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HCD Agile AIHuman-Centered Design meets Agile for AI

A meta-framework for implementing HCD with Agile in collaboration with AI agents

HCD Agile AI ​

Using an AI agent to follow Human-Centered Design with an Agile approach

This repository provides a meta-framework for implementing Human-Centered Design (HCD) with an Agile approach in collaboration with AI agents. The framework emphasizes shared vision, cross-functional collaboration (human-AI), and continuous validation.

About HCD Agile ​

HCD Agile is a methodology that combines Human-Centered Design (HCD) principles with Agile development practices. This approach ensures that software products are built efficiently and iteratively while meeting the real needs of users through continuous research, testing, and validation.

Key Principles ​

  • Empathy First: Understand users deeply through research and observation
  • Iterative Learning: Each sprint includes learning cycles about user needs
  • Continuous Validation: Test with real users frequently
  • Collaborative Design: Cross-functional teams work together throughout
  • Measurable Outcomes: Define success through user-centric metrics

What is it? ​

HCDAgile combines the empathy and user focus of Human-Centered Design with the iterative, collaborative approach of Agile development. This methodology ensures that teams:

  • Build solutions users actually need and want
  • Iterate quickly based on real feedback
  • Deliver value incrementally
  • Maintain quality and sustainability
  • Keep users at the center of all decisions

Learn more in the knowledge-base ReadMe.

Quick Start ​

Explore the comprehensive guides to understand and implement HCD Agile:

Reference ​

This documentation is based on industry best practices in Human-Centered Design and Agile methodologies. For additional context, see the archived 1904 Labs process page.

Contributing ​

We welcome contributions! Whether you have:

  • New Agent.MD templates for specific industries or project types
  • Examples from your projects
  • Improvements to existing guides
  • Feedback on the methodology

Please feel free to open issues or submit pull requests.

Released under the MIT License.