The AI ecosystem will evolve into an "orchestration age" where large 'boss' models delegate tasks to a network of smaller, faster, specialized models. This means different chip architectures (e.g., NVIDIA for large models, Cerebras for speed) will function as complementary parts of a larger system, not just direct competitors.

AI will not evolve into a single, omnipotent entity. Due to fundamental limitations like context windows, AI will be structured like human organizations: a fleet of specialized agents with distinct roles (e.g., content, research). This mimics how humans partition work to manage complexity.

Moving beyond isolated AI agents requires a framework mirroring human collaboration. This involves agents establishing common goals (shared intent), building a collective knowledge base (shared knowledge), and creating novel solutions together (shared innovation).

The next evolution for autonomous agents is the ability to form "agentic teams." This involves creating specialized agents for different tasks (e.g., research, content creation) that can hand off work to one another, moving beyond a single user-to-agent relationship towards a system of collaborating AIs.

Complex AI development uses a pool of specialized agents. Like ants building a hill, some are workers, some are managers, and some review and discard bad code. This collaborative, layered system produces emergent results without a single orchestrator.

Building one centralized AI model is a legacy approach that creates a massive single point of failure. The future requires a multi-layered, agentic system where specialized models are continuously orchestrated, providing checks and balances for a more resilient, antifragile ecosystem.

Human intelligence leaped forward when language enabled horizontal scaling (collaboration). Current AI development is focused on vertical scaling (creating bigger 'individual genius' models). The next frontier is distributed AI that can share intent, knowledge, and innovation, mimicking humanity's cognitive evolution.

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.

A more likely AI future involves an ecosystem of specialized agents, each mastering a specific domain (e.g., physical vs. digital worlds), rather than a single, monolithic AGI that understands everything. These agents will require protocols to interact.