> And vibe coding is fun. Even Bret Taylor, OpenAI’s chair, acknowledges it’s become a legitimate development approach.
Color me shocked! Bret, who directly profits by how his product is perceived, thinks it's legitimate???? /s
??? Do you mean biased or do you mean impartial?
A lot of companies have been too smart for that, and a lot of SaaS offerings are too small to be truly entrenched. Arguably the investment horizon is too short (IBM took decades getting to that point).
The only real vendors who managed to become the next IBM are the cloud providers.
I was surprised when I saw the numbers from Bloomberg myself as well!
Enterprise sales basically works like this: A non-technical sales team aggressively promises everything to win a deal to a non-technical procurement or exec team. When the deal is won, the SaaS sales team tells engineers "go build this" regardless of how stupid it is. And the customer tells their employees "you now have to use this SaaS" regardless of whether it makes sense.
Since when does stock price / valuation have to match actual business realities?
I feel like there's an interesting story in there.
Wrong take. You don't need to build something better, you only need something good enough that matches what you actually need. Whether you build it or not and ditch the SaaS is more of an economic calculus.
Also, this isn't much about ditching the likes of Jira not even mentioning open source jira clones exists from decades.
This is more of ditching the kind of extremely-expensive-license that traps your own company and raises the price 5/10% every year. Like industrial ERP or CRM products that also require dedicated developers anyway and you spend hundreds of thousands if not millions for them. Very common, e.g. for inventory or warehouse management.
For this kind of software, and more, it makes sense to consider in-housing, especially when building prototypes with a handful of capable developers with AI can let you experiment.
I think that in the next decade the SaaS that will survive will be the evergreen office suite/teams, because you just won't get people out of powerpoint/excel/outlook, and it's cheap enough and products for which the moat is mostly tied to bureaucratic/legal issues (e.g. payrolls) and you just can't keep up with it.
The sheer volume of data, the need for real time consistency in store locations, yada yada means that bad early decisions bite hard down the road.
Lots of drudge work can be assisted by AI, especially if you need to do things like in ingest excel sheets or spit out reports, but I would run far away from anything vibe coded as hard as possible.
I rather use Excel. It's likely More robust and safer than the vibe coded app that could trigger data loss / incorrectness / issues any time.
Let's put an example an exception-tracking SaaS (Sentry, Rollbar). How do the economics of paying a few hundred bucks per month compare vs. allocating engineering resources to an in-house tracker? Think development time, infra investment, tokens, iteration, uptime, etc. And the opportunity cost of focusing on your original business instead.
One would quickly find out that the domain being replaced is far more complex and data-intensive than estimated.
If you are selling SaaS consider that a vibe-coding customer is validating your feature roadmap with their own time and sweat. It's actually a very positive signal because it demonstrates how badly that product is needed. If they could vibe code a "good enough" version of something to get themselves unstuck for a week, you should be able to iterate on those features and build something even better in short order, except deployed securely and professionally.
Everyone's going to talk about how cool their custom vibe-coded CRM is until they get stuck in a failed migration.
but they don't want to. and they will be replaced, as it's good and well.
But, not sure which successful SaaS companies just stopped shipping any updates to the product, never talked to their customers and never added any new features to win over major new accounts - and still managed to survive and thrive?
And the author actually confirms this:
> AI isn’t killing B2B SaaS. It’s killing B2B SaaS that refuses to evolve.
Can you though? With major bugs? We've been getting more and more crashes, downtime, issues etc lately and a lot of it has had to do with vibe coding.
The whole point of these B2B SaaS is meant to be quality.
i.e. it's set users' expectations but in the wrong way.
You can shit out an app with AI, just like you could with Indian workers. But that doesn’t mean it will work properly or that you’ll be able to maintain it.
And most importantly, it only works for code they could steal from GitHub. It has no idea how to replicate sensitive systems which aren’t publically documented, and those are some of the most valuable contracts.
