Modular intelligence: a human-like model for agent orchestration

Human language production offers a valuable model for designing modular AI agent architectures. This approach suggests separating complex tasks into distinct stages for reasoning, planning, and execution, mirroring established cognitive models of language. Adopting this modularity helps prevent issues like context drift and enables more robust, external self-monitoring to detect and repair errors. This architectural style ultimately produces AI systems that are more auditable, diagnosable, and easier to evaluate, as each component can be assessed independently.