The Death of the B2B SaaS Model

For the last decade, I followed the Golden Rule of Engineering:

If it isn't your core competency, don't build it.

Don't build auth. Don't build billing. And for the love of god, don't build analytics.

The logic was sound. It was based on a single, immutable constraint:

Developer time was the scarcest resource on Earth.

(And usually the most expensive.)

If you were a startup founder, asking your lead engineer to build a custom logging dashboard was a distraction. It meant pulling your best brain away from the product that actually made you money.

So, we happily handed over our credit cards to B2B SaaS Companies.

It was clear that wasting weeks of engineering time and creating more code to maintain was not the right call.

But now, the build vs buy math has fundamentally changed.

The scarcity of code is gone.

Vibe Coding (and I use this term generously) has driven the marginal cost of generating boilerplate code to near zero.

Think about what it actually takes to buy a B2B SaaS tool today:

• You have to compare a bunch of products that you can't actually try. This means sitting in lots of demos.
• You have to read pages of poorly-written documentation to do the integration or pay them extra for service support.
• You have to report issues and follow up to try to get them fixed.

That's "Buy".

Meanwhile, the "Build" workflow looks like this:

I open Cursor. I type: "Create a telemetry endpoint that logs user clicks in collection x in this new database. Don't use words like telemetry, events, analytics, etc."

(I will get back to this example in a bit, because I implemented this today.)

I hit Enter.

Done.

(Okay, maybe I prompted and tweaked for about 2 more hours until I was happy.)

You are not paying SaaS vendors for their technology or unique product.

You are paying them to so you don't have to "Build." But since AI removes the headache, the SaaS subscription is no longer such a "no-brainer" purchase.

It is a tax on orgs who don't vibe code.

And let's be honest, in this economy?

You can't afford not to.

The Historical Context: The Era of "Buy Over Build"

To be fair, we weren't idiots.

The logic of the build vs. buy was built on trauma.

We had all seen (or worked for) that one startup that imploded because the CTO insisted on building everything from scratch so that it's done "properly."

(We all know that person.)

After that trauma, we embraced a new philosophy:

Unless a feature aligns to the core benefits and mission of the org, AND can't be outsourced, only then should you build it.

(I remember doing many workshops about defining our core competency.)

It felt like the smart, mature play. We were outsourcing the boring stuff to the experts. We traded our scarce engineering hours for a monthly subscription fee, convinced we were getting the better end of the deal.

(And we were, if you compared the cost of paying an engineer to build/maintain vs. paying the subscription.)

So we kept doing it.

By 2023, the average vendor stack wasn't a selection of smart choices to augment the main product.. It was a Frankenstein monster held together by:

• Brittle Lamda functions.
• Overpriced Service Fees (just to move data from Tool A to Tool B).
• Webhooks that failed silently on Fridays at 11:45 PM.

(While the whole team was out drinking - except the tech lead - because the tech lead decided he wanted to know what all the fuss about microdosing was.)

We accepted this mess because of one lingering fear:

Maintenance.

The argument against "Build" was never really about the initial build. It was about the upkeep.

• "Who is going to patch this when the lead dev quits?"
• "Who is going to update the libraries?"
• "Who is going to wake up at 3 AM when the server crashes?"

Maintenance was the cage that kept us locked in the SaaS subscription model.

But here is the controversial truth about Build or Buy in 2026:

AI doesn't just write the code. It writes the tests. It writes the documentation. It debugs.

And if you can't maintain it, you can always rebuild it.

(Just keep your vibe coded stuff cleanly seperated - might be a good time for microservices to make a comeback.)

When the cost of maintenance drops near zero, the cage door swings open.

And we are finally realizing just how much rent we've been paying to live in it.

Here's my example from today: I built a bespoke analytics tool.

Why?

All the top analytics platforms get blocked by privacy browsers and AdBlock tools.

If you build a custom one that no one knows about, you can get all the user data.

If I even mentioned this solution 10 years ago, I would have been laughed out of the room.

The Analytics Example: Why "Build" is Suddenly Superior

Here is the dirty secret that Amplitude and Mixpanel won't tell you:

You are losing 30% to 50% of your data before it even leaves the user's browser.

Why?

Because ad-blockers, privacy browsers (Brave), and corporate firewalls are trained to kill known patterns.

They see a request to Segment's API or a GA Event Tag, and they block it immediately.

When you buy a SaaS analytics tool, you are inheriting their baggage. You are inheriting their domain reputation. You are painting a giant target on your back that says:

"Hello, I am tracking you."

