GitHub Enterprise @GitHubEnt

When developers purchase their own AI tools, it signals unmet needs rather than a simple compliance problem. Instead of implementing a blanket ban, here's how your organization can provide safe, viable alternatives. Learn more in GitHub's Agentic Engineering System about creating an agent-native platform that supports the developer experience and drives customer value. gh.io/aes-framework

When an agent makes a change to your code, you want to review it, run it, and see what changed. Great news: now you can do all three without having to leave the GitHub Copilot app. github.blog/ai-and-ml/gith…

AI coding tools increase developer output. But growing pull request backlogs can easily overwhelm engineering teams, contributing to what’s known as “review fatigue.” Here’s how to calibrate your workflows for agentic development. Improve prompts, use stacked pull requests, and recognize how the developer role is changing. github.com/resources/insi…

The September 2026 GitHub Monthly Enterprise Roundup is now available. Explore how GitHub’s Agentic Engineering System helps enterprise teams use AI to accelerate software delivery while maintaining quality, security, governance, and human oversight. This edition also highlights Project HydraFusion, along with Copilot’s expanding agent, app, CLI, SDK, IDE, and collaboration experiences. We cover three priorities for enterprise leaders: • Build an agentic engineering operating model • Measure adoption by outcomes, not output • Embed quality, security, and human approval into AI-assisted workflows Scale a more productive, secure, and resilient engineering system. github.com/resources/insi…

A pilot often starts with excitement, strong adoption, and increased productivity. But why do those results sometimes fall flat when organizations try to scale? GitHub’s Agentic Engineering System helps organizations understand the conditions that make scaling agents successful. This way, they can set realistic expectations and improve the odds of seeing similar results at scale. Learn more ⬇️ gh.io/aes-framework

If your enterprise used a managed-settings.json file to control what your users can do in Copilot clients, you can now apply different settings to different enterprise teams. For example, if a team needs access to certain plugins for specialized work, you don’t need to give access to everyone in the enterprise. Learn more with GitHub Docs. docs.github.com/en/enterprise-…

Enterprise administrators can now tailor GitHub Copilot managed settings for specific teams using itemized configuration files. Teams can adapt Copilot to their workflows while enterprise-wide guardrails remain in place. github.blog/changelog/2026…

Learn practical ways to scale Copilot adoption while maintaining control over cost, security, quality, and developer experience. The takeaway: successful AI adoption leads to building trusted automation, strong feedback loops, and human judgment into the engineering system. github.com/resources/insi…

Discover how GitHub Copilot is expanding across: • Desktop, cloud agent, CLI, IDEs, Jira, and mobile • Code review and MCP-connected workflows • Policy controls for models, teams, devices, clients, usage, and AI credits

The August 2026 edition of the GitHub Monthly Enterprise Roundup (MER) is now available. This month’s roundup explores how AI is moving beyond code completion into governed, measurable, end-to-end engineering workflows. 🧵⬇️

Governance should follow developers wherever they build. Enterprise managed settings now apply to the GitHub Copilot app and Copilot cloud agent, helping organizations: • Define guardrails once across supported Copilot experiences • Control approved plugins and marketplaces centrally • Manage approval-prompt policies for interactive clients • Override local settings with enterprise-managed values • Extend existing configurations automatically (no additional setup required if you already use managed-settings.json) Scale AI adoption with consistent governance across the Copilot app, cloud agent, CLI, and VS Code. github.blog/changelog/2026…

Find out how to measure the real impact of AI at your organization. On July 30, we'll demonstrate how to evaluate adoption and pinpoint opportunities to drive greater engagement. Plus, get special insights from the @code team on using AI to complement work and reduce workflow overhead. Register here ⬇️ github.registration.goldcast.io/webinar/bc1319…

Many teams can tell you whether developers are using AI. Fewer can show how they’re using it and whether those behaviors are associated with measurable engineering outcomes. Drawing on findings from thousands of organizations, we explore adoption trends across surfaces and how progression from code completion to agentic workflows is associated with higher throughput and faster time-to-merge. With the new GitHub Copilot impact dashboard, enterprise leaders can measure those same adoption patterns and engineering outcomes within their own organizations—helping them identify opportunities for enablement, guide investments, and advance adoption. Learn how your organization can connect Copilot adoption to impact and scale with confidence. github.com/resources/insi…

