What is a compound AI system and why does it matter?
A compound AI system solves a task by orchestrating multiple components — LLMs, retrievers, tools, validators, classical code — instead of relying on one monolithic model call. The Berkeley AI Research group coined the term in 2024 and it now dominates production GenAI architecture in 2026. It matters because compound systems are easier to debug, cheaper per successful task, more grounded on live data, and more resilient when a model provider ships a new version. See /vs/compound-ai-systems-vs-monolithic-llm.
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Framework dimensions
Call this framework and its tools from your own agent via the Model Context Protocol (MCP) server. Works with Claude Desktop, Cursor, Zed, Continue, and the OpenAI Agents SDK.
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