The initial reaction I think most people have to this is "SaaS companies/devs are in trouble."
I actually think the opposite is true.
With an outpouring of vibe-coded apps/SaaS, you have the new wave of vulnerabilities/leaks/problems that happen even with the best software. Except now, it's worse because it's being done on platforms "built" by people who haven't the slightest clue how they work.
One of many examples: https://dig.watch/updates/women-only-dating-app-tea-suffers-...
This I imagine will, over time, erode trust in most apps/SaaS products. With that erosion of trust will come skepticism and with that, will come trust in the "old faithful" of SaaS products/companies. Basecamp is a good example of this.
I could be wrong on this one, but it seems to me those that have built credibility for privacy/security/competence will become more valuable in the AI age, not less.
You know what's funny, less than a week ago I signed up for Basecamp.
Could I have asked Codex/Claude to whip me up a Basecamp clone with the exact features I want?
Of course. Do I want to deal with managing that codebase, even with AI? No.
The problem has been solved and the $15/mo. is well worth the time I will save not having to deal with managing that codebase and can instead focus my attention on things that bring in revenue.
From a market perspective bundling this into SaaS players is more efficient.
But: AI might enable niche applications which were to expensive to capture thus far
Earlier if you had developers and no domain knowledge you were able to land a contract building application for a company and maybe spin it off to get more customers in that niche.
If you got lucky and you landed law firm and made case management for them you probably had nice little niche.
But as it turns out lawyers can also use JIRA, Trello, Basecamp or whatever and they really don't need Facebook for lawyers so those gigs dried up.
Main point is, software development alone is not going to bring as much money as it did earlier. You will have to have backing of domain experts to get the business going to offer something special in your SaaS. Like possibility to actually have call with those domain experts or their oversight on whatever it is you are doing but you not having budget or enough work to hire domain expert full time.
I agree with you that is incorrect.
With AI, not everyone needs a SaaS.
They can make a bespoke tool for themselves with 5% of the SaaS features they actually need. If it's only used by authorized, internal, users and never exposed to the outside, many of the risks you mention disappear.
That's not to say everyone will vibe-code their Slack replacement, but a bar for relying on an external SaaS vendor will go up (and I think that's a good thing).
People want to outsource some things. Thats what markets are for.
The internet will become even more scammy and noisy.
Hence trusted vendors will be like beacons, and not drown.
Replacing SAAS isn't about building a replacement services 1:1. It's about figuring out what you actually needed in the first place! Often we only use a tiny fraction of what the full-blown SAAS offers. IOW it's about eliminating the service entirely and building something that fits your actual needs, rather than following what some VC thinks your needs are.
AI or not, the "build vs buy" pendulum is now swinging hard to build. And IMO that's a real opportunity to consolidate, trim some fat, and actually apply engineering practices rather than just blindly signing up for every SAAS that crosses your path.
DIY software is "free" like a free yacht is free. It initially looks appealing but there's a lot of expensive hidden costs and upkeep and pitfalls and problems.
For one, this is a bad assumption:
> building something that fits your actual needs
Unless your business is very small and not growing, this is a moving target. Your needs are going to change as you grow and different groups in the org are going to have different needs.
You really don't want to be dicking around creating software that already exists instead of doing the shit that actually makes you money. Spending a few hundo thousand on a bunch of software is nothing, you spend that on one engineer.
You buy a SaaS product because you have a problem and want to throw money at someone else to deal with it.
You also have to factor in that bespoke software is... bespoke. ie. much more suited to your org's use-cases than the primary solution is. Way less bloat. Way less vulnerability when you don't need an enterprise SaaS solution and instead can host on your private networks.
And as far as security considerations: Imagine you had a separate Opus 4.6 agent tasked with managing and monitoring and updating devoted to a specific slice of vulnerabilities. Of course this is highly inefficient, but it would take care of the vast majority of vulnerabilities that even enterprise SaaS have. This is simply a scaffolding issue at this point, not model ability. Scaffolding issues like this will continue to dominoe.
