DIY Loop, LangGraph, or Custom Orchestration: How to Pick Your AI Agent Stack

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A developer who ships AI agents into production weekly has outlined a practical framework for choosing between three agent-building approaches in 2026: a DIY loop, a framework like LangGraph, and custom orchestration. The decision hinges on three factors — number of steps, concurrency requirements, and crash recovery needs. For simple agents with fewer than five tools and a linear workflow, a plain while loop in roughly 150 lines of Python is preferred and covers about 40% of use cases. LangGraph becomes the better choice when workflows involve significant branching, durable execution over hours or days, or multi-agent coordination. Custom orchestration on tools like Temporal or AWS Step Functions is reserved for the most complex, long-running, or mission-critical workloads.

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