Traditional SaaS is like a ready-made shirt—cheap and fast, but ill-fitting. The founder argues AI makes custom-fit software that adapts to each enterprise's unique processes cheaper and faster to deploy than one-size-fits-all SaaS, disrupting the entire software stack.

Previously, building bespoke software for niche internal problems was too expensive. AI agents dramatically lower this cost, allowing companies to create custom-fit solutions for 99% of their problems, ending the era of contorting workflows to fit generic, off-the-shelf tools.

Frustration with a mediocre, AI-lacking vendor drove the decision to build a custom replacement, even when a commercial option existed. This signals a major vulnerability for incumbent SaaS players who fail to innovate with AI, as customers may choose to build rather than renew.

A new trend sees AI-native companies leveraging their own AI-assisted developers ('vibe coders') to create internal software that replaces their subscriptions to commercial SaaS products. This represents a significant threat to the traditional SaaS business model, as companies opt to build rather than buy simple tools.

The barrier to creating software is collapsing. Non-coders can now build sophisticated, personalized applications for specific workflows in under an hour. This points to a future where individuals and teams create their own disposable, custom tools, replacing subscriptions to numerous niche SaaS products.

Companies are now rejecting expensive SaaS contracts because their internal teams can build equivalent custom solutions in days using AI coding tools. This trend signals a fundamental threat to the traditional SaaS business model, as the 'build vs. buy' calculation has dramatically shifted.

AI trivializes the creation of internal tools, allowing early-stage companies to build bespoke Enterprise Resource Planning (ERP) systems. This enables unique organizational structures and process management far sooner than traditional buy-at-scale models.

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

Nimble small and medium-sized businesses will increasingly use AI to build custom internal tools, especially for CRM. They will opt to create the 20% of features they actually need, rather than pay for complex, expensive enterprise software where they ignore 80% of the functionality.