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.

Users can now prompt an AI to build a custom version of a SaaS tool, tailored to their exact needs. This marks a shift towards personal, disposable software, which increases software's abundance while simultaneously eroding the moats of traditional SaaS businesses.

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.

AI will democratize software development to the point where building your own custom apps becomes commonplace. Instead of settling for one-size-fits-all solutions, people will create "personal software" perfectly tailored to their specific workflows, like a custom workout tracker.

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.

Traditional enterprise software is a usability compromise designed for everyone. LLMs move beyond simple personalization (showing relevant data) to full individualization, creating unique interfaces and experiences for each user based on their role and context, finally solving the 'mega menu' problem.

AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.

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.

Non-technical users are leveraging agents like Moltbot to build their own hyper-personalized software. By simply describing a problem in natural language, they can create internal tools that perfectly solve their needs, eliminating the need to subscribe to many single-purpose SaaS applications.