At GitHub Universe 2024, developers were treated to a myriad of AI-powered software development tools. Is this what the future of DevOps and AppDev looks like?

In the ‘low-code, no-code’ world of DevOps, nothing could be more exciting today than the availability of AI platforms for software development.

At its 10th GitHub Universe conference, GitHub emphasized the power of developer choice delivering multi-model GitHub Copilot with models from Anthropic, Google, and OpenAI, as well as the introduction of GitHub Spark, and additional updates across Copilot and GitHub models.

“In 2024, we experienced a boom in high-quality large and small language models that each individually excel at different programming tasks,” said GitHub CEO Thomas Dohmke.

“There is no one model to rule every scenario, and developers expect the agency to build with the models that work best for them. It is clear the next phase of AI code generation will not only be defined by multi-model functionality, but by multi-model choice.” 

Tim Hogarth, CTO, ANZ Bank, commented: “GitHub Copilot has steered software engineers at ANZ Bank toward improved productivity and code quality. From mid-June – July 2023, ANZ Bank conducted an internal trial of Copilot that involved over 100 of the bank’s 5,000 engineers. The group that had access to Copilot was able to complete some tasks 42% faster than the control group participants.”

The trial provided compelling evidence of the transformative impact of Copilot on engineering practices at ANZ Bank. “The adoption of this tool has marked a shift, empowering engineers to focus more on creative and design tasks while reducing time spent on repetitive boilerplate tasks. Copilot has now already been widely adopted within the organization,” said Hogarth.

“I experienced my Eureka moment with GitHub Copilot when I realized it significantly reduces the learning curve required to become an efficient cloud developer. It’s much easier for developers to jump onto new languages and platforms, because GitHub Copilot will hold your hand and guide you, ”commented Peter Birkholm-Buch, Head of Software Engineering, Carlsberg Group.

Sharryn Napier, GitHub’s VP for APAC, emphasized the developer community’s desire for choice and the ability to compare different models to make informed decisions. “In our region, we have many different cloud vendors and hyperscalers, and I think choice is one of the things that our developer communities want. They want the opportunity to get the best outcome that they can possibly get, without being forced down a certain path to a certain decision.”

Copilot’s natural language capabilities have broken down language barriers, accelerating AI adoption in APAC where the great diversity of languages often is an obstacle in software development. India is predicted to overtake the US by 2028, with 17 million developers. China is also seeing fast AI adoption, with Indonesia the fastest-growing having started from a small base.

In advanced markets such as Japan and Singapore, “the opportunities lie in modernization of software development lifecycles and AI adoption,” said Napier.

Creating sparks

In pursuit of its vision to enable 1 billion developers, GitHub Spark makes it easy for developers of all skill ranges to bring ideas to life by using natural language to build micro apps called a “spark.” Sparks are fully functional micro apps that can integrate AI features and external data sources without requiring any management of cloud resources.

“For too long, there has been an unscalable barrier of entry separating a vast majority of the world’s population from building software. This can change with GitHub Spark, our new AI-native tool to build applications entirely in natural language,” said Dohmke.

“With Spark, we will enable over one billion personal computer and mobile phone users to build and share their own micro apps directly on GitHub — the creator network for the Age of AI.”

What users are saying

“At Infosys, we’re passionate about unlocking human potential, and GitHub is a strategic partner in this endeavor. Generative AI is transforming every aspect of the software development lifecycle, and using Infosys Topaz assets, we are accelerating Gen AI adoption for our clients. We are excited to work with GitHub to unlock this technology’s full potential and deliver client-relevant solutions,” said Mohammed Rafee Tarafdar, Chief Technology Officer, Infosys.

“The integration of GitHub Copilot at MakeMyTrip has resulted in substantial productivity gains on several fronts,” said Sanjay Mohan, Group CTO, MakeMyTrip. “Coders are spared the monotony of routine tasks, freeing up time to solve higher-order problems that are core to our travel domain. The quality assurance team spends more time on being the real voice-of-the-customer within the organization, using Copilot to auto-generate unit tests and integration tests and, effectively, utilizing the efficiency gains towards driving comprehensive edge-case coverage. The DevOps/SecOps teams also gain significant efficiency by employing a ‘shift left’ approach to application security, making the feedback loop much more responsive within the process.”

Norishige Nagase, Senior Managing Executive Officer & CTO, CyberAgent, commented: “Tailored to our knowledge base, GitHub Copilot Enterprise ensures our developers can operate efficiently. Developers can inquire about repositories and branches that haven’t been cloned yet, and the introduction of docsset – which makes it possible to ask questions about a project without having to search for documentation – has been a game-changer. We believe this feature could significantly support and streamline the onboarding process for new engineers.”

“Personalized, natural language recommendations are now at the fingertips of all our developers at Figma,” said Tommy MacWilliam, Engineering Manager for Infrastructure, Figma. “Copilot Enterprise has improved collaboration across the SDLC by making it easier for our engineers to source and find information via Copilot Chat. We’re also seeing a significant increase in overall developer productivity. Our engineers are coding faster, collaborating more effectively, and building better outcomes.”