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12-Factor Agents is a conceptual engineering guide that defines a set of principles for building reliable, scalable, and maintainable LLM-powered applications. Inspired by the original Twelve-Factor App methodology, the project reframes best practices specifically for agentic systems and AI software. It outlines patterns such as treating prompts as first-class assets, owning the context window, and converting natural language into structured tool calls. The repository emphasizes operational discipline, arguing that even as models improve, strong engineering patterns remain essential for production-grade AI systems. Rather than providing a traditional framework, it serves as a strategic blueprint that teams can apply to their own agent architectures. The guide is especially useful for developers moving from experimental prototypes to robust, customer-facing AI products. Overall, 12-Factor Agents functions as an architectural manifesto for professionalizing LLM application development.
Features
- Twelve principles for LLM system design
- Focus on prompt and context ownership
- Guidance for production-ready agents
- Tool-calling and control flow patterns
- Scalability and reliability best practices
- Framework-agnostic architectural guidance
Project Samples
