For one thing, the threat model assumes customers can build their own tools. Our end users can't. Their current "system" is Excel. The big enterprises that employ them have thousands of devs, but two of them explicitly cloned our product and tried to poach their own users onto it. One gave up. The other's users tell us it's crap. We've lost zero paying subscribers to free internal alternatives.
I believe that agents are a multiplier on existing velocity, not an equalizer. We use agents heavily and ship faster than ever. We get a lot of feedback from users as to what the internal tech teams are shipping and based on this there's little evidence of any increase in velocity from them.
The bottleneck is still knowing what to build, not building. A lot of the value in our product is in decisions users don't even know we made for them. Domain expertise + tight feedback loop with users can't be replicated by an internal developer in an afternoon.
Nowhere near the level of complexity that would enter your threat model. But this would be the first, minimal step towards customers building their own tools, and the fact that not even this workflow has entered the zeitgeist is... well, it's not the best news for some of the most bullish projections of AI adoption in businesses large and small.
This is the answer to a happy B2B SaaS implementation. It doesn't matter what tools you use as long as this can be achieved.
In the domain of banking front/back office LOB apps, if you aren't iterating with your customer at least once per business day, you are definitely falling behind your competition. I've got semi-retired bankers insisting that live edits in production need to be a fundamental product feature. They used to be terrified of this. Once they get a taste of proper speed it's like blood in the water. I'm getting pushback on live reloads taking more than a few seconds now.
Achieving this kind of outcome is usually more of a meat space problem than it is a technology problem. Most customers can't go as fast as you. But the customer should always be the bottleneck. We've done things like install our people as temporary employees to get jobs done faster.
Yes, certain parts of our product are indeed just lightweight wrappers around an LLM. What you're paying for is the 99% of the other stuff that's (1) either extremely hard to do (and probably non-obvious) (2) an endless supply of "routine" work that still takes time (3) an SLA/support that's more than "random dev isn't on PTO"
Many SaaS products I am interested in have very little “moat”. I am interested in them not because I can’t build them, but because my limited engineering time is better spent building business specific stuff.
Many products with product management teams spend a lot of their effort building functionality either to delight their highest paying customers, or features that are expected to be high-revenue.
I’m never going to be your highest paying customers, so I’m never going to get custom work from you (primarily orienting workflows to existing workflows inside your customers).
What everyone wants when they buys SaaS is to get value from it immediately without having to change our internal processes, broken as they are. But your model of feature prioritization is antithetical to this; you don’t want to build or support the 5-10 integration points I want; because that would allow me to build my own customizations without paying for your upsells.
You aren’t at immediate risk from agentic Ai from losing your big customers. But Agentic AI is enabling me and thousands of others to build hobby projects that deliver part of your core value but with limitless integration. I expect that you’ll see bleeding from the smallish customers way before you see hits from your whales.
However in a couple of years there will be OSS alternatives to what you do, and they will only become more appealing, rapidly.
As a side note it’s not just license pricing that will drive customers to agentically-coded solutions; it’s licensing terms. Nowadays whenever I evaluate SaaS or open source, if it’s not fully published on GitHub and Apache or MIT licensed, then I seriously consider just coding up an alternative - I’ve done this several times now. It’s never been easier.
That's not the threat model. The threat model is that they won't have to - at some point which may not be right now. End users want to get their work done, not learn UIs and new products. If they can get their analysis/reports based on excels which are already on SharePoint (or wherever), they'd want just that. You can already see this happening.
As it stands today; just a bit of complexity is all that is required to make AI Agents fail. I expect the gap to narrow over the years of course. But capturing complex business logic and simplifying it will probably be useful and worth paying for a long time into the future.
Being unrestrained by team protocols, communications, jira boards, product owners, grumpy seniors.
They can now deliver much more mature platforms, apps, consumer platforms without any form of funding. You can easily save months on the basics like multi tenant set up, tests, payment integration, mailing settings, etc.
It does seem likely that the software space is about to get even crowdier, but also much more feature rich.
