software-engineering, engineering-culture, generative-ai,

Boosting Developer Productivity with GitHub Copilot: TomTom experience

Silvia Longo Silvia Longo Follow Dec 08, 2023 · 3 mins read
Boosting Developer Productivity with GitHub Copilot: TomTom experience
Share this

At TomTom, we are thrilled to share our positive experience with GitHub Copilot. Launched in July 2023 by the Internal Developer Experience team, GitHub Copilot has been a game changer for our developers at TomTom.

What’s GitHub Copilot? It’s an AI tool developed by GitHub and OpenAI that assists developers by providing intelligent code suggestions and documentation. It helps with tasks such as code analysis, generation, conversion of comments to code, autofill code, running tests, and exploring unfamiliar code. It’s essentially an AI-powered coding buddy, making our work more efficient and effective.

Some of the benefits of Copilot are:

  • Increased productivity and efficiency by providing accurate and relevant code suggestions 
  • Improved code quality and consistency and reduced potential errors during code review 
  • Speed up your coding workflow and reduced cognitive load by using machine learning models to assist with syntax, API usages 
  • Better code completion  
  • Enhanced collaboration potential and fostered experimentation 

What do we want to achieve?

We (Internal Developer Experience) deliver tools and services for our engineering teams, helping them to increase productivity, efficiency, and code quality across our code base. We also aim to reduce product deliverables’ cycle and lead times by enabling GitHub Copilot as an AI-supported pair programming capability. Through this initiative, we aim to optimize our development processes and enhance the overall output of our engineering teams.

OSM Sectioned Map Data Model

How’s it going so far?

We established feedback loops at both the individual and organizational levels to gauge the impact of GitHub Copilot on productivity. This involves monitoring and analyzing Copilot usage data to assess its effectiveness and identify areas for improvement. We built internal metrics to measure the adoption, to investigate which programming languages are most tested, to evaluate what is the percentage of accepted lines of code, to define our productivity baseline, and to collect direct feedback through user surveys.

The positive feedback and experiences shared by our early adopters have reinforced our belief in the immense potential of this tool. More specifically,

  • 85% of our users feel more productive,
  • 70% of our users feel they can focus more on more satisfying work
  • This is a huge testament to what new technologies can help us do. We are proud to witness our engineers becoming more productive, efficient, and inspired in their coding journey.

What’s next?

With Copilot’s advanced features, we are confident that our development processes will reach new heights, resulting in remarkable outcomes - including increased productivity and efficiency.

We will continue to involve more developers and boost these benefits across our tech teams, and we are investigating and delivering more initiatives to include AI in our daily work.  

Looking ahead, we are committed to further harnessing the power of GitHub Copilot. We will continuously explore its capabilities, adapt them to our specific use cases, and provide ongoing support and training to our developers. Our goal is to unlock even greater potential and continue delivering exceptional results.

We are excited about this next chapter in our journey with GitHub Copilot, and we invite our external customers to join us in experiencing the transformative power of AI-supported pair programming. Together, we can revolutionize the way we write code and drive innovation to new heights.

Stay tuned for more updates and success stories as we embark on this exciting journey with GitHub Copilot!

Silvia Longo
Written by Silvia Longo
Product Manager