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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 founder predicts that hyper-specific vertical AI solutions are too easy to replicate. While they may find initial traction, they lack a durable moat. The stronger, long-term business is building horizontal tools that empower users to solve their own complex problems.
Ben Horowitz highlights that specialized AI companies like Eleven Labs are thriving despite foundational models having similar raw capabilities. This reveals a durable competitive advantage for startups: the significant effort required to transform a model's latent ability into a polished, developer-friendly product creates a defensible business moat.
The notion of building a business as a 'thin wrapper' around a foundational model like GPT is flawed. Truly defensible AI products, like Cursor, build numerous specific, fine-tuned models to deeply understand a user's domain. This creates a data and performance moat that a generic model cannot easily replicate, much like Salesforce was more than just a 'thin wrapper' on a database.
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.
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.
In the SaaS era, a 2-year head start created a defensible product moat. In the AI era, new entrants can leverage the latest foundation models to instantly create a product on par with, or better than, an incumbent's, erasing any first-mover advantage.
Despite the power of large foundation models from OpenAI and Anthropic, specialized AI companies like Cursor are succeeding. This suggests the AI market is a rapidly expanding pie, not a winner-take-all environment, where "transcendent" companies with superior product execution can capture significant value.
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.
Startups like Cursor that are built on foundation models face existential platform risk. Their supplier (e.g., Anthropic) could limit access, degrade service, or copy their product, effectively killing their business, much like the scorpion stinging the frog mid-river.
The common critique of AI application companies as "GPT wrappers" with no moat is proving false. The best startups are evolving beyond using a single third-party model. They are using dozens of models and, crucially, are backward-integrating to build their own custom AI models optimized for their specific domain.