December ‘25 enterprise roundup

December 11, 2025 // 19 min read

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In case you missed it…

Published via GitHub Executive Insights | Authored by Dave Burnison

The December '25 Monthly Enterprise Roundup (MER) highlights significant advancements in GitHub's AI strategy, enterprise governance, and developer experience. Key updates include new features for governing Copilot at the enterprise level, alongside platform enhancements like required team reviews and clearer license reporting. Numerous resources enabling you to get the most out of the GitHub Copilot coding agent, custom agents and agentic code review. The roundup also provides strategic resources on capturing AI-driven productivity gains, improving developer experience, and recapping key sessions from Microsoft Ignite and GitHub Universe.

We don't expect you to read every word. Skim through the topics that apply to how you use GitHub and dig into links that are the most relevant to you. Any one person will not read every link in this post but, across your team, every link may be read by at least one of your team members. Pass this MER along to your colleagues or pass along specific links that will be beneficial to others.

Prefer to get updates through podcasts? Check out the GitHub at Work Podcast.

Want to get notified of when the next MER is available? Go to GitHub Enterprise on LinkedIn and click on the "Follow" button. In addition to MER notifications you'll be notified when new episodes of GitHub at Work Podcast and other enterprise focused content becomes available.

Contents at a Glance

  1. Events
  2. GitHub platform - Enterprise Management & Governance
  3. Developer skills
  4. AI & ML – GitHub Copilot
  5. Security
  6. Code Quality
  7. CI/CD
  8. Engineering
  9. Legend

Events

While GitHub hosts our own marquee events like Universe and Galaxy each year, you will also find GitHub participating in other industry events. Here is the latest news about upcoming conferences and webinars.

  • 📅 Microsoft Ignite - GitHub had a huge presence at Microsoft Ignite November 17-20. Check out the GitHub landing page to access recordings and resources such as featured GitHub sessions:
    • 📺 Safe and scalable DevOps with AI agents on GitHub (44:47) - AI agents like GitHub Copilot have transformed how developers build software. Learn how to leverage GitHub’s governance and security capabilities to enable agents at scale. We’ll cover best practices for rolling out agents across your organization, aligning with developer workflows, and maintaining oversight.
    • 📺 Secure code to cloud with AI infused DevSecOps (35:48) - Modern development moves fast. Security teams are overwhelmed with alerts. But not all risks are equal. GitHub Advanced Security and Microsoft Defender for Cloud make DevSecOps seamless by connecting code to runtime context and unifying developer and security admin tools. Learn how to prioritize what’s actually exploitable in production, reduce alert fatigue, and accelerate remediation with AI-powered fixes with agentic workflows.
    • 📺 Reimagining software development with GitHub Copilot and AI agents (45:56) - The teams that have strong DevOps practices are the ones best positioned to take advantage of the power of AI. See how you can use GitHub Copilot and AI Agents to bring speed, scale and security across the software development for your organization.
    • 📺 AI-powered workflows with GitHub and Azure DevOps (45:26) - Modernize your DevOps strategy with Agentic DevOps by migrating your Azure Repos to GitHub while continuing to leverage the investments you’ve made in Azure Boards and Azure Pipelines. We'll walk through real-world patterns for hybrid adoption, show how to integrate GitHub, Azure Boards and Azure Pipelines, and share best practices for enabling agent-based workflows with the MCP Servers for Azure DevOps and Playwright.
    • 📺 Secure, compliant, and fast with GitHub - (45:18) Balancing security and developer productivity is no longer optional—it’s essential. This session dives into how enterprise platform teams are using GitHub’s governance features to streamline onboarding, enforce consistent policies, and support cross-functional collaboration at scale. Discover how to unlock developer velocity while maintaining control and compliance across thousands of repositories and users.
  • 📅 GitHub Universe 2025
  • 📅 GitHub Roadmap Webinar, Q4 2025 - The Americas and Europe November 13 - We dove into our advancements in agent-powered developer experiences and offered live demonstrations of our newest features.
  • 📅 Check out the complete upcoming conference schedule and upcoming webinar schedule.

GitHub Platform - Enterprise Management & Governance

We have been listening to our enterprise customers for years. We are excited to share updates to assist those who manage GitHub for hundreds if not thousands of stakeholders.

