Master AI Agent workflows to get reliable, high-quality outputs. Learn prompt chaining, routing, orchestration, parallelization, and evaluation loops.

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Medium

Five structured AI agent workflows are presented to replace ad-hoc prompting: prompt chaining breaks complex tasks into sequential steps, routing directs queries to appropriate models based on complexity, parallelization runs independent tasks simultaneously, orchestrator-workers use a planning model to coordinate specialized workers, and evaluator-optimizer creates feedback loops for quality improvement. Each workflow includes Python code examples and addresses specific use cases like code generation, content creation, and data analysis to achieve more consistent and production-ready results.

5 Agent Workflows You Need to Master (And Exactly How to Use Them)