#74 · Primary category: Education & Research

12-factor-agents

12-factor 12-factor-agents agents ai context-window framework llms memory orchestration prompt-engineering rag

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

Project last updated:09/21/25

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Why we included this project

Most agent frameworks sell you a library, but this project treats LLM application engineering as a set of decisions you make yourself. It lays out twelve practices, each in its own chapter: own your prompts and context window, treat tools as structured outputs, unify execution and business state, and keep agents as stateless reducers. The value is that it gives you a vocabulary and a checklist to work through before you pick any framework, which is exactly what teams designing their own agent architecture need. There is also a scaffolding tool that generates a project already following the principles, so you can test the guidance instead of just reading it. If you are deciding how to structure a production agent, or you want one shared reference to get your team agreeing on what reliable means, this is a good place to start.

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