General

GitHub Copilot & AI

Developer Skills

General developer expertise based on our own experience and the collective experience of our customers and partners. It's time to start diving into how AI is going to work along side of you to make you a better, more productive developer not, replace you. Check out the new posts 📢, documentation 📄, and articles 📚 to see how AI can make you an awesome developer and guidance for how large enterprises should approach adopting AI.

  • 💡 How to Capture AI-Driven Productivity Gains Across the SDLC - Discover the Gartner® roadmap for achieving 25% to 30% productivity gains by applying AI across the entire software development lifecycle. Gartner predicts that by 2028, teams that apply AI across the SDLC will achieve 25 to 30 percent productivity gains, compared to the 10 percent typically seen with code focused use. Learn how engineering leaders can move from fragmented time savings to meaningful, system level productivity improvements.
    • Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
  • 📚 Measuring developer experience beyond system metrics - Understanding developer experience isn’t just about morale—it’s a business imperative. See how measuring DevEx uncovers hidden friction points that slow delivery and erode team efficiency, and why leaders who act on these insights see gains in productivity, retention, and innovation. If you want to build high-performing teams and deliver software faster without burning out your developers, you need to know this.
  • 📢 TypeScript, Python, and the AI feedback loop changing software development - AI is reshaping the very choices developers make before writing a line of code. This Octoverse insight reveals why typed languages like TypeScript are surging, how AI compatibility is becoming a critical factor in language selection, and what that means for enterprise teams optimizing for speed, safety, and future-proof architectures. Understand the feedback loop driving the next decade of software development.
  • 📢 What 986 million code pushes say about the developer workflow in 2025 - Developer workflows have fundamentally shifted—986 million code pushes in 2025 signal the end of big, infrequent releases and the rise of continuous, lightweight iteration. See why smaller, faster commits, feature flags, and automated pipelines aren’t just trends—they’re now essential for reducing risk, accelerating delivery, and staying competitive. If your team’s processes haven’t adapted yet, you need to understand what’s changed and why it matters for quality, speed, and hiring.
  • 📢 Why developers still flock to Python: Guido van Rossum on readability, AI, and the future of programming – Python, though no longer GitHub’s top language, continues to grow rapidly and remains the leading choice for AI, science, and education. In this insightful interview, Python’s creator Guido van Rossum, credits Python’s readability and low friction for its dominance and ongoing relevance, even as trends like static typing and AI reshape programming. He also notes Python’s foundational role in machine learning and discusses the potential for stronger typing in its future.
  • 📢 & 📺 TypeScript’s rise in the AI era: Insights from Lead Architect, Anders Hejlsberg (5:31) – The creator of TypeScript discusses how the language grew 66% in one year to become the most-used on GitHub, providing developers with "JavaScript with superpowers" for improved teamwork and scale. TypeScript's static types give AI tools a "safety net" for correct code generation, creating a positive feedback loop where AI's strength with popular languages drives more developers to adopt it.
  • 📚 Playbook series: Executive support - Effective executive support isn’t about passively signing checks; it’s about actively setting a new standard. It’s about fundamentally reframing AI from a "nice-to-have" tool into a core competency for every single employee. Communicating that this isn't a suggestion, it's the new reality of work. This post is a blueprint for leaders who want to be the engine of their company's AI transformation.
  • 📚 Playbook series: Fostering AI learning opportunities - See why access alone isn’t enough—and a proven blueprint for scaling AI fluency: from curated learning hubs and structured paths to real-world use cases and live “office hours” sessions—empowering every developer and leader to go from curiosity to confident, productive AI usage.
  • 📚 Playbook series: Communities of practice - Your organization’s AI knowledge may be disappearing into private chats and siloed conversations. This post explains why Communities of Practice are the key to turning scattered insights into scalable, shared intelligence—and how they accelerate adoption, reduce duplication, and build true AI fluency across teams.
  • 📄 Using GitHub Copilot to reduce technical debt - Technical debt accumulates in every codebase: duplicate code, missing tests, outdated dependencies, and inconsistent patterns. These issues can accumulate because feature development is typically given a higher priority. See how you can use GitHub Copilot to tackle technical debt systematically, without sacrificing feature velocity.

AI & ML - GitHub Copilot

Recent advancements and feature updates for GitHub Copilot, with a particular focus on the coding agent, custom agents and agentic code review. There are some great posts on how to get the most out of some of the latest copilot innovations.

