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.

The one-size-fits-all SaaS model is becoming obsolete in the enterprise. The future lies in creating "hyper-personalized systems of agility" that are custom-configured for each client. This involves unifying a company's fragmented data and building bespoke intelligence and workflows on top of their legacy systems.

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.

Users are leveraging AI agents to build their own bespoke software, stripping away unused features from SaaS giants like Notion. This trend toward hyper-personalization threatens the one-size-fits-all SaaS model as users create cheaper, more effective personal tools.

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.

With AI, building custom internal tools for shallow, high-customization needs (like HR or payroll) is now cheaper and faster than buying and integrating third-party SaaS. This challenges the traditional 'buy vs. build' calculus for standard business functions.

In the future, it will be easier for businesses to build their own custom software (e.g., Salesforce) through prompting than to buy and configure an off-the-shelf solution. This shift towards "liquid software" will fundamentally challenge the one-size-fits-all SaaS model, especially for companies that currently rely on implementation partners.