12-Factor Agents: Patterns of reliable LLM applications — Dex Horthy, HumanLayer

About this Video

• Video Title: 12-Factor Agents: Patterns of reliable LLM applications — Dex Horthy, HumanLayer
• Channel: AI Engineer
• Speakers: Dex Horthy
• Duration: 00:17:06

Introduction

This video discusses the 12 factors of reliable Large Language Model (LLM) applications, presenting patterns observed from numerous LLM-based applications. The speaker, Dex Horthy, aims to encourage viewers to rethink agent development from first principles, applying established software engineering practices for enhanced reliability. He introduces a GitHub repository containing the detailed 12 factors.

Key Takeaways

• LLMs as Pure Functions: LLMs are treated as stateless functions; input tokens determine output tokens. Reliability hinges on careful context engineering.
• Context Engineering: Managing context windows is crucial. Optimizing the density and clarity of information passed to the LLM significantly impacts output quality. Addressing errors and managing context are emphasized.
• Owning Control Flow: Instead of relying on implicit LLM control, the speaker advocates for explicit control of the agent's workflow using structures like loops and switch statements, enabling features like pausing, resuming, and breaking.
• Small, Focused Agents ("Micro-agents"): The speaker suggests building smaller, more manageable agents with limited steps (3-10) instead of large, complex ones. This improves reliability and allows integration of LLMs within deterministic workflows.
• Human-Agent Collaboration: Seamless integration with various communication channels (email, Slack, Discord, etc.) is vital for effective human-agent interaction. Early consideration of when human intervention is needed is recommended.