GitHub Copilot coding agent

  • 📢 GitHub Copilot tutorial: How to build, test, review, and ship code faster (with real prompts) – Walk through an entire development workflow supercharged by Copilot – from writing code with mission control and agent mode, to generating tests, to having Copilot review your pull requests. See examples of prompts you can try and best practices to get the most out of each Copilot feature. It demonstrates how Copilot has evolved into a full-fledged AI partner throughout the dev lifecycle, and teaches you step-by-step how to leverage it to build, debug, and ship code faster.
  • 📺 How to assign and manage Copilot agent tasks from anywhere (4:15) - GitHub Copilot coding agent meets you where you're at, allowing you to assign tasks from basically anywhere. You can even create custom agents focused on specific types of tasks. And the new agent page gives you a central location from which to monitor and steer any coding agent tasks. Meanwhile, Copilot CLI allows you to run autonomous agents locally.
  • 📢 How to orchestrate agents using mission control – Learn to coordinate multiple AI coding agents simultaneously with Copilot’s new mission control interface. See how to assign several Copilot agents different tasks across repos, watch real-time logs, and intervene as needed – all from one dashboard. By running agents in parallel instead of one-by-one, you can unblock work and tackle parts of a project concurrently, dramatically boosting team productivity without losing oversight.
  • 📄 Using GitHub Copilot to reduce technical debt - Technical debt accumulates in every codebase: duplicate code, missing tests, outdated dependencies, and inconsistent patterns. These issues can accumulate because feature development is typically given a higher priority. See how you can use GitHub Copilot to tackle technical debt systematically, without sacrificing feature velocity.
  • 🗣️ Taming Your Monorepo with GitHub Copilot 🚀: Managing a massive, complex monorepo can feel like herding cats— but what if your AI coding assistant could become an instant expert on any part of your codebase? Read our blog to learn more!
  • 📢 How we’re making GitHub Copilot smarter with fewer tools – We share how we streamlined Copilot’s toolset in VS Code (from 40+ tools down to 13 core ones) to cut response times and boost accuracy. By using embedding-guided tool selection and grouping similar capabilities, Copilot now finds the right tool for the job with less confusion. In benchmarks, these changes improved success rates by ~2–5% and made suggestions ~400ms faster on average. In short, Copilot became faster and more reliable – a win for developers who get quicker completions and less waiting.
  • 📢 Evolving GitHub Copilot’s next edit suggestions through custom model training – Copilot’s “next edit” suggestions just got faster and smarter. See how GitHub made in-editor code suggestions more precise by training a custom AI model on real editing session data and applying reinforcement learning. The takeaway for devs: Copilot now better understands what you’re trying to do and can suggest the right small code edits with higher accuracy.
  • 📢 How GitHub’s agentic security principles make our AI agents as secure as possible – This post details GitHub’s blueprint for building safe Copilot agents, outlining strict security principles to counter risks like data leakage, wrong actions, and prompt hijacking. These principles require agents to only use visible, maintainer-provided context, be firewalled from the internet and sensitive data, and secure human-in-the-loop oversight for irreversible changes.
  • 🚢 Copilot coding agent supports organization custom instructions - Enable consistent, organization-wide guidance for Copilot coding agent with custom instructions that streamline how your teams build, test, and validate code changes.
  • 📺 How to use GitHub Copilot coding agent in Slack (0:59) - You can now use the GitHub app for Slack to collaborate with GitHub Copilot right inside your Slack conversations. This initial release introduces the Copilot coding agent, built to translate conversations into code and pull requests. It’s the first step toward bringing the full power of GitHub Copilot into Slack.
  • 📺 Assign Linear issues to Copilot coding agent (0:57) - You can now use the GitHub app for Linear to collaborate with GitHub Copilot right inside your Linear issues. This release introduces the Copilot coding agent, built to translate issues into code and pull requests.

Custom Copilot Agents

  • 📢 How to write a great agents.md: Lessons from over 2,500 repositories – Most agents.md files (for defining custom Copilot agents) fail by being too vague. We've distilled best practices from thousands of repos to help you avoid that trap. The secret is to treat your AI agent like a focused specialist: give it a clear role and persona, list explicit commands and examples it should use, and set firm boundaries on what it must not do. The guide provides concrete tips so that your custom agents produce consistent, high-quality results instead of generic or risky ones.
  • 📢 Your stack, your rules: Introducing custom agents in GitHub Copilot for observability, IaC, and security – Meet Copilot’s new custom agents, which act like domain-specific AI teammates for your dev workflow. See a growing ecosystem of partner-built agents (and how to create your own) that can debug, secure, or automate tasks across your terminal, IDE, and GitHub itself. The big idea: you can extend Copilot with specialized “skills” – from observability queries to infrastructure as code – all while keeping your existing tools and processes. You can find many custom agents and more in the Awesome-Copilot public repo: https://github.com/github/awesome-copilot.

