Comment by keiferski | Hacker News Reader

Comment by keiferski | Hacker News Reader

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I work for a SaaS and we recently had an interesting situation where we lost some smaller customers but are in the process of getting dramatically larger ones at the same time. As in, we lost some customers that were roughly 20-people companies, but gained some customers that are 100+-people companies. The ones we lost seem to have just built our solution in-house, presumably with AI helping.

Conventional wisdom would suggest the opposite: the big companies with more resources will obviously just decide to create their own internal version, whereas the small companies don’t have the time or resources to do that.

What actually seems to happen is that IMO if a team is nimble enough to copy a SaaS product internally, and doesn’t want to pay the $100-$1000 a month for your services, they’ll likely build it in house with AI.

However if the company is large enough, it’s coalesced into different departments with specific resources and plans, and ergo no one wants to give themselves a ton of new work when they can just outsource it to a SaaS and get corporate to pay for it.

Larger companies also have some other traits that lend themselves to prefer SaaS:

They usually need much more than an AI MVP product. They’ll tend to have a lot more different scenarios covered by one product category. For example, a small company looking for a PAM tool might only need to access Linux servers over SSH and PostgreSQL databases, while a large company might also have a mix of Windows servers, Oracle databases, and a complicated org structure with subsidiaries and acquisitions.

Large companies also need their SaaS tools to outsource compliance, not use pure functionality. They need to be able to tell customers “vendor XYZ handles ABC and they are certified under 123 standard.”

Finally, I also think larger companies, perhaps counterintuitively, have more of a cognitive limit or something you might call an aversion to a bus factor.

A small team with a more focused set of tools and products can more easily deal with something bespoke. Fewer people need to be able to work with something like that. Larger companies with bigger teams need to be able to tap into a labor market that can work with a more standardized toolset. Maybe they even deal with higher turnover.

1. If multiple companies use given SaaS, then "per company" cost is likely to be lower than in-house solution. Think of tools that have wide range of use cases, like Windows or Photoshop.

2. Even if SaaS has only one customer it might still be cheaper to outsource a project. Big companies tend to have lots of managerial overhead - a meeting where we discuss the prospects of designing a schedule of meetings to manage the plan of meetings. This cost might be higher than profit margin of a company consisting of five dudes and a tank truck of energy drinks.

Seen similar. They will be back when they realise the vibe coded SaaS run by two people in a trailer park isn’t what it looked like.

A lot of the big SaaS stuff isn’t code or product. It’s support and hand holding.

Your last phrase is bang in on the money.

Also the assurance it won't evaporate one day

Yeah we have actually have to prove to some enterprises that we have a certain level of staffing.

And AI cannot do support + hand-holding?

We did that and our customer satisfaction tanked and the query logs were full of "fuck off and tell me how to speak to someone". This was as I expected it would be.

You really think people will give you any respect or interest if you stick something between them and you? How

I'm one of the most pro-AI support/solutions/FDE engineers you'll find, and I really don't see AI taking away support and hand holding.

Even though I use AI to answer questions large customers would still rather wait for a weekly meeting to ask a question or have someone fly onsite then write the same question in an email or to a chatbot and get a near instant answer

Have you tried actually pretending to be human when replying to support? In many scenarios it leads to the same satisfaction

Smaller companies might either want to utilize their employees better, avoid ever increasing Saas subscriptions, while larger ones will just defer responsibilities on suppliers, it's just easier to blame your suppliers for any faults.

Smaller companies probably use a small subset of the features in the SaaS. This means one of two devs with an AI can implement the used subset fairly easily.

Bigger companies probably use more features and have more advanced requirements and the SaaS is integrated in different ways within different departments of the company. This means more developers are required, more interaction with different departments and thus less benefits of AI versus the traditional way of developing without AI (as the actual work is more in coordination, specification etc, than the actual coding bit).

That is, until a given SaaS becomes too greedy and someone identifies the core features people actually use, then spends a few weeks replicating them internally.

I think AI familiarity still varies a lot across companies and individuals. Small companies/startups often move much faster than large corporations, so that may also explain what you're seeing. Long before LLMs I worked at places where even monitoring solutions were implemented in-house because the vendors' pricing was extremely greedy.

My point is that I'm sure this will also change for some large corporations in the short to medium term. Not saying SaaS is doomed because it's obviously not and at the end of the day you want a battle-tested solution, but it does feel like the market will shrink.

> That is, until a given SaaS becomes too greedy and someone identifies the core features people actually use, then spends a few weeks replicating them internally.

I think a lot of SaaS are actually pretty safe, if only due to organisations desiring to make compliance someone else's problem.

We don't pay $$$ for a SaaS just because it would be time consuming to replicate it - we pay it because we'd rather not have to add the in-house replacement to our SOC2/HIPAA/GDPR compliance audit every year, and legal prefers it because there is someone else to sue if things go sideways in those areas.

Yeah, this is basically why I as a landlord have an agent who takes 10%+VAT just to know what the rules are and who to call when things go wrong, and then bills me on top for listing the property when empty, any works that need doing etc.

I'm aware of the responsibility shifting here but even then my point still stands. I've seen some SaaS companies tighten their grip thinking "they'll never bother because of the regulatory burden" only to watch large customers walk away and build in-house solutions instead. Super common? No, but this was pre-LLM and slightly later.

Compliance is an important factor in customer retention, but the cost of the other side of the equation (technical implementation) has dropped significantly and in some cases could be what tips the balance.

Greed and inefficiency is what define SaaS. Compare what Microsoft give you for 50 bucks per month vs Atlassian or any ticketing services. It's absurd. They can charge up to $80/month for what shouldn't cost more than $5.

Looking at some of the pricing and then multiplying it by 12 and ask question would you pay this for shrink wrapped software is bit eye opening. At least from not filthy rich Europen perspective.

Not to say that some products like MS aren't seemingly very good value. But on other side like chat and source control I do raise eye brow...

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