Agentic Workflow Patterns
Agentic Workflow Patterns are standardized, reusable architectural designs that define how AI agents execute complex tasks, make decisions, and interact with systems and other agents. These proven patterns include sequential processing, parallel execution, conditional branching, feedback loops, and human-in-the-loop validation. Common orchestration patterns include prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer loops, ReAct (Reasoning + Acting), and multi-agent collaboration, each giving a structured way to break a complex problem into manageable steps. Chain-of-Thought sits on a different layer: it is a prompting technique used inside a single model call, not a workflow pattern. By implementing these established patterns, organizations can build more reliable, predictable, and scalable AI agent systems that consistently deliver business value while minimizing hallucinations and errors.
Related terms
Related services: AI agent development company, Agentic AI consulting.
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