GitHub Scales As A Real Global Corporation

GitHub Universe was held this past November 8–9 in San Francisco. By far, the star performer was GitHub Copilot, the AI assistant based on OpenAI’s ChatGPT-4 technology that set the development world abuzz last year and has the world talking about its impact on “developer productivity.” But before we get to that (and more), let’s explain why GitHub matters.

GitHub is truly a global corporation. According to GitHub, it serves over 100 million developers from around the world, 4 million organizations, and over 420 million private and public code repos. Ninety percent of the Fortune 100 use GitHub, and there have been 4.5 billion code contributions so far in 2023. GitHub has users in over 100 geographical regions on every continent. In comparison, Salesforce (no slouch when it comes to size of developer communities) reported 14 million developers in 32 countries.

And while most companies focus on the traditional regions of North America, Europe, and APAC, GitHub tracks developers in South America and Africa, as well, providing a refreshing injection of global perspective. For example, according to GitHub, Nigeria has a 45% year-over-year growth rate of software developers, and Vietnam has the fastest growth rate (by country) of software developers in the world.

The Shiny Object: GitHub Copilot

Let’s get back to GitHub Copilot, the AI assistant that’s helping all developers — well, those signed into a cloud account — go faster. GitHub Copilot is what Forrester calls a coder TuringBot. TuringBots represent one of Forrester’s top 10 emerging technologies for 2024. As a TuringBot, GitHub Copilot keeps developers in the flow and inside their integrated development environment (IDE) of preference (it’s a plug-in to most of the common IDEs in use). GitHub Copilot in fact:

  • Helps developers while they are coding with what can be best described as intelligent code auto-complete. You start writing code and ask GitHub Copilot to do its best to grok what you’ve written and complete the rest.
  • Provides developers a prompt to simply describe the code that they want Copilot to create — for example, “create a method that adds two numbers together” — or even to resolve more complex tasks such as calling APIs (for which the developer doesn’t remember the signature) and service-level agreements.
  • Creates unit tests for both existing code and for newly generated code. It can explain code, as well as review and document code. In other words, you can look at Copilot as being your first pass of an automated code reviewer and pair programmer.

New Features And Options

GitHub announced a new offering tier, as well: GitHub Copilot Enterprise comes in at $39/user/month and hits general availability in February 2024. That’s in addition to the GitHub Copilot Business tier, which stays at $19/user/month. A few important, newly announced GitHub Copilot features include:

  • A natural language chatbot (like ChatGPT — in fact, based on OpenAI’s GPT-4) inside the IDE that a developer can query for insights into the code, to provide high-level designs or API information, to generate and document code, and more.
  • The ability to customize GitHub Copilot on your enterprise custom code, enabling enterprises to fine-tune Copilot’s capabilities to observe coding styles, libraries used, APIs, and other development norms to get tailored code suggestions (limited to the new Enterprise tier).
  • The ability, at the same time, to restrict access to code in your repositories from the tailored customization (Enterprise only).
  • Offering GitHub Copilot on, as well as a new partnership program that was launched for third-party partner integrations, along with a few already active such as Databricks, New Relic, Postman, Red Hat, and Docker.

A Comprehensive Platform Infused With AI Is The Future …

In addition to GitHub Copilot announcements, for the first time ever, GitHub referred to the GitHub collection of products as a platform. In other words, what began as a source code repo is evolving to become a platform that can do nearly anything needed for software development, all infused by AI. Announcements related to the expanding platform capabilities included:

  • Security offerings such as Dependabot, auto-triage, and secrets scanning.
  • GitHub projects, a workflow/issue tracker with integrated automation.
  • GitHub Actions on more silicon — GitHub has created runners for macOS M1 and ARM for native Actions support.
  • Lastly, the really interesting thing: GitHub announced migration tools for Atlassian Bitbucket (a competitor and no surprise) and Microsoft’s Azure DevOps (its parent company and a big surprise).

… But We Expect More

With all these announcements, you’d think we’d be satisfied, but actually, Diego, Andrew, and I walked away wishing that we saw more or had greater clarity as to what the future holds for both GitHub and its parent, Microsoft. For example:

  • GithUb showcased individual developer metrics but not team or organization metrics. While GitHub talks a good game for providing a platform, all the focus was on individual developers and not on team metrics, platform teams, or enterprise maintainers. And while GitHub’s announcement of user interface (UI) enhancements that integrate personal and corporate GitHub accounts in the same UI got rousing applause from developers, this may cause consternation with corporate security teams.
  • The relationship with Microsoft appears more complicated than it should. We’d like to see GitHub address the confusing relationship that it has with Microsoft. If GitHub has tools to migrate users from Azure DevOps (ADO), what does that say about the future of ADO? It makes Azure DevOps users rightfully wonder.
  • There’s a strong focus on the creation side of coding but not the other steps. GitHub Copilot is currently addressing developers’ needs mainly in the coding step of the software development lifecycle (SDLC). But true productivity gains will come with TuringBots addressing all steps of the lifecycle. Generic announcements were made about integrating Microsoft functional testing tools — for example, to implement the tester TuringBot. Although we are aware that Microsoft testing tools do not shine as market leaders, we are eager to see how effectively and quickly GitHub executes on infusing TuringBots throughout the entire SDLC and not just in code generation and security.
  • There’s a question of to what degree enterprises can customize Copilot to match their specific needs. We also wonder how well clients can fine-tune GitHub Copilot. GitHub addresses fine-tuning with an existing code base but could become more aware of enterprises’ own specificities or for specific verticals, for example, before starting a greenfield project leveraging architecture patterns, specifications, policies, and standards that are not just code abstractions.

In summary — GitHub is all in on AI. It is aiming to become indispensable to the enterprise SDLC beyond its role as Git-Repo. “By developers, for developers” sounds great if you’re a coder, but GitHub needs to convince nondevelopers that its platform has the enterprise chops that managers and executives require.

Reach out on the Forrester website with an inquiry or guidance session to for questions about GitHub as a platform, for questions on GitHub Copilot and TuringBots, and for developer experience with GitHub.