1) The must-haves. These are your email and communication systems, the things you absolutely have to have up and available at all times to do business. While previously self-hosted (Exchange/Sendmail, IRC/Skype/Jabber, CallManager/UCS), the immense costs and complexities of managing systems ultimately built on archaic, monolithic, and otherwise difficult-to-scale technologies meant that SaaS made sense from a cost and a technical perspective. Let's face it, the fact nobody really hosts their own e-mail anymore in favor of Proton/Microsoft/Google/et al shows that self-hosting is the exception here, not the norm - and they're not going anywhere regardless of how bad the economy gets. These are the "housing stock" of business, and there's plenty of cheap stock always available to setup shop in without the need for technical talent.
2) The juggernauts. The, "we can do this ourselves, but the pain will be so immense that we really don't want to". This is the area where early SaaS solutions cornered and exploded in growth (O365, ServiceNow, Google Workspaces), because managing these things yourself - while feasible, even preferable - was just too cheap to pass up having someone else wrangle on your behalf with a reasonable SLA, freeing up your tech talent for all the other stuff. The problem is that once-focused products have become huge behemoths of complex features that most customers neither need nor use on a regular basis, at least after the initial pricey integration. Add in the ease of maintainability and scalability brought by containers or microservices, along with the availability and reliability of public cloud infrastructure, and suddenly there's more businesses re-evaluating their relationships with these products in the face of ever-rising prices. With AI tooling making data exfiltration and integration easier than ever from these sorts of products, I expect businesses to start consolidating into a single source of truth instead of using dozens of specific product suites - but not toppling any outright.
3) The nice-to-haves. The Figmas, the HubSpots, the myriad of niche-function-high-cost SaaS companies out there making up the bulk of the market. Those whose products lack self-hosted alternatives risk having vibe-coded alternatives be "good enough" for an Enterprise looking to slash costs without regard to long-term support or quality; those who compete with self-hosted alternatives are almost certainly cooked, to varying degrees. If AI tooling can crank out content similar in quality to Figma and the company has tech talent to refine it for long-term use, why bother paying for Figma? If AI tooling can crank out a CRUD UI for users that just executes standard REST API calls behind the scenes, then why bother paying for fancy frontends? While it's technically interesting and novel at how these startups solved issues around scaling, or databases, or tenancy, the reality is that a lot of these niche products or services could be handled in-house with a container manager, a Postgres instance, and a mid-level IT person to poke it when things go pear-shaped. The higher per-seat prices of a lot of these services make them ripe for replacement in businesses comfortable with leveraging AI for building solutions, and I expect that number to grow as the tools become more widely available and IT-friendly in terms of security.
Ultimately, the core promise of SaaS to business customers was all the functionality with none of the costs of self-hosting support. Nowadays, many of them have evolved into solutions that are more expensive than self-hosted options, and businesses that have shifted IT into public clouds or container-based systems have realized they can do the same thing for less themselves, at the cost of some UI/UX niceties in the process. Now that we (IT) can crank out integrations with local LLMs with little to no cost, we're finally able to merge datasets into singular pools or services - and I'm not talking about Snowflake or its "big data" ilk so much as just finally getting everything into Salesforce or ServiceNow without having to bring in consultants.
The must-haves and many of the juggernauts will remain - for now. It's the niche players that need to watch their moats.
Charging hundreds of thousands if not millions per year for very basic functionality is what is "killing" b2b SaaS.
d_watt•1h ago
A given company or enterprise does not have to vibe code all this, they just need to make the 10 features with the SLA they actually care about, directly driven off the systems they care about integrating with. And that new, tight, piece of software ends up being much more fit for purpose with full control of new features given to company deploying it. While this was always the case (buy vs build), AI changes the CapEx/OpEX for the build case.
namanyayg•1h ago
bdcravens•1h ago
I'm pretty sure every developer who has dealt with janky workflows in products like Jira has planned out their own version that fits like a glove, "if only I had more time".
gritspants•59m ago