Most AI Agent Frameworks Are Overkill — Here's How to Choose the Right One in 30 Seconds

A senior engineer's field-tested breakdown of LangGraph, AutoGen, CrewAI, Microsoft Agent Framework, and Haystack — from reviewing real production systems across teams. Everyone is building AI agents right now. LangGraph. AutoGen. CrewAI. Semantic Kernel. Microsoft Agent Framework. But most production AI systems don't actually need an agent framework. Across multiple teams and production codebases I've reviewed, the same two failure modes appear constantly — over-engineering and under-engineering. In one case, replacing a complex agent framework with ~200 lines of plain tool-calling code made the system 3× faster, easier to debug, and easier to maintain. In another, the absence of a framework caused a codebase to collapse under its own complexity. Both failures had the same root cause: The problem isn't choosing the wrong framework. It's choosing a framework before understanding the workflow. This guide is the decision framework I now use before touching any agent tooling. TL;DR — Pick