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GitHub Copilot: Exploring AI pair programming tools

As a digital services company at the forefront of government transformation, we’re always exploring how emerging technologies like AI can enhance our development capabilities. 

This year we’ve been trialling GitHub Copilot, an AI pair programmer that suggests code as you type. In this blog, I’ll share our experience of using Copilot and how tools like these can accelerate software delivery.

What is GitHub Copilot and why use AI pair programming?

Copilot is a cloud-based AI trained on public GitHub code repositories. This training allows it to suggest code in all open source languages including Python, JavaScript, Java and Go, and also works well with markup formats used by Terraform, among others.

It’s similar to ChatGPT in using a large language model, but Copilot is specialised for code, while ChatGPT is used in a broader context.

As you write code, Copilot provides relevant suggestions to accelerate development. For example, Copilot can generate entire code blocks when given plain English descriptions of what the code should accomplish.

Zaizi started exploring large language models at the start of the year.

Our Design Authority evaluated different AI pair programming tools and selected GitHub Copilot for initial testing given its trusted reputation. GitHub’s use of open source means there should be no copyright issues with its code suggestions.

Importantly, Copilot operates securely— it doesn’t store code snippets or prompts from your editor. It’s essentially an experimental sandbox. As a company that works with secure public sector organisations, this was an important consideration.

We formed a group to conduct a three month Copilot trial across our internal projects and on some of our customer projects where we had obtained permission.

The key benefits

It’s fair to say that our engineers became fans of Copilot pretty quickly. Having an AI whispering code suggestions as you type is, not surprisingly, very useful! 

Here are some of the key benefits we saw:

The longer we used Copilot, the better it got. We learned how to give clear instructions to get useful code. By the end of our trial, the team gave feedback that they definitely wanted a tool like this as a permanent part of their toolkit.

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The pitfalls of Github Copilot

Copilot isn’t infallible, so oversight remains critical. Soon after starting the trial, we realised the need to provide some initial training on how to provide specific instructions to get maximum productivity gains.

We created guidance and terms of use stating that ultimately developers are accountable for the code, which must go through the standard review cycles and quality checks. For example:


Below are firsthand experiences from our developers who tested Copilot:

What’s the future?

The trial has convinced us that AI-powered coding is incredibly valuable. The productivity boost was significant while the cost was minimal.

We know this technology is evolving rapidly — Copilot is only a year old! To stay on the cutting edge, we’ll broaden our trials to other emerging tools.

In the long term, our goal is to integrate the best AI assistant into our workflows. As these AI pair programmers continue improving, they’ll become integral to efficient, high-quality software development.

And we can bring these benefits directly to our public sector clients. Beyond significant efficiency gains for our consultants, we can share our hands-on knowledge to help government teams take full advantage of AI’s potential.

Along with many other things, AI will transform the future of programming. Our team is excited to be leaders in leveraging these tools to accelerate digital change in the public sector.

If you’re exploring how emerging technologies like AI can transform service delivery, our team has the knowledge to guide you. Get in touch to discuss how we can help accelerate your digital transformation with AI pair programming.

Thanks for joining us! We’ll keep you informed with regular updates.

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