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.

Alex Karp states enterprises are skeptical of AI ROI and fear that feeding data to frontier models from OpenAI and Anthropic trains these platforms to understand and eventually replicate their core business. This IP risk is a major hurdle for adoption, which Palantir positions itself to solve.

Anthropic is moving up the stack from model provider to application developer, putting it in direct competition with its own customers like Figma and Canva. It allegedly downplayed the capabilities of its new design tool to partners before launch, leading to broken trust and strategic fallout.

By building AI-native products like Cloud Code that compete with applications built on its API (e.g., Cursor), Anthropic risks alienating its developer ecosystem. The emergence of powerful, customizable open-source models like Kimi K3 now provides these developers with a viable off-ramp, threatening Anthropic's platform strategy.

Startups building on proprietary AI platforms like Anthropic or OpenAI face significant risk. The platform can analyze token usage, identify successful applications, and then launch a competing, integrated feature, as Anthropic did to its partner Cursor with Claude Code.

While AI platforms like Anthropic's Claude Science provide a common workbench, true differentiation for biopharma companies comes from the middle layer. This is where proprietary data, custom-built tools, and expert-guided queries create a competitive edge that the commoditized platform itself cannot provide.

Cursor once constituted up to 50% of Anthropic's revenue, but Anthropic later competed directly by launching its own coding product. This illustrates the extreme danger for application-layer companies building on foundational models that can easily move up the stack and become competitors.

Big pharma is heavily investing in AI-driven drug discovery platforms. Deals like Sanofi with Irindale Labs, Eli Lilly with Nimbus, and AstraZeneca's acquisition of Modelo AI highlight a strategic shift towards acquiring foundational AI capabilities for long-term pipeline generation, rather than just licensing individual preclinical assets.

Anthropic is creating its own medicines not just to enter pharma, but to gain hands-on experience using its AI products to solve real scientific problems. This internal R&D effort is a strategy to improve their core large language model for scientific use, potentially giving them a competitive edge.