A structured route into AI-assisted development

Engineering leaders evaluating GitHub Copilot for their organizations face two distinct questions: what the tool can actually deliver, and how to bring it into a development workflow without friction. A new expert-guided GitHub Learning Pathway, built with engineering leaders from companies including ASOS, Lyft, Cisco, and CARIAD (a Volkswagen Group company), aims to answer both.

The pathway is designed for organizational leaders who need to make the business case for AI-assisted development and then manage the rollout. Its curriculum covers what a business can achieve with GitHub Copilot, how the tool handles data, what an effective AI governance policy looks like, and how to successfully deploy Copilot to developers.

What the pathway covers

The GitHub Copilot pathway is the latest addition to GitHub's Learning Pathways series, joining existing tracks on CI/CD with GitHub Actions, application security with GitHub Advanced Security, and administration and governance with GitHub Enterprise. Each pathway is broken into three tiers:

  • Essentials modules introduce key concepts and establish a foundational understanding.
  • Intermediate modules expand on the basics and detail best practices.
  • Advanced modules give a starting point for building deep expertise.

Banner of logos representing the companies whose experts contributed to the Learning Pathway.

Experience from production rollouts

The new Copilot content draws on real deployments at large engineering organizations. Engineering leaders from the participating companies share how they used GitHub Copilot to raise operational efficiency, ship products faster, and improve developer satisfaction. For executives weighing adoption, the pathway also walks through how to measure the potential impact of Copilot on the business. For teams already started, it covers the essential components of a rollout.

What is next

GitHub is continuing to develop the Copilot pathway. A follow-up module will go deeper into day-to-day work with the AI pair programmer, covering best practices for prompt engineering and using Copilot to write tests and refactor code.