What Are Agentic Workflows? Design Patterns & When to Use Them

Agentic workflows offer a dynamic approach to handling unpredictable processes by allowing AI systems to determine the next actions based on real-time context and feedback, rather than following a fixed sequence of steps as in traditional deterministic workflows. These workflows are particularly useful in scenarios like fraud detection, where the path to a solution is not predefined and requires adaptive decision-making. Agentic workflows involve a loop of planning, tool usage, reflection, and orchestration, with each step being informed by previous outcomes and current conditions. They differ from non-agentic workflows, which might use language models in a fixed pipeline, by actively using tools and iterating with feedback to achieve goals. By incorporating reusable design patterns such as planning, tool use, reflection, and orchestration, agentic workflows balance flexibility with control, offering reliability and adaptability in complex environments. Knowledge graphs enhance these systems by providing structured context and multi-hop reasoning capabilities, which improve retrieval precision and decision traceability.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.