AI is killing B2B SaaS

It’s not as far-fetched as people think. I see so many comments here doubting you can vibe code a full CRM or e-commerce SaaS, but a skilled AI-assisted programmer absolutely can, especially if they're aware of strong open-source alternatives already out there.

For Salesforce-like CRM, there's Twenty[0], a good-enough alternative. For Shopify-style e-commerce, Medusa[1] is a headless commerce platform.

The real power comes from using AI to study how these projects implement specific features (payments, inventory, customer dashboards, etc.) and adapt them to your stack. AI excels at finding the "seams" (those connection points where a feature ties into the tech stack) and grasping the full implementation. The trick is knowing precisely where the feature lives in the code (files, functions, modules), because AIs often miss scattered pieces otherwise. That's what I'm building at opensource.builders[2]: turning OSS repos into a modular cookbook with structured "skills" that point to exact details for reliable remixing and porting.

SaaS companies are forever beholden to raising their market cap, even in solved spaces like cart, payment processing, and CRMs. Most businesses run on CRUD apps anyway, and if your core app exposes an API, you can build any customization you need on top of it. People here discounting how valuable it is for a business to have the software that runs their business on a tech stack they understand and something they truly own.

[0] https://github.com/twentyhq/twenty

[1] https://github.com/medusajs/medusa

[2] https://opensource.builders

Of course it has, but it's more likely to happen when nobody is paying attention.

I'm sorry but the amount of companies that need something like DataDog is quite small compared to their 30,000+ customer count. Maybe 5,000 companies on Earth truly need something like DataDog, 80% of their customers would be perfectly fine with a self hosted instance of grafana.

Using an open source self hosted solution should be the industry standard, encouraged position, by default. Our industry does not gain overall from using DataDog but only from truly open source solutions that utilized AGPL licenses that allows everyone to move forward together + share lessons together + contribute together toward a common goal of better observability.

Why are we acting like it's hard to set up? This isn't the 1990s, it's 2026. Tooling has gotten quite good over the last decade.

Also corporations stupidly spend money all the time, they over spend too. I recently left a company that was paying SalesForce $10mil a year in licenses when only 8 people in the entire 3,000 person company was using it. I doubt that was the only single instance across our industry too. There is a massive amount of waste and graft in enterprise sales.

I honestly doubt it if you replaced grafana for 10,000 DataDog customers they would notice the difference.

Lot of places that I see AI disrupting - I'm not buying that SaaS is going to be a significant one.

Reading through the article:

> They were paying $30,000 to a popular tool3

Couple things we needed to understand here:

  - How large is the client company
  - Is that $30,000/month or day or hour....

If it's a technology company of > 1000 employees - then $30,000 month doesn't even get Finance's attention. And there is next to zero chance that anyone is going to vibe-code, deploy, support and run anything in a 1000 person+ company for $30,000 a month. SaaS wins hands down.

Any product/service that people care about comes with a pager rotation - which is 6-7 employees making > $200k/year. If you can offload that responsibility to a SaaS for < $1mmm/year - done deal.

All those things are true. It still doesn’t sound like 1000+ engineers at 350k/yr.

What actually happens in a startup is you encounter these problems one at a time as they arise.