Why Some AI Frameworks Feel Like Driving a Tank (And When You Actually Need One)

Why Some AI Frameworks Feel Like Driving a Tank (And When You Actually Need One) A practical guide to choosing between lightweight agent libraries and heavyweight orchestration frameworks—with code to prove the point. Why Some AI Frameworks Feel Like Driving a Tank (And When You Actually Need One) I spent three days last month setting up an AI agent framework to do something I could have built in 47 lines of Python. Three days of configuration files, dependency conflicts, and documentation rabbit holes—all for a tool that sends emails when my calendar looks busy. I'm not proud of it, but I'm also not alone. The AI framework landscape in 2025 looks like an arms race where everyone's building aircraft carriers and nobody's asking whether we actually need to cross an ocean. LangChain, CrewAI, AutoGen, Semantic Kernel—each one promises to be the "right" way to build AI agents, and each one comes with enough abstraction layers to make a simple task feel like enterprise architecture. Meanwhi