How to Build Production-Ready AI Agents (12 Factor Agents)

This is a deep dive into humanlayer/12-factor-agents, an open-source engineering guide for building reliable LLM-powered applications.

The repo applies the spirit of 12 Factor Apps to agent systems: prompts, context, tool calls, state, human approval, control flow, errors, focused agents, and reducer-style execution. It focuses on the engineering decisions that keep agents debuggable when real users depend on them.

Repo: https://github.com/humanlayer/12-factor-agents

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Chapters
0:00 Most AI Agents Break In Production
0:28 Twelve Production Rules For Agents
1:00 A Widely Shared Agent Engineering Guide
1:28 Agents Are Usually Product Code
1:51 The Agent Loop Needs Edges
2:13 Natural Language Becomes Structured Work
2:35 Prompts Belong In The Codebase
2:57 Context Is An Interface
3:19 Real Agent Work Has To Survive
3:42 Approval Is A First-Class Tool
4:03 Own The Loop Around The Model
4:24 Errors Need To Be Useful Context
4:46 Small Agents Are Easier To Trust
5:08 Reducers Make Agent Steps Explicit
5:29 Why This Stands Out
5:50 Who Should Care
6:13 Tradeoffs
6:36 What You Actually Build
6:59 A Practical Workflow
7:20 The Leverage Is Clarity
7:39 Agent Reliability Is An Engineering Choice

Видео How to Build Production-Ready AI Agents (12 Factor Agents) канала Build Things With AI