There is of course also a wide array of dreamers & visionairies who know jump into the developer role. Wether or not they are able to fully run their own platform im not sure. I did see many posts asking for help at some point.
Even if they could, the vast majority of them will be more than happy to send $20-100 per month your way to solve a problem than adding it to their stack of problems to solve internally.
The worry is that customers who do not realize the full depth of the problem will implement their own app using AI. But that happens today, too: people use spreadsheets to manage their electronic parts (please don't) and BOMs (bills of materials). The spreadsheet is my biggest competitor.
I've been designing and building the software for 10 years now and most of the difficulty and complexity is not in the code. Coding is the last part, and the easiest one. The real value is in understanding the world (the processes involved) and modeling it in a way that cuts a good compromise between ease of use and complexity.
Sadly, as I found out, once you spend a lot of time thinking and come up with a model, copycats will clone that (as well as they can, but superficially it will look similar).
The fallacy here is believing we already had all the software we were going to use and that AI is now eliminating 90% of the work of creating that. The reality is inverted, we only had a fraction of the software that is now becoming possible and we'll be busy using our new AI tools to create absolutely massive amounts of it over the next years. The ambition level got raised quite a bit recently and that is starting to generate work that can only be done with the support of AI (or an absolutely massive old school development budget).
It's going to require different skills and probably involve a lot more domain experts picking up easy to use AI tools to do things themselves that they previously would have needed specialized programmers for. You get to skip that partially. But you still need to know what you are doing before you can ask for sensible things to get done. Especially when things are mission critical, you kind of want to know stuff works properly and that there's no million $ mistakes lurking anywhere.
Our typical customers would need help with all of that. The amount of times I've had to deal with a customer that had vibe coded anything by themselves remains zero. Just not a thing in the industry. Most of them are still juggling spreadsheets and ERP systems.
AI-generated code still requires software engineers to build, test, debug, deploy, secure, monitor, be on-call, handle incidents, and so on. That's very expensive. It is much cheaper to pay a small monthly fee to a SaaS company.
I’m pretty certain AI quadruples my output at least and facilitates fixing, improving and upgrading poor quality inherited software much better than in the past. Why pay for SaaS when you can build something “good enough” in a week or two? You also get exactly what you want rather than some £300k per year CRM that will double or treble in price and never quite be what you wanted.
- anything that requires very high uptime
-very high volume systems and data lakes
-software with significant network effects
-companies that have proprietary datasets
-regulation and compliance is still very important
Then it dawned on me how many companies are deeply integrating Copilot into their everyday workflows. It's the perfect Trojan Horse.
The only named product was Retool.
Looks like we're headed back to the internal IT days of building customized LoB apps.
Spreadsheets! They are everywhere. In fact, they are so abundant these days that that many are spawned for a quick job and immediately discarded. In fact, the cost of having these spreadsheets is practically zero so in many cases one may find themselves having hundreds if not thousands of them sitting around with no indication to ever being deleted. Spreadsheets are also personal and annoying especially when forced upon you (since you did not make it yourself). Spreadsheets are also programming for non-programmers.
These new vibe-coded tools are essentially the new spreadsheets. They are useful,... for 5 minutes. They are also easily forgettable. They are also personal (for the person who made them) and hated (by everyone else). I have no doubt in my mind that organisation will start using more and more of these new types of software to automate repetitive tasks, improve existing processes and so on but ultimately, apart from perhaps just a few, none will replace existing, purpose-built systems.
Ultimately you can make your own pretty dashboard that nobody else will see or use because when the cost of production is so low your users will want to create their own version because they would think they could do better.
After all, how hard is to prompt harder then the previous person?
Also, do you really think that SaaS companies are not deploying AI themselves? It is practically an arms race: the non-expert plus some AI vs 10 specialist developers plus their AIs doing this all day long.
Who is going to have the upper-hand?
