Connected LLMs Pattern
As large language models (LLMs) become increasingly integral to modern AI systems, the need to move beyond monolithic architectures has grown more urgent. Traditional approaches, whether standalone models or retrieval-augmented generation (RAG) systems, offer powerful capabilities but suffer from inherent limitations in flexibility, scalability, and specialization. The “connected LLMs” pattern introduces a new paradigm: linking multiple LLMs, often with distinct roles or areas of expertise, into cooperative and orchestrated systems.
This chapter explores the motivations, architectures, enabling technologies, and advanced design patterns behind connected LLM systems, offering a roadmap for building the next generation of modular, intelligent AI solutions.
