AI companies built to fill feature gaps on top of foundation models are at high risk. As core models rapidly improve, they often absorb these adjacent features, disintermediating the "wrapper" companies. Their early-adopter customers are also the quickest to switch to better tools.

Startups building on OpenAI or Anthropic APIs face a major platform risk. Their usage data trains the underlying foundational models, enabling the platform owners to eventually absorb their features natively and make the startups obsolete.

Specialized SaaS companies like Writer and Intercom are moving beyond simply wrapping OpenAI or Anthropic APIs. They are now training their own foundation models to create more defensible, vertically-integrated AI products, signaling a shift away from platform dependency toward bespoke AI stacks.

The "bitter lesson" of AI applies to product development: complex scaffolding built around model limitations (like early vector stores or agent frameworks) will inevitably become obsolete as the models themselves get smarter and absorb those functions. Don't over-engineer solutions that a future model will solve natively.

Similar to how blockchain protocols like Bitcoin and Ethereum accrued more value than the apps built on them, AI foundation models are getting 'fatter.' They are absorbing more capabilities, allowing users to perform complex tasks in a single step within the base model, reducing the need for specialized application-layer companies.

Counter to fears that foundation models will obsolete all apps, AI startups can build defensible businesses by embedding AI into unique workflows, owning the customer relationship, and creating network effects. This mirrors how top App Store apps succeeded despite Apple's platform dominance.

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.

The battleground for AI startups is constantly shrinking like the map in Fortnite. Foundation models like Anthropic's Claude are aggressively absorbing features, turning what was a standalone product into a native capability overnight. This creates extreme existential risk for application-layer companies.