Agentic Code Review

  • 📢 Unlocking the full power of Copilot code review: Master your instructions files – See how to fine-tune GitHub Copilot’s code review comments to your team’s standards by writing effective instructions files. It offers practical tips for structuring copilot-instructions.md (repo-wide) and path-specific *.instructions.md files: keep them concise, use bullet points and section headings, and include examples of good code and bad code. You’ll learn why short, direct rules (“Prefer X over Y”) work better than long paragraphs, and how to avoid pitfalls like unsupported directives or overly broad mandates. Bottom line: with a well-crafted instructions file, Copilot’s automated PR reviews will consistently flag the issues you care about and offer suggestions in line with your style guides.
  • 📺 How to close pull requests faster with Copilot code review (10:40) - Join us for a deep dive into GitHub Copilot code review, an AI assistant designed to increase developer productivity without compromising quality. Elle Shwer, Senior PM at GitHub, explains how it helps teams maintain consistency and adds crucial context for reviewers so nothing gets missed.
  • 📄 Using custom instructions to unlock the power of Copilot code review - You'll learn how to write clear, effective custom instructions that help Copilot provide more relevant code reviews. You'll discover best practices for structuring your instructions, common pitfalls to avoid, and strategies for organizing instructions across different files.
  • 🚢 Linter integration with Copilot code review now in public preview - Unlock customizable, enterprise-grade code quality checks by combining Copilot’s AI reviews with integrated linters like ESLint and PMD—giving your team precise, automated feedback across languages and repositories.
  • 🚢 Copilot code review and coding agent now support agent-specific instructions - Gain precise control over GitHub Copilot’s behavior with new agent-specific instructions, enabling tailored guidance for code review and coding agents to streamline enterprise workflows.

IDE Related GitHub Copilot Updates

GitHub Copilot - New Models

Additional GitHub Copilot Updates

Security

Application security with GitHub, ensuring the code that lives in GitHub and the dependencies that go into the solutions you build are secure and do not contain any secrets.

Code Security

Secret Protection

Supply Chain Security

Additional Security Updates

Code Quality

GitHub Code Quality helps you ensure your codebase is reliable, maintainable, and efficient. Whether you're building a new feature, reducing technical debt, or reporting on repository health, Code Quality provides actionable insights and automated fixes so you can improve and maintain the code health of your repository efficiently.

  • 📄 About GitHub Code Quality - GitHub Docs - Use GitHub Code Quality to flag code quality issues in pull requests and repository scans, apply Copilot-powered autofixes, and enforce standards with rulesets.
  • 📺 How to improve code health with GitHub Code Quality (1:50) - GitHub Code Quality helps you ensure your codebase is reliable, maintainable, and efficient. Whether you're building a new feature, reducing technical debt, or reporting on repository health, Code Quality provides actionable insights and automated fixes so you can improve and maintain the code health of your repository efficiently.

CI/CD

Continuous Integration & Continuous Deployment with GitHub Actions.

Engineering

An inside look at how we’re building the home for all developers. Resources based on our internal experiences.

  • 📢 How Copilot helps build the GitHub platform – This case study reveals that GitHub Copilot acts as a junior engineer on GitHub’s own team, assigned real issues and opening pull requests for fixes and features. Over a month, Copilot handled tedious, large-scale refactors. This new collaboration pattern allows human engineers to delegate routine toil to Copilot, freeing them to focus on high-value work like architecture and edge cases.
  • 📢 & 📺 Level up design-to-code collaboration with GitHub’s open source Annotation Toolkit (7:14) – The Annotation Toolkit is a Figma library that lets designers embed critical UX and accessibility details directly into their design files. Documenting design intent upfront prevents details from being lost in translation, which GitHub found could have prevented 48% of accessibility issues. This leads to smoother handoffs and fewer ambiguities for engineers.

Legend

That’s it for the December '25 edition of the MER. Follow GitHub Enterprise on LinkedIn to see the next round of key updates.

We want to hear from you! Did you find this curated list of updates from GitHub helpful? Do you have suggestions on how we can provide the information that is going to be the most useful and timely for your role? Visit the GitHub Community. December ‘25 enterprise roundup - community · Discussion

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