How much of that is better models, and how much is it AI companies throwing more resources at each one? E.g. larger context windows and higher token/s correlate with the better models.
Yet I will still pay for a plumber. I wonder why.
Even today it can probably find a lot of issues automatically. With basic knowledge of what to look for, it certainly helps in understanding data flow too.
That means we'll see even more niche apps, and more custom apps.
That doesn't mean everyone becomes a builder.
It means that the people who can build can now do so much more cheaply. Custom apps that were previously too expensive may now be cost-effective.
Nobody is going to ask Chat GPT to write them an app. They'll just ask something like "show me all the nearby restaurants that don't have any shellfish products for allergic reasons and let me browse like on ubereats", and Chat GPT will (eventually) do the right thing.
People will just see some UI, which will be like many UIs they've seen before. They won't care whether that UI is some UberEats embed designed by a programmer in California, or something that Chat GPT just came up with on the spot to wrap some API.
"Eventually, everybody is going to use computers" was a ridiculous thesis in the age of mainframes. It was a slightly less ridiculous (if still unlikely) thesis in the age of minicomputers. In the DOS days, it started to look likely, in the Windows days, it seemed inevitable, iOS and Android is what made it actually happen.
Sounds just like the bespoke software product companies and consultants out there.
It’s not about personal software it’s about how 1-3 people team will deliver a SaaS that actually works at scale for the 1/10th of the price.
In terms of personal software, he’s absolutely right, it’s great for hobbyist and things like in house tooling but that’s it.
If you don’t need 1M investment to start a business than tons of people will start those business around the world, and guess what some of them will be truly good, and people will use different tools, interoperability etc. will be much easier to solve with AI, so locking is not big deal, workflow integrations not big deal.
All of it will take time but surely will happen.
Is this already happening?
Shouldn't it be?
> In terms of personal software, he’s absolutely right, it’s great for hobbyist and things like in house tooling but that’s it.
That much is true.
The biggest problem is discoverability, doesn’t matter what you built if you cannot advertise it won’t matter. But there a lot fields where enterprise SaaS is 5-10K, if you cans build the same product and sell for 1K and make profit yet it will work. And just to be clear this is already working in tons of enterprise markets, there are small players who follows this strategy but this time 1-3 people will able to follow this strategy instead of 20, which is a game changer and will change the market forever. Not all but most big enterprises going grow much slower, and valuations will crash. It might take 2-5 years though, it’s just nature of SaaS, it takes a while to slow 100mph train.
If they're not doing it now, why would they do it when they have to build it, too?
The world these investors are envisioning is not one where a software engineer gives a detailed spec to a model and reviews its output, deploys the resulting files and monitors said application. It’s where Jo-shmo at the law firm can tell the model “give me a new billing system”, and the AI does everything correctly and better than a team of software engineers, in a matter of minutes or hours. And that AI maintains it for them, better than the engineers would have
And you respond by saying that you can, but you need to do a _lot_ of work with him to spec this billing system out. You can't just build "a new billing system" without any more details. You tell him that this will take many hours of work between the two of you where you ask him questions, write a spec, get his feedback, and repeat that a number of times.
At this point, he says "wow, that sounds like a ton of of work for me just get started", and he gives up.
AI does not fix any of this, and this is the thing that I think most people will not want to do, and that's why I think this blog post is making a very good point. The amount of work it takes to build a new software system, even with a super competent programmer as a partner, is still quite significant. And it requires thinking about hundreds of tiny little details in a way that drives a lot of people nuts. They will only do it if they _really_ have to do it.
Clear and comprehensive Requirements are always the tricky bit, at least in business software. Twilight zone covered it perfectly and presciently decades before AI, with genies taking your requests literally and giving you unpredictable and usually negative outcomes.
Consultants are not spinning up a bespoke SaaS product given the risk.
