Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via cosine similarity — is effective for unstructured semantic search.

The company formerly known as Intercom just did something that no major customer service platform has attempted at scale: it built an AI agent whose sole job is to manage another AI agent.