Introduction Generative AI has become a shared C-Level priority with many enterprises setting goals in their annual statement and numerous press releases. As Generative AI is gaining traction, there is much anticipation around their evolving model performance capabilities. However, as developers increasingly move beyond Generative AI pilots, the trend is shifting to compound systems. The SOTA results often come from compound systems incorporating multiple components rather than relying solely on standalone models. A recent study by MIT Research has observed that 60% of LLM deployments in businesses incorporate some form of retrieval-augmented generation (RAG), with 30% utilizing multi-step chains or compound systems. Rise of Compound Systems A Compound AI System addresses AI tasks through multiple interconnected components, including several calls to different models, retrievers, or external tools. AI models are constantly improving, with scalability seemingly limitless. However, com
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