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HU

humanlayer/12-factor-agents

AI Agent

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?

25k Stars1.9k Forks26 Open Issues25k WatchersTypeScriptNOASSERTION
LLM ToolAI AgentDeveloper ToolAutomationUI Framework
Source and compliance noteLast synced: Jul 21, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy
Editorial Evaluation

humanlayer/12-factor-agents is tracked as a TypeScript project in the LLM Tool, AI Agent, Developer Tool, Automation, UI Framework area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.

Momentum check: the repository has 25k total stars, with +49 today, +0 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.

Maintenance check: current activity is Inactive; the latest push was 303 days ago, and the open issue queue is 26, about 0.11% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.

Adoption check: 1.9k forks and 25k watchers suggest how often the project is reused or followed. License signal: NOASSERTION. Always verify license compatibility before commercial or internal use.

Practical fit: this project is most relevant when you need AI prototypes, LLM workflows, and agent-style applications. Be cautious when you require frequent releases or active maintenance.

Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 49. Follow the original GitHub repository for final install, security, and release information.

Best For
  • AI prototypes, LLM workflows, and agent-style applications
  • TypeScript teams evaluating ecosystem-native tooling
  • teams that prefer mature projects with broad adoption signals
Avoid When
  • you require frequent releases or active maintenance
  • you need a legal review, security audit, or production SLA
Adoption Signals

Momentum

25k Stars

Reuse

1.9k Forks

Attention

25k Watchers

Maintenance

inactive

License

NOASSERTION

Open issues

26

Overview

12-Factor Agents is a set of principles for building reliable LLM-powered applications, inspired by the 12 Factor App methodology. It provides guidelines for creating production-grade AI agents that are scalable, maintainable, and robust.

Key Features

- Defines 12 core factors for building reliable LLM applications, from owning prompts to stateless reducers. - Provides a visual navigation and detailed content for each factor. - Includes community contributions and discussions for practical implementation.

Tool Positioning

LLM Tool

Libraries and tools for LLM apps, RAG, prompts, and evals

AI Agent

Agent frameworks, autonomous workflows, and tool-use systems

Developer Tool

Tools that improve coding, testing, build, and local workflow

Automation

Workflow automation, integration glue, and orchestration

UI Framework

Frontend frameworks, design systems, and interface libraries

Quick Start
No installation required; the project is a guide. For the CLI tool, run `npx create-12-factor-agent` or `uvx create-12-factor-agent`.
View on GitHub
Project Activity

70

Health Score

Inactive

Commit Activity

Mar 30, 2025

Created

Sep 21, 2025

Last push

Source Trail

GitHub repository metadata

metadata

GitHub README

readme_summary

Star History

+0

Today's growth

+0

7-day growth

+0

30-day growth

Jul 21, 2026Jul 21, 2026
Community Health
1.9k

Forks

26

Open

25k

Watchers

Owner
HU

humanlayer

GitHub profile
Topics & Language
TypeScript12-factor12-factor-agentsagentsaicontext-windowframeworkllmsmemoryorchestrationprompt-engineeringrag
Ecosystem & Usage
GitHub Repository Search on npm
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License
NOASSERTION
CreatedMar 30, 2025
Last pushSep 21, 2025
Last syncedJul 21, 2026
Community Standards

✓

License

✓

Forked

✗ Inactive

Maintained

AI AnalysisAnalyzed by Git-Stars

Problem Solved

It addresses the lack of reliability and production-readiness in current agent frameworks by advocating for a software-first approach where LLMs are used as components within deterministic systems. This contrasts with the 'prompt + tools + loop' pattern that often fails in production.

Capabilities

Developers can build customer-facing AI applications that are reliable, scalable, and maintainable, such as customer support bots, code assistants, or data processing pipelines. The ceiling is high: any application where LLM capabilities are needed but must be tightly controlled and integrated with existing software engineering practices.

Bottom Line

This guide is for developers who want to build production-grade LLM applications without the fragility of current agent frameworks. It's not for those seeking quick prototypes or fully autonomous agents. The key trade-off is more upfront engineering effort for significantly higher reliability and maintainability.

Full AI Analysis