Creating frontier AI models is incredibly expensive, yet their value depreciates rapidly as they are quickly copied or replicated by lower-cost open-source alternatives. This forces model providers to evolve into more defensible application companies to survive.

According to Box CEO Aaron Levie, the stickiest SaaS products are those with strong network effects, deep integrations, and mission-critical workflows. A simple heuristic for vulnerability: if you can get the same value from a fresh install as a decade-old one, your product can be easily replaced by AI-generated software.

The true threat to SaaS isn't just cheap software creation, but AI agents that automate data migration between platforms. This destroys the lock-in effect of proprietary data models, turning SaaS into a low-multiple utility business where switching costs approach zero.

The ease of building applications on top of powerful LLMs will lead companies to create their own custom software instead of buying third-party SaaS products. This shift, combined with the risk of foundation models moving up the stack, signals the end of the traditional SaaS era.

Unlike sticky cloud infrastructure (AWS, GCP), LLMs are easily interchangeable via APIs, leading to customer "promiscuity." This commoditizes the model layer and forces providers like OpenAI to build defensible moats at the application layer (e.g., ChatGPT) where they can own the end user.

The enduring moat in the AI stack lies in what is hardest to replicate. Since building foundation models is significantly more difficult than building applications on top of them, the model layer is inherently more defensible and will naturally capture more value over time.

Mobile networks built expensive global infrastructure with massive usage but captured little value as profits moved "up the stack" to apps. Foundation models, despite huge CapEx, face a similar risk of becoming a commoditized infrastructure layer with low pricing power.

The threat of AI models replicating SaaS features is real. Superhuman's defense isn't a superior core technology but a platform strategy. The bet is that users won't build their own tools if the platform offers a powerful network effect of pre-built, integrated agents that work everywhere, creating a defensible ecosystem.

Foundation models like OpenAI won't dominate the enterprise application layer. Similar to how AWS became infrastructure for a software explosion, LLMs will do the same for AI apps. Their core business and GTM motion is fundamentally different from what's required to sell complex enterprise solutions.