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While compound AI systems can offer clear benefits, the art of designing, optimizing, and operating them is still emerging. On the surface, an AI system is a combination of traditional software and AI models, but there are many interesting design questions. For example, should the overall “control logic” be written in traditional code (e.g., Python code that calls an LLM), or should it be driven by an AI model (e.g. LLM agents that call external tools)? Likewise, in a compound system, where should a developer invest resources—for example, in a RAG pipeline, is it better to spend more FLOPS on the retriever or the LLM, or even to call an LLM multiple times?

Extracted from: beyond-llms-compounds-systems-agents.md