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In the early days of applied AI, the pattern was simple: one model, one query, one response. As models have become cheaper, faster, and more specialized, a new architecture has emerged: multi-agent systems where multiple AI agents collaborate to solve complex problems. A multi-agent pipeline is not just multiple sequential API calls. It is a deliberate architecture where agents have defined roles, communication protocols, and orchestration patterns. When designed correctly, multi-agent systems achieve results that no single model can match—at costs that are often lower than monolithic approaches.
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