Practical AI Policy for Developers

I've been thinking... If you want your developers to move fast but safely then AI policy and governance can't just be an afterthought.

Here's what I've learned from helping organizations implement GitHub Copilot and other AI-powered tools, and why I believe every team should have a practical, living AI policy:

Let's face it: developers are already using AI, whether you've approved it or not. If you put clear guidelines in place, you get an actual chance to protect your code's security and integrity, steer productivity in the right direction, and help your team get the most out of these tools.

Security and Responsibility

Don't just list which tools are "allowed" - make it clear that code written by AI should meet the same standards as anything they'd write from scratch.

You want to give your devs access but remind them that they are responsible for any code merged. Understanding what the AI throws out isn't optional - it's critical to delivering safe software.

Governance, Not Gatekeeping

A policy shouldn't feel like a handbrake. It's a roadmap that keeps people focused on your business goals. Define the purpose, spell out everyone's responsibilities, and show how safe, responsible AI use advances your mission.

What to Include?

• Purpose: Why is this policy here? Remind folks code security and integrity are non-negotiable.
• Scope: Who's covered? Anyone touching generative AI.
• Responsible Use: Use AI to amplify, not replace, dev skill. All output is subject to review, regardless of who (or what) writes it.
• Intellectual Property: Avoid copy-paste pitfalls - use built-in features to avoid replicating public code.
• Validation: Mandatory code reviews for AI-generated output. Hold it to the same standards as your own work.
• Monitoring: Regularly check: Is this AI actually helping, or just creating extra work?
• Documentation: Keep track - who used AI, when, how, and why. Super helpful for learning and compliance.
• Training: Don't just "turn it on and hope for the best." Train your devs on both the tools and the policy itself.
• Review: Make it a living document. Tech evolves fast and so should your policy.

Real-World Impact

With the right training, you can even push concrete objectives like using Copilot to accelerate TDD feedback loops, not just "writing code faster." That's where policy and business objectives intersect.

Bottom Line

A thoughtful AI policy doesn't just keep you safe - it empowers developers, inspires trust, and helps everyone align behind best practices.

Do you already have an AI policy in place? What's worked (or not) in your org? Curious to hear other approaches!