Does every billing system need to be a one of a kind snowflake?
At best, if AI is supergenius enough to just intuit everything Joe needs, then the cost of running the AI to constantly maintain a billing system will far exceed the cost of just paying someone for their existing billing system SaaS.
Of course both models and tooling will need to be far more powerful for all this, but it doesn't exactly seem sci-fi to me.
Once system is built it could run detailed analysis on its usage and figure out what parts seem to be confusing or slow for users, and simply refine, deploy, keep analyzing, rinse and repeat.
The biggest upside is probably that workers could also simply request features, have Joe sign off on them (would get messy otherwise) and minutes later they actually roll out.
To me anyways most systems are a PITA because they do so much and your own organization only utilizes a small subset. Good systems actually let you turn off stuff you don't use so that users don't even know it's possible and don't have to drown in menu options, but that's still rare enough. And good luck getting dev focus on your specific requests regarding the parts of the system most important to your specific company, since there are a zillion other things and hundreds or thousands of other customers.
Something literally tailored to what you need will surely be the norm eventually. In five years or whatever I'm sure we'll be plenty on our way towards something like that.
But again just like LLM training in general this all requires having something existing to analyze and work off of. So yeah nobody will be going from paper to custom agent-built system.
But I think thats what the investors are envisioning.
We are way beyond the 90s-early 00s wild west where billing can be some random consultants opinions.
HN seems to attract a lot of weird gatekeeper contrarian takes
I think this is probably true, and basically how I got into software myself.
I always dabbled in writing software and things for the web, but for some reason I never thought studying computer science would be any fun and that a career as a software developer sounded boring. But then I got an actual full time office job and oh boy, did my perspective on things change fast.
That first job did not have anything to do with writing software at all. But I saw people struggle with things that seemed to me trivial to automate, such as making annotations on paper bank statements and entering them into the system line-by-line. The bookkeeping system did support electronic bank statements, but lacked features to match certain descriptions to certain cost places. In the end it was indeed faster to go the paper route... It took me a couple of hours to write something that saved hours every week and that basically kick started my software career.
Would AI have made much of a difference here? Yes, in terms of getting to the correct solution faster, but probably not in terms of who would have done that. People would still come to the person who came up with the solution to ask for maintenance and new features.
If one thinks AI can do this eventually then it makes sense. But I feel that is impossible the predict.
AI doesn't solve for ideas and product market fit. But it did allow me to fail pretty fast before I sunk too much time into it. But also, I should have spoken to potential users earlier rather than vibe coding.
https://claude.ai/share/be61468f-9f38-4dc0-aae3-5d758bf0f200
Possibly true, dependent on the service you use,
and the software space being evaluated.
Are any saas companies actually reducing their prices?
At the individual level, I think most people will be writing software, whether they realise it or not. Asking Claude to do something for you will often result in a purely generated script built for that one specific task. Some might even take it further, generating custom dashboards or whatever else they need to support their work.
At the company level though... most companies can hardly maintain opensource deployments, let alone write and maintain their own bespoke software. Pick any company that uses GitLab, they're probably a few major versions behind. It's across the board.
There's no doubt people will try to write more software.
But we've all seen how this plays out.
The smart engineer who built a weekend solution leaves, and nobody supports the software afterward. Coding agents certainly help, and only time will tell, but my bet is that for most organisations it will end up miserably.
I’m building an app and many things I’d normally pay for like metrics and emailing I can just do myself.
A friend has a law firm employing 100+ people and they are building so many internal tools they would otherwise be delaying or paying salesforce consultants for.
My current guess about the future is that the age of SaaS is coming stronger than ever. I expect many vibe coders to come up with half-assed prototypes that will be copiously replicated and improved by more qualified devs aided by LLMs. In a similar way, I also expect smaller qualified teams (3 to 5) to leverage LLMs to become more relevant competitors of medium to large SaaS players. By 2029, we'll have more, but smaller SaaS companies.
