Seven Core Design Patterns Powering Modern Agentic AI Systems

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A software developer writing for DEV Community outlines seven recurring architectural patterns that underpin most agentic AI systems, arguing these structures do the real work beneath the industry hype. Key patterns include ReAct, where a model reasons and acts iteratively based on live observations, and Plan-and-Execute, which separates planning from action to allow human inspection before anything runs. The Reflection pattern improves output quality by having a model critique and revise its own drafts in a loop, while Tool Use emphasizes clean API design so models can compose actions effectively. Multi-agent orchestration splits large tasks among specialized workers coordinated by a central agent. The author stresses that understanding and naming these patterns helps developers recognize them across popular frameworks like LangChain and Claude Code.

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