Then this project lets you generate static sites from svelte components (matches protobuf structures) and markdown (documentation) and global template variables: https://github.com/accretional/statue
A lot of the SaaS ecosystem actually has rather simple domain logic and oftentimes doesn't even model data very well, or at least not in a way that matches their clients/users mental models or application logic. A lot of the value is in integrations, or the data/scaling, or the marketing and developer experience, or some kind of expertise in actually properly providing a simple interface to a complex solution.
So why not just create a compact universal representation of that? Because it's not so big a leap to go beyond eating SaaS to eating integrations, migration costs/bad moats, and the marketing/documentation/wrapper.
> But my key takeaway would be that if your product is just a SQL wrapper on a billing system, you now have thousands of competitors: engineers at your customers with a spare Friday afternoon with an agent.
I think it’s pertinent to point out that a lot of SaaS products are aimed at businesses and individuals who don’t have engineers at all.
AI agents aren’t going to disrupt the SaaS market for software intended for businesses like small business retail where the owners and staff have minimal technical knowledge and zero extra time.
I also think that some SaaS products are so cheap that about an hour of effort is too much. Is it worth a month of effort to vibecode a Dropbox alternative? Even some pretty complicated software that is untouchable by agents and engineers’ side projects like the Microsoft 365 suite and Jira are priced at under $20/month/user.
On the other hand, some entrenched solutions that aren’t all that complicated could be finding themselves with new, smaller competitors.
Going back to the beginning, I think we just lack good tools for other cases where agents could be used. Copilot is not great, chatgpt alone lacks some features to use it for business as is. I think what will happen is that we will see a lot more new tooling pop up that relies on agents in niche markets which will just amplify the power users. It will be another category of SAAS the companies will adopt.
You do not want to have to plan out a system with 800 unique requirements yourself. It takes a ridiculous amount of work, and you are then stuck maintaining it.
It’s never been about the difficulty of programming, it’s been about the pain of designing and maintaining.
SaaS maintenance isn't about upgrading packages, it's about accountability and a point of contact when something breaks along with SLAs and contractual obligations. It isn't because building a kanban board app is hard. Someone else deals with provisioning, alerts, compliance, etc. and they are a real human who cannot hallucinate that the issue has been fixed when it hasn't. Depending on the contract and how it is breached, you can potentially take them to court and sue them to recover money lost as a result of their malpractice. None of that applies to a neural network that misreads the alert, does something completely wrong, then concludes the issue is fixed the way the latest models constantly do when I use them.
What Iam seeing is that customers are delaying purchases of large expensive software. Prime example; SAP. ECC migrations to SaaS model RISE/GROW-PublicCloud are stalling, same with onprem S4 to RISE. I see a whole bunch of my customers instead go with retaining the core but modernize surround apps with intelligent custom apps without feature bloat. For now, SAP/oracle/whatever remains the system of record, the edges are going away. I guess the same is likely happening in other spaces.
This change is coming. Definitely. The current moats around SaaS will fall and the alternate ecosystem might not have moats at all.
But that does leave a weird gap where SaaSes that took a lot of time to make but can now be handled by an Ai won't survive either. If the business stays hand-coded it costs too much to be viable, if it moves to Ai it looses any advantage over doing it youself.
The problem is, nobody knows how much and how fast AI will improve or how much it will cost if it does.
That uncertainty alone is very problematic and I think is being underestimated in terms of its impact on everything it can potentially touch.
For now though, I've seen a wall form in benchmarks like swe-rebench and swebench pro. Greenfield is expanding, but maintenance is still a problem.
I think AI needs to get much better at maintenance before serious companies can choose build over buy for anything but the most trivial apps.
Oh, child.... building is easy. Coordinating maintenance of the tool across a non-technical team is hell.
As for Retool, I see the several waves of low/no-code products, the current one being LLMs, as repeated attempts to get non technical idea-guys to build their ideas. Where they all fail, and this is fundamental to the problem they're trying to solve, is that idea-guys' ideas crack when meeting reality. And neither Retool nor LLM fix that.
