The Boring Stack That Beats Every AI Agent Framework

Every AI agent framework promises to make agents easy. None of them do. The complexity just moves from your code to their abstractions. I've shipped production agents at Astraedus using LangChain, AutoGen, and CrewAI. I've also shipped agents with zero frameworks. The zero-framework versions are in production today. The framework versions got rewritten. Here's what I learned. The Boring Stack The boring stack is not a product. It's not a company. It's five things: A strong model (Claude Sonnet, GPT-4o, or similar) Well-designed tools (functions your model can call) A simple orchestration loop (while not done: think, act, observe) Structured output (Pydantic or JSON schema) Error handling (retry logic, fallbacks, logging) That's it. No graph state. No agent personas. No multi-layer memory abstractions. No "agentic frameworks." Just a model, tools, and a loop. Why Frameworks Add Overhead Every framework you add to a codebase is a dependency you now maintain. That's not an opinion, it's a