A practical playbook for adopting AI coding agents in real engineering organizations.
Most teams are experimenting with AI coding tools. Few have a clear strategy for adopting AI agents in their development workflows.
This repository is a structured guide for engineers, architects, and engineering leaders who want to move from experimentation to repeatable adoption.
ā If this repository helps you, please consider giving it a star. It helps more teams discover the guide.
| Section | What's inside |
|---|---|
quick-paths/ |
Quick-start recipes ā short, actionable guides for common dev tasks with AI agents |
technical/ |
Training materials ā how agents work, prompt engineering, and agent-driven coding workflows |
repository/ |
Shared repository ā reusable solutions, patterns, ideas, and lessons learned from teams |
process/ |
The framework ā adoption process, team roles, maturity model, and rollout playbooks |
articles/ |
Analysis and comparisons ā adoption models, industry approaches, trade-offs |
This repository is intended for people involved in software engineering and AI adoption.
Typical readers include:
- Engineers evaluating AI adoption
- Developers experimenting with AI coding agents
- Software engineers designing AI-assisted development workflows
- Internal AI champions driving adoption initiatives
Many engineers today are asked to:
"Figure out how we should use AI for development."
This repository helps people responsible for designing and implementing AI adoption strategies.
It provides material useful for:
- understanding the challenges of AI-assisted development
- exploring adoption strategies
- learning from industry approaches
- preparing internal proposals or pilot programs
Start with the content in:
process/ā enterprise rollout and governancearticles/ā industry perspectives and adoption models
Teams already experimenting with AI tools can use this repository to:
- understand how AI agents change development workflows
- introduce structured agent usage
- avoid common pitfalls in AI-assisted coding
- design better collaboration between developers and AI agents
More practical guidance will be added over time.
Planned additions include:
- Benefits, limits, and risks of AI coding agents
- Reusable prompts, skills, and agent architectures
- Building agentic workflows
- Spec-driven development
- Internal AI adoption playbooks
and many more ...
Shipped by Agents on Facebook Updates, tips, and discussions around AI agents in software development.
Created by Alex Popescu ā solution architect exploring how AI agents are changing the way we build software.
CC BY-NC-ND 4.0 You can share with credit, but no commercial use or derivatives without permission.