% over the past year.
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?
It's just correction.
however those system of record apps - will outlast most "A.I" companies - since the effective data is within their systems
Google "Project Genie" which allegedly can take your input and the AI will make it rain, drove investors into panic mode. They think that you can create GTA6 like that.
It was the perfect storm: clueless investors + the whole AI bubble already bursting if you are following non-biased news.
Of course such an angle would require much more research on behalf of the journalists for much less spotlight than what you would get for free by just singing to the tune of AI-doomerism.
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.
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 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.
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.)
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.
"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.
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
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
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.
Are there any software products that you think will survive?
Having worked in healthcare, this is the current state (per provider, not physical building).
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.
IE, before software automates a business process, it's typically done by hand, by a real person.
What if someone sells a "virtual person" that's capable of doing the job? What if that "virtual person" is harder to train than a real person, but orders of magnitudes easier than writing custom software or custom business rules?
More importantly: What if the "virtual person" can explain the job they do much better than trying to read source code? That's very useful in ~30ish years when the "virtual person" understands the business process better than the people in the company, and someone is trying to update / streamline processes.