When it comes to SaaS that's industry specific, I just don't see it'll be that much of a change any time soon. I've worked heavily in the engineering industry and the security requirements that get put upon anything are nuts. It is difficult to enter this market, ISO compliance is important, even being in the cloud is a barrier for some customers, and often the type that you have no choice but to contract with if you want to make a profit because of their outsized importance in the market.
When I speak to customers, they actually quite often have tried to build something themselves. Usually it's been an intern or grad trying to make their life easier. Often it's spreadsheet based, but some go as far as knocking up little Python web apps. In one company I interned in they had a shadow PHP app. They often have a small 'data science' team that has struggled to get access to the data they need. While they can often get something that does the barebones of the tasks, and can do it well, where they fall down is that they're vulnerable to security issues and can't navigate their internal company politics to get permission to host things in the cloud and make their life easy, plus they don't have the experience to know what's good practice. I don't see AI changing things that much in that.
A couple of them mentioned that they plan to cancel subscriptions totaling more than $100k/year for the apps they will replace with that SaaS. According to them, they have many subscriptions they keep only because of one feature. Another issue is that their workflows become a real mess when they need to copy and paste data into multiple tabs. Custom-built internal tools seem like an obvious solution. Those who migrate to custom-built tools, however, will face the challenge of orchestrating their lifecycle and creating a consistent deployment workflow, but this is one of the challenges we are trying to solve at UI Bakery.
In my understanding, SaaS products that provide customers access to proprietary data are in a much better position than other SaaS platforms. HubSpot’s acquisition of Clearbit a couple of years ago now makes even more sense because it will help them retain some of their clients.
This practice predates even SaaS.
I read this article expecting to see a specific SaaS that was at risk, and the most I saw was "dashboards." (Which: dashboards frequently aggregate data, while the ongoing work of collection/maintenance/etc. is done by more complex applications.)
The thesis seems to be that companies can use coding agents to build one-off internal versions of SaaS apps like e.g. Workday or Salesforce or Slack or Jira or MixPanel or HubSpot. Which, if one could make such a thing for free and maintain it for free, why not?
Fortunately/unfortunately depending on where you sit, magical thinking isn't going to get Claude Code to build Workday, regardless of the quality of your AGENTS.md. Sometimes I wonder if the people who write these takes have spent any real time using Claude Code. It's good, but please be realistic.
This is inevitable, you can't rely on user licenses as a growth metric
Experienced developers have the humility to understand that there are always roadbumps and risks in building a system in a domain we do not understand, and therefore paying another company with expertise can often be worth it. Obviously some SaaS companies are better than others, which is why there is an evaluation process.
It does not surprise me (unfortunately) that proponents of using AI agents for everything minimize the value of actual lived experience in working in a given domain.
With AI, that equation is now changing. I anticipate that within 5 years autonomous coding agents will be able to rapidly and cheaply clone almost any existing software, while also providing hosting, operations, and support, all for a small fraction of the cost.
This will inevitably destroy many existing businesses. In order to survive, businesses will require strong network effects (e.g. marketplaces) or extremely deep data/compute moats. There will also be many new opportunities created by the very low cost of software. What could you build if it were possible to create software 1000x faster and cheaper?"
Paul Bucheit
Our customers ask for about AI features and it’s a constant struggle to explain to them that they just aren’t there yet.
All you've done is swapped a SaaS built for your problem domain with another, more expensive SaaS that has no support at all for your actual problem. Why would anyone want that? People buy SaaS products because they don't want to solve the problem, they just want it fixed. AI changes nothing about that.
The optimistic angle nobody's exploring: maybe 'eating SaaS' means we finally escape the subscription hellscape where every basic function costs $29/month. If an AI agent can stitch together free/cheap APIs instead of forcing you into Notion/Airtable/Whatever, that's not destruction—that's evolution.
It wasn't even a coherent grammatically correct sentence that I entered and it busily went to work building the site I had in mind.
It's not hard to imagine that in the next 2-3 years, anyone will be able to build personalized apps on request.
This is the key point. Sure, you don't have the chops to be able to replicate the SaaS product locally with Claude/Gemini, but you don't have to, because you're no trying to make a product that can handle N+1 workflows.