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Roman Chernin argues that if the AI market consolidates into a few dominant players, infrastructure companies like Nebius lose their value-add software stack and become simple commodity providers. A diverse ecosystem of builders is essential for their long-term viability.

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Nebius's talks to acquire AI21 reflect a broader trend where NeoClouds (e.g., CoreWeave) are buying software companies. This strategy aims to create a full-stack platform, offering more than just compute power, thereby increasing customer stickiness and diversifying revenue streams beyond commoditized hardware rentals.

Contrary to fears of a monopoly, the AI market is heading toward a diverse ecosystem. The proliferation of open-weight models and specialized tooling allows companies to build and control their own differentiated AI systems rather than simply renting intelligence token-by-token from a handful of large labs.

AI models are commoditized, but the ecosystem of tools, services, and compliance standards is increasingly complex. The example of needing nine Azure services for only 39% NIST compliance highlights this. Companies offering a consolidated, simplified path to value will hold a significant competitive advantage.

Nebius's competitive edge is full vertical integration. By controlling the stack "down" to building its own data centers, it gains cost and speed advantages. By building "up" with software platforms, it accesses enterprise markets that competitors focused on raw compute cannot.

While network effects drive consolidation in tech, a powerful counter-force prevents monopolies. Large enterprise customers intentionally support multiple major players (e.g., AWS, GCP, Azure) to avoid vendor lock-in and maintain negotiating power, naturally creating a market with two to three leaders.

The middle layer of the AI stack (software infrastructure for data movement or frameworks) is a difficult place to build a company. Foundation models are incentivized to add more capabilities from below, leaving little room for defensible platforms in between applications.

Value in the AI stack will concentrate at the infrastructure layer (e.g., chips) and the horizontal application layer. The "middle layer" of vertical SaaS companies, whose value is primarily encoded business logic, is at risk of being commoditized by powerful, general AI agents.

The threat of AI models replicating SaaS features is real. Superhuman's defense isn't a superior core technology but a platform strategy. The bet is that users won't build their own tools if the platform offers a powerful network effect of pre-built, integrated agents that work everywhere, creating a defensible ecosystem.

The enormous scale of Meta's deal with specialized data center operator Nebius proves that "NeoClouds" are now critical infrastructure players. They are successfully competing with hyperscalers by offering specialized services and, crucially, available capacity, making them essential partners for AI giants.

As AI models become commoditized, a slight performance edge isn't a sustainable advantage. The companies that win will be those that build the best systems for implementation, trust, and workflow integration around those models. This robust, trust-based ecosystem becomes the primary competitive moat, not the underlying technology.