Even if AI dramatically lowers coding costs, it won't destroy established SaaS businesses. Technical expenses only account for 10-20% of revenue for major SaaS players. The other 80% is spent on marketing, events, and client service, creating an opportunity for significant margin expansion.

Even tech-savvy users who build their own AI agents are increasingly turning to paid software. The ongoing cost and hassle of maintaining personal, "vibe-coded" tools makes polished SaaS solutions more attractive, demonstrating the enduring value of professional software development and support.

The idea that AI will kill SaaS is too simplistic. It most accurately applies to large, public companies with significant inertia whose existing moats are disappearing. Startups and growth-stage companies that can maintain a 'day one' mentality and constantly re-evaluate their product have a significant advantage.

As AI makes the software itself easier to build and replicate, the durable value of a SaaS company is no longer the code. Instead, the moat lies in the customer relationship, the proprietary data, the system of record it represents, and the deep understanding of user workflows.

SaaS pricing has always been determined by the value it delivers to customers, not its cost to build. While AI makes development cheaper and faster, it doesn't fundamentally change the value a product provides. Therefore, companies that solve important problems will maintain their pricing power and high margins.

Building a custom tool with AI to replace a SaaS subscription seems cost-effective, but building is only 10% of the work. The other 90% is the often-forgotten overhead of maintenance, on-call support, security, and bug fixes that SaaS vendors typically handle.

Despite predictions of SaaS's collapse, leading AI companies like OpenAI and Anthropic are still significant customers of traditional SaaS tools. This suggests that AI agents are augmenting, not completely replacing, established enterprise software.

With AI commoditizing code creation, the sustainable value for software companies shifts. Customers pay for reliability, support, compliance, and security patches—the 'never ending maintenance commitment'—which becomes the key differentiator when anyone can build an initial app quickly.

The fear that AI agents will kill SaaS is overblown. Corporations will not replace mission-critical, supported software with AI-generated code from junior employees. The need for vendor accountability, reliability, and support creates a durable moat for enterprise software companies.