But when you vibe code a bespoke solution, you are a ghost.

You aren't calling an external API. You are calling your own backend. And because you control the code, you can name the endpoints whatever boring, mundane thing you want.

Instead of POST /track-event, you name it POST /ui/sync.

(Who blocks a sync? Nobody.)

By leveraging the ideas behind Security by Obscurity, you bypass the privacy filters entirely.

You recover the data that your competitors (who are still paying $50k a year for "enterprise" analytics) are losing.

The End of "Tagging"

If you have ever implemented product analytics, you know the specific circle of hell that is "Tagging."

It usually goes like this:

• Marketing wants to track a button click.
• Product writes a Jira ticket.
• Engineering pushes back because the sprint is full.
• Two weeks later, the code ships.
• Marketing realizes they forgot to track the "Cancel" button.
• Repeat until death.

This workflow assumes that capturing data is expensive, so we must be selective about what we track.

But in a vibe-coding world, code is cheap.

In my implementation, I asked my AI buddy to write a global React wrapper for my app.

Its only job?

Indiscriminately vacuum every single user interaction.

Clicks, scrolls, hovers, inputs. It goes into a buffer and sends every few seconds.

I didn't define "events." I didn't tag "Sign Up Button." I just told the AI: "Log the DOM path, the timestamp, and the user ID for everything."

I looked at the first few examples it started collecting and it was so data rich, I knew I had enough to map out a detailed journey for every user. That means I could not just see what page or step they dropped off at, I could see what button they hovered over before they decided not to move on.

This shifts the entire paradigm.

We move from "Decide what to track" to "Capture everything, query later."

AI Is the Dashboard

Another barrier to "Building" analytics is the UI.

Nobody wanted to build a bespoke dashboard. Nobody wanted to mess around with D3.js or Chart.js to make a line graph look pretty for the CEO, only to have to continually tweak it until it's just right.

We paid SaaS vendors (partly) for their pretty charts.

But look at your workflow today.

Do you actually want to log into a dashboard, click through twelve filters to try to build a chart?

I know what I do - I export the CSV and hand it over to my little AI buddy.

(Julius AI is a great product for this. So I guess there's room for some B2B SaaS in this Brave New World.)

Anyway, when it comes to reports, all you want is answers.

The "Build" approach in 2026 argues that raw database logs + an LLM prompt effectively replaces the need for a polished SaaS dashboard.

I don't need a visualization UI. I have a text box.

I type: "Show me retention for users who signed up in March but didn't click the 'Upgrade' button. Outline the most common paths they took and how this is different from those who did."

The AI writes the SQL. I take a look to see that it makes sense.

I run the query and the AI Buddy generates several tables and charts.

The barrier to entry for building custom event tracking + analytics has collapsed.

The Compromise of SaaS we never really addressed

Because we didn't want to build all those non-core features, we never thought much about the downside of outsourcing all of this. At the end of the day, it was cheaper, even if not perfect.

The thing is though...

Every time I bought a SaaS tool, I was actively making my product worse.

That sounds dramatic. But hear me out.

When you buy a piece of software, you aren't just buying a login screen. You are buying a philosophy. You are buying a workflow designed by a Product Manager in San Francisco who has never met you, doesn't know your customers, and frankly, doesn't care about your edge cases.

SaaS is the "average" of 10,000 customers.

It is regression to the mean, packaged as a solution.

To use their tool effectively, you have to compromise. You have to bend your unique, competitive business processes to the way they do things.

(Or frankenstein a few tools together.)

You are warping your company to fit the tool(s).

In 2015, we accepted this because the alternative was building a CRM from scratch, which was insanity.

But in 2026? Insane things are starting to not feel so insane.

We are entering the era of Disposable Software.

In the old world, if you built an internal tool, it was a marriage. You had to support it forever.

In the new world, software is cheap enough to be single-use.

Need a tool to manage a specific influencer campaign?

Build it. Use it for two weeks. Delete it.

Need a portal for vendors to upload invoices that validates against a specific regex?

Prompt it. Deploy it. People complain about missing features? Toss it and Rebuild it.

(Save your initial prompts, friends.)

The "Buy" mentality forced us to search for the "Swiss Army Knife" ie one giant platform that did everything. (poorly)

The "Build" mentality gives us a drawer full of scalpels.

Sharp. Precise. And yours.

The barrier isn't technical anymore. It's psychological.

We have to get over the idea that "real" software comes with a monthly invoice or a commitment to maintain it.

Because the best software for your business isn't for sale.

It's currently sitting in your clipboard, waiting for you to hit Paste.