Instead of competing with OpenAI's mass-market ChatGPT, Anthropic focuses on the enterprise market. By prioritizing safety, reliability, and governance, it targets regulated industries like finance, legal, and healthcare, creating a defensible B2B niche as the "enterprise safety and reliability leader."

When evaluating AI startups, don't just consider the current product landscape. Instead, visualize the future state of giants like OpenAI as multi-trillion dollar companies. Their "sphere of influence" will be vast. The best opportunities are "second-order" companies operating in niches these giants are unlikely to touch.

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.

Instead of building generic chatbot wrappers, entrepreneurs should target high-value niches by building tools on top of specialized AI models. For example, creating an 'AlphaFold wrapper' could create a multi-billion dollar company by serving the specific workflow needs of pharmaceutical companies and research labs.

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.

Simply using AI provides no competitive advantage, as it's a widely available tool. A true, defensible moat is created by combining AI's capabilities with your unique domain expertise, proprietary processes, and established relationships. AI should augment your existing strengths, not replace them.

YC Partner Harsh Taggar suggests a durable competitive moat for startups exists in niche, B2B verticals like auditing or insurance. The top engineering talent at large labs like OpenAI or Anthropic are unlikely to be passionate about building these specific applications, leaving the market open for focused startups.

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.

A VC offers an analogy for competing with AI giants like OpenAI: they are 'Godzilla.' Instead of direct confrontation, startups should 'find an alleyway to hide in.' This means focusing on niche applications or non-software domains where they won't be 'stomped' by inevitable foundation model improvements.