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After building his own voice-to-text tool, Hartman discovered that maintaining self-coded software requires substantial ongoing effort. He argues that paying for SaaS products is less about initial feature access and more about outsourcing continuous updates and model integration.
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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.
While AI can build an initial version of a software product instantly, the true, defensible value lies in the ongoing maintenance, support, and reliability. Customers will always pay for a product that is actively maintained and improved over time.
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.
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.
The current excitement around AI is fueling a “build it yourself” trend, echoing past tech cycles. This approach often overlooks the significant long-term costs of maintenance, versioning, security, and 24/7 support, which previously led companies to abandon homegrown systems for specialized vendors.
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.
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.
The fantasy of replacing a major SaaS platform like Salesforce with a custom-built tool ignores the total cost of ownership. Beyond initial development, the internal team becomes responsible for documentation, feature upgrades, security, support tickets, and user enablement—functions that are bundled with a commercial product.
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 ability to rapidly build custom software with AI is tempting. However, the ongoing maintenance and data quality assurance are the core business of SaaS companies. Buying a dedicated tool like a CRM often provides more value and less overhead than a custom-built solution, even with AI assistance.