Global technology company enhances developer productivity with AI

A global technology company partnered with Modus Create to explore how a GitHub Copilot adoption strategy could improve developer experience. Our experts designed and delivered three tailored training cycles for developers across the US, Europe, and India. The enablement program covered GitHub Copilot fundamentals, custom modules based on roles and integrated development environments (IDEs), and stakeholder workshops focused on adoption metrics and ROI. By the end of the project, the company had a more productive engineering team ready to build faster with AI.

Our work involved

• 101 (introductory) and 201 (intermediate) GitHub Copilot trainings
• Advanced sessions tailored to roles and IDEs
• Region-specific enablement across the US, EU, and India
• Stakeholder workshops on adoption metrics and ROI

Impact

All Fortune 500 companies have a sprawling IT infrastructure comprising several networks, systems, and configurations. Almost every one of them uses the company's software at the center of this case study to manage some of that complexity. The US-based company serves over 300,000 organizations, including key US government agencies.

That kind of scale means the company’s engineers have an outsized impact on almost every major industry. The company takes that responsibility seriously, constantly investing in better tools and processes to improve developer experience, especially with AI.

The company needed a scalable approach to evaluate GitHub Copilot and roll it out to its 600+ engineers in the US, Europe, and India. But it knew that one-size-fits-all training wouldn’t be enough. It needed a strategic adoption strategy that reflected the challenges and requirements of each team.

CHALLENGE

Slowed developer productivity across global teams

The technology company connected with Modus Create to assess GitHub Copilot’s potential through a tailored, hands-on adoption strategy. After initial conversations, two major challenges stood out:

First, the engineering team was distributed across the US, Europe, and India, with each region bringing its own technical context and team dynamics. Second, day-to-day development was slowed by common friction points such as repetitive coding tasks and delays in finding the right patterns or references, affecting overall productivity. On top of that, some stakeholders expressed uncertainty about the scalability and measurable impact of GitHub Copilot training.

To deliver value, the program had to do more than explain how GitHub Copilot works. It had to prove that it could enhance productivity across varied environments and generate clear returns.

SOLUTION

A role-based GitHub Copilot adoption strategy

Modus Create led a multi-phase initiative that combined structured training, real-time support, and reusable learning assets. The program was designed to evolve with the company’s teams, meeting them where they were and scaling with their needs.

1. Defining success metrics

Before initial training began, we partnered closely with the company’s leaders to define success metrics. This included defining clear adoption KPIs, establishing a tailored ROI measurement framework, and aligning the strategic adoption program to the company’s broader AI strategy. Two of our key goals were:

• improving the ability to understand large codebases across languages like Java, JavaScript, C#, SQL, and Kotlin
• accelerating development in areas such as automation and testing

By using GitHub’s Copilot APIs, user surveys, downstream impact metrics, and visualization tools, we ensured stakeholders had both the data and the strategy needed to measure impact effectively.

2. Foundation & fundamentals

We kicked off training with GitHub Copilot 101 (introductory) and 201 (intermediate) sessions, designed to bring engineers up to speed through practical, real-world examples. These sessions provided a structured path from foundational understanding to advanced application of GitHub Copilot's capabilities.

The 101 session introduced participants to GitHub Copilot’s core features, including code suggestions, basic prompt writing, and IDE integration, helping users gain confidence in setup and everyday usage.

Building on this, the 201 session explored intermediate-level functionality such as slash commands, test generation, refactoring, and debugging. It also covered prompt engineering techniques like zero-, one-, and few-shot prompting, secure coding practices, troubleshooting, and real-world use cases involving GitHub Copilot Chat and GitHub REST APIs.

Together, these sessions gave developers and QA engineers the skills and confidence to integrate GitHub Copilot effectively into their daily workflows. This created a secure, shared foundation across teams while allowing regional trainers to localize examples and pace based on timezone and audience.

3. Role, IDE, & language-based sessions

Once the basics were in place, we shifted to custom sessions tailored by role, language, and tooling. These GitHub Copilot trainings gave developers, QA engineers, DevOps engineers, and security engineers a hands-on, role-specific learning experience. The focus was on real-world use across Java, JavaScript, C#, SQL, Kotlin, and scripting languages, using IDEs like Visual Studio, VS Code, and IntelliJ.

The sessions helped participants apply GitHub Copilot to advanced development and testing tasks, such as:

• writing and debugging code
• generating unit tests
• building test automation frameworks
• integrating security practices

Attendees also learned to boost productivity using prompt engineering, slash commands, GitHub Copilot Chats, and GitHub REST API integration.

4. Ongoing support & office hours

Training didn’t stop at the session level. We hosted weekly office hours in each major region, enabling developers to ask questions, troubleshoot blockers, and share feedback in real time. Trainers worked closely with team leaders to adapt session content based on participation trends and team needs, making the program flexible and responsive across all time zones.

5. GitHub Copilot adoption materials

To reinforce learning and ensure the lasting impact of the adoption strategy, we shared a comprehensive set of hands-on training materials with the company after each session. This included polished slide decks summarizing session content, session recordings for async learners, and dedicated code repositories for each module.

These repositories contained detailed setup instructions, step-by-step hands-on exercises, example code, and best practices for each training track. Our collateral served as a long-term reference for the company to revisit key concepts and scale their GitHub Copilot usage over time.

IMPACT

Improved developer experience

By the end of the engagement, the company had the structure, confidence, and resources to expand GitHub Copilot adoption across its engineering teams. It achieved:

• A consistent, role-based training model that scaled across US, European, and Indian teams
• Clear alignment between engineering leaders and business goals, with KPIs and ROI frameworks in place
• Increased developer engagement and confidence using GitHub Copilot in daily workflows
• A reusable internal enablement toolkit to support future GitHub Copilot training and onboarding

Right from the outset, the company kept the focus on outcomes. Every session had a purpose, and the entire project was tied to measurable KPIs. The company avoided a one-size-fits-all approach and instead built a model that respected the unique needs of each region and role. That decision made the difference.

With a strong foundation in place, the company is now ready to iterate and expand the GitHub Copilot adoption strategy even further, empowering several more teams with AI and fostering a community of GitHub Copilot champions.

Get more from GitHub Copilot. Take the next step with practical sessions designed to help your teams optimize Copilot usage, manage AI credit consumption, and build better habits. Explore Copilot optimization sessions →