Compound AI Systems
A compound AI system solves a task with multiple components — several model calls, retrieval, tools, and control logic — rather than a single prompt to a single model. Most real production AI is compound, which is why reliability is a systems problem, not a model problem.
Also known as: compound AI
A single call to a single model is rarely the whole product. A compound AI system wires together multiple pieces — several model calls, a retrieval step, tool use, validation, and the control logic that orchestrates them — into one pipeline that produces the result. RAG systems and agents are both compound by nature.
Naming the pattern matters because it relocates where quality comes from. When the system is compound, performance depends on how the parts fit together — the retrieval, the routing, the guardrails — at least as much as on the raw model. It’s why evaluation and observability have to cover the whole pipeline, and why swapping in a better model often helps less than fixing the system around it.