The fear that large AI labs will dominate all software is overblown. The competitive landscape will likely mirror Google's history: winning in some verticals (Maps, Email) while losing in others (Social, Chat). Victory will be determined by superior team execution within each specific product category, not by the sheer power of the underlying foundation model.

Instead of relying solely on massive, expensive, general-purpose LLMs, the trend is toward creating smaller, focused models trained on specific business data. These "niche" models are more cost-effective to run, less likely to hallucinate, and far more effective at performing specific, defined tasks for the enterprise.

The "agentic revolution" will be powered by small, specialized models. Businesses and public sector agencies don't need a cloud-based AI that can do 1,000 tasks; they need an on-premise model fine-tuned for 10-20 specific use cases, driven by cost, privacy, and control requirements.

The AI industry is not a winner-take-all market. Instead, it's a dynamic "leapfrogging" race where competitors like OpenAI, Google, and Anthropic constantly surpass each other with new models. This prevents a single monopoly and encourages specialization, with different models excelling in areas like coding or current events.

The AI arms race will shift from building ever-larger general models to creating smaller, highly specialized models for domains like medicine and law. General AIs will evolve to act as "general contractors," routing user queries to the appropriate specialist model for deeper expertise.

Initially, even OpenAI believed a single, ultimate 'model to rule them all' would emerge. This thinking has completely changed to favor a proliferation of specialized models, creating a healthier, less winner-take-all ecosystem where different models serve different needs.

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.

Block's CTO believes the key to building complex applications with AI isn't a single, powerful model. Instead, he predicts a future of "swarm intelligence"—where hundreds of smaller, cheaper, open-source agents work collaboratively, with their collective capability surpassing any individual large model.

Conventional venture capital wisdom of 'winner-take-all' may not apply to AI applications. The market is expanding so rapidly that it can sustain multiple, fast-growing, highly valuable companies, each capturing a significant niche. For VCs, this means huge returns don't necessarily require backing a monopoly.