To survive against subsidized tools from model providers like OpenAI and Anthropic, AI applications must avoid a price war. Instead, the winning strategy is to focus on superior product experience and serve as a neutral orchestration layer that allows users to choose the best underlying model.

AI model providers like Anthropic analyze usage data from customers to identify lucrative verticals, then launch competing applications (e.g., Claude Design vs. Figma). This commoditizes their partners, posing an existential risk for developers building on these platforms.

The narrative that model providers will easily disrupt SaaS is flawed. Incumbents like Figma can integrate the same frontier models as challengers (e.g., Anthropic) while benefiting from their established products, distribution, and user trust, creating a level playing field on the core technology.

A vertical AI startup is extremely vulnerable if its core offering can be easily replicated by the foundational model it's built upon. True defensibility comes from integrating unique, proprietary data sources or solving non-obvious workflow problems that the base model cannot simply be prompted to do.

Gurley notes that major AI model providers like OpenAI and Anthropic are shifting from solely selling API access to building their own applications. This move up the stack signals a fear that being a pure model provider is not a defensible moat and could lead to commoditization.

Leading AI companies like Anthropic are positioning themselves as the infrastructure layer for intelligence, akin to how AWS provides infrastructure for computing. Their strategy is to partner with and enable existing SaaS companies, not to destroy them by competing directly at the application level.

A key risk for AI tools is that LLM providers like Anthropic (Claude) could build competing products. However, it may be more economically rational for these giants to serve as the underlying engine for many specialized tools, collecting fees without needing to build and market for every vertical.

In the AI era, defensibility comes from building a complex system of record, not just a thin wrapper on an LLM. Companies with a 'thick application layer' that offers standalone value are unattractive for model providers to replicate, whereas thin wrappers risk being absorbed by the platform they are built on.

Startups building on top of AI models, like coding assistant Cursor, are extremely vulnerable. As foundation model companies like Anthropic improve their own native capabilities (e.g., Claude Code), they can quickly capture the market and render specialized tools obsolete.