We benchmarked the GitHub Copilot agentic harness against the harnesses that ship leading models natively. Holding the model and task fixed across SWE-bench Verified, SWE-bench Pro, SkillsBench, TerminalBench, and Win-Hill, the results were clear: • Task resolution on par with model-vendor harnesses • Fewer tokens across most configurations A key learning: With GitHub Copilot supporting more than 20 models, you're free to pick efficiency or peak quality per task. Explore the data. github.blog/ai-and-ml/gith…

GitHub is powered by open source, and using it responsibly means respecting the licenses behind every dependency. Find out how GitHub’s OSPO uses License Compliance to review dependencies in pull requests, manage exceptions, and reduce risk. github.blog/enterprise-sof…

"GitHub Copilot for Jira has changed how product and engineering teams work together. Backlog items move straight from Jira into delivery, with AI generating draft pull requests from ticket context, shifting us towards a more automated, agent-driven model." - John Duggan, Principal Engineer at Allica Bank GitHub Copilot for @Atlassian's Jira is now generally available. github.blog/changelog/2026…

Kimi K2.7 Code is now generally available for Copilot Business and Enterprise accounts. This is the first open-weight model offered as a selectable option in the Copilot model picker, providing more choice for developers at a lower cost. Plan administrators can enable the Kimi K2.7 Code policy in Copilot settings to make it available for their organization. Learn more about Kimi K2.7 Code ▶️ github.blog/changelog/2026…

.@MicrosoftAI's MAI-Code-1-Flash is now generally available for GitHub Copilot Business and Copilot Enterprise. Built for coding and optimized for GitHub Copilot, MAI-Code-1-Flash delivers fast, low-latency responses that make it well-suited for high-volume, iterative agentic coding workflows where speed and efficiency matter most. github.blog/changelog/2026…

From "AI as autocomplete" to "AI as an agent" 🚀 The March GitHub Enterprise Roundup highlights the industry shift: moving from simple AI suggestions to governed, measurable, and auditable AI that can handle real-world engineering tasks. As GitHub’s Dave Burnison notes, the pace of innovation right now is "mind-blowing," but the goal remains consistent: "To work alongside you to make you a better, more productive developer—not replace you." 🤝 Key updates this month: Agentic Development: With the Copilot coding agent and GitHub Agentic Workflows entering technical preview, AI is shifting from suggestions to delegated execution. This allows teams to delegate tasks like planning, triage, and CI/CD reasoning while maintaining human approval and enterprise controls. 🤖 Measurable ROI: Telemetry tools, like the Copilot usage metrics API, allow engineering leaders to programmatically track pull request throughput and time-to-merge, providing data-driven evidence for AI impact. 📊 Governance at Scale: The "Required Reviewer" rule is now GA, and new organization-level dashboards for Code Quality help leaders enforce standards across thousands of repositories without manual oversight. ✅ Security Incident Response: New enterprise-wide credential management tools allow administrators to rapidly audit and revoke compromised credentials during an incident, significantly reducing "time-to-contain." 🛡️ 🔗 Read the full March roundup here: github.com/resources/insi… #GitHubEnterprise #SoftwareEngineering #AI #DevOps #TechLeadership

Community Invite: GitHub Social Club @ Amsterdam We’re hosting a GitHub Social Club in Amsterdam on Monday, March 23, and we’d love to see you there. This is a low-key hangout designed for developers, builders, researchers, founders, and the open-source community to unplug and meet others who care about the craft of building software. The Vibe: No talks, no pitches: Just good conversations, coffee, and snacks. Meet the team: Connect with Hubbers building GitHub, Copilot, and MCP. Swag: We’ll have GitHub gear and plenty of stickers. Flexible: Come solo, bring friends, drop in for a bit, or stay awhile. Event Details: 📍 Location: Ceintuur Theater, Amsterdam 📅 Date: Monday, March 23 ⏰ Time: 10:00 AM – 4:00 PM RSVP or Drop-in: luma.com/githubsocialcl… If you know developers or communities who would value this space, please feel free to share this post and invite them along. Hope to see you there. #GitHub #KubeCon #CloudNativeCon #OpenSource #SoftwareEngineering