This of course will be software in general imho. It's not that the profession will disappear overnight. There is going to be this tight squeeze until all the margin/excess salaries/etc.. is gone. There is also going to be immense pressure to produce as much as possible and productivity expectations are going to go way up (even if it is unjustified).
Basically, the good days are over. It's going to be a miserable profession.
If you've already figured out what features are actually needed and which workflows work best, somebody can use AI to replicate those. This is the part of programming that AI is best at and accelerates most. The hard part, coming up with ideas, is far harder to copyright.
Bespoke sofware does exist. And yes, consultants small and large have built, deployed, and charged through the roof for bespoke software. And often it sucks. Here's why it sucks: because clients can't coherently describe what they need, don't have a budget, consultancies don't care and - critically - the person writing the spec (and controling the budget) isn't the same person that will use it. (here you also have "A Tragedy of EdTech" in one sentence, but that's a different post)
But there's another kind of bespoke software, which, for a lack of a better name, I'll unimaginatively call "internal tool". This is what VB6/Access/VBA/HyperCard enabled back in the day, what Retool tried to own recently, and what many Excel spreadsheets are secretly doing.
This is duct-taped-code-pasta that barely holds but does exactly what the business needs, and nothing more. I've seen and heard of many cases already of non-techies doing exactly that. It's not scalable, it's not maintainable, it doesn't follow best practices, it doesn't have tests or docs, but it doesn't matter, because it works and solves a biz problem.
The reason it works is that the person can iteratively narrow down to what they need, feedback is instant, iteration is minutes not days or weeks and is super cheap (compared to external developers).
No sane freelancer or agency would ship something like it - for many reasons: as a software engineer you want to ship quality product and charge appropriate amount of money. Many times, that's the right thing for the customers.
Often, it's overkill, and these types of smaller "quick win" projects never get started in the first place. And there's loads of potential projects like these!
So yeah, nobody will vibe-code a payroll system for 100+ person company, nor should they. But people absolutely will, and already do, whip up something that solves their niche problem. Now maybe they'll use AI instead of Excel.
Excel is 'free-at-point-of-use', i.e. once you've paid for it, to use it doesn't cost anymore. But LLMs do cost per use (unless we all go to local models). Either this cost is billed directly, or some sort of bundling occurs with 'fair use' limits.
Excel is deterministic, yes scary spaghetti-fied spreadsheets are routinely constructed, but, for example, sorting a result column somewhere can be done with a bit of poking in the right place. LLMs have a tendency to dangerously change many things if the prompting is a bit wrong (and even if it is a bit right).
Like that logistics company owner, he doesn't want to fill in your crappy insurance form, he wants to call insurance broker and have an insurance.
Doesn't matter if you put AI in the form, make 10% discount, polish UX to finest levels. He just doesn't want to spend time on it.
https://forstarters.substack.com/p/for-starters-72-vibe-code...
Self selecting biology gonna self select.
Which makes me think there's a lot more room for "virtual people." Imagine a very smart AI bot that could hold multiple conversations at once and remember a lot of things.
> So when someone suggests that AI means everyone will build their own custom tools, ask who "everyone" is. The three-person accounting firm drowning in client paperwork? They want the paperwork gone, not a new system to maintain. The regional logistics company with 40 trucks? They want the routes optimized, not Joe spouting off about this new system he’s been messing around with. The law firm billing 70-hour weeks? They want leverage on their time, not a software project to design.
What if there was a bot that was just smart enough to figure those things out, without needing traditional "software"?
To me, that's more what AI is, instead of adding chatbots to everything, and vibecoding everything.
which is essentially the direction that were heading in: we're sequentially and iteratively building improvements.
what the logistics company did pre computers and even pre trucks was not all that different in many aspects.
the future will be via evolution not revolution.
Ummmm, what? People love their smartphones, and do you know what those are?
Computers.
