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Join us for a final session of open source voices, unexpected demos, and the kind of nerdy joy that reminds you why you got into this in the first place. The #GitHubUniverse Day 2 Keynote starts now 🎉

Time to commit to the answer ⏰ Did you get them correct? #GitHubUniverse

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17.9 billion pushes. 34.3 billion commits. 1.3 billion pull requests merged. All in the last year. Developers pushed code to GitHub more times in the past 12 months than in 2024 and 2025 combined with merged pull requests, averaging 3.5 million a day. Dive into the data behind how developers are building now with this year's Octoverse report. ⬇️

Catching up on #GitHubUniverse? From Copilot Fusion to infrastructure investments, here's what you missed from the day 1 keynote.

Unboxing the #GitHubUniverse blind box keyboard ⌨️

RT @msdev: The @github engineering team built a best-in-class, truly multi-model harness, which we've implemented across Microsoft products. Introducing Microsoft Copilot harness in Foundry Agent Service, a simpler way to build agents without rebuilding the execution layer. It handles orchestration, tools, context, and controls so you can focus on your agent’s skills and outcomes. Watch @jeffhollan's demo to see it in action.

What it means to be a developer has changed, but the goal of completing meaningful software work remains the same. Today we shipped some updates to help you create while staying in control of what actually ships. ⬇️

Copilot Automations ⚙️ Every developer has work they shouldn’t have to repeat. Define the job once, then run it on demand, on a schedule, or in response to activity in GitHub or a connected service. Share automations with your team and set their access, actions, and spending limits.

Check out everything we launched today 👇

RT @jayparikh: Today at #GitHubUniverse we laid out how we're evolving GitHub for the agentic era. Check it out:

#GitHubUniverse 2026 begins now! 🎉 Watch the Day 1 Keynote 👇

Join Universe Insider right after the keynote for live demos and deeper dives from today's announcements!

RT @ArtificialAnlys: GitHub has released Copilot Fusion in GitHub Copilot, which orchestrates between Anthropic and OpenAI models. It scores 2 points below Opus 5.5 in Claude Code at half the Cost per Task in the Coding Agent Index GitHub describes Copilot Fusion as a runtime orchestration system, which selects and coordinates models to optimize performance, cost, and latency for each task. Copilot Fusion chooses between a number of models from Anthropic and OpenAI, including Claude Opus 5.5, Claude Sonnet 5.5, GPT-6 Astra, and GPT-6 Sol. We benchmarked its max setting in GitHub Copilot CLI in the Artificial Analysis Coding Agent Index v2.0. Token costs are charged based on the underlying models used to complete a request. Key takeaways: ➤ Cost-efficient for near-frontier performance: Copilot Fusion in GitHub Copilot costs $5.59 per task, versus $11.42 for Claude Code with Opus 5.5 (max). Devin Fusion with Opus 5.5 (max) + GPT-6 Luna (high) scores 62 at $8.00 per task. ➤ Slight lead in Terminal-Bench 4.0: The Coding Agent Index v2.0 weights its three constituent benchmarks equally. Copilot Fusion in GitHub Copilot leads Terminal-Bench 4.0 with a score of 71. It ranks third on FrontierCode in the chart at 51, behind Claude Code with Opus 5.5 (max) at 56 and Devin Fusion with Opus 5.5 (max) + GPT-6 Luna (high) at 54. Its SWE-Atlas-QnA-AA score lags at 57, between GPT-6 Astra in Codex and Gemini 4 Argon in Antigravity CLI. ➤ Half the token use of Opus 5.5 in Claude Code: GitHub Copilot Fusion used 7.2M tokens per task in the Coding Agent Index, approximately half of the tokens used by Claude Opus 5.5 in Claude Code, and 30% less than Devin Fusion with Opus 5.5 (max) + GPT-6 Luna (high).

Frontier performance at a fraction of the cost. In the @ArtificialAnlys Coding Agent Index, Copilot Fusion Max scored within two points of Claude Code with Opus 5.5 Max at about half the API cost per task. Get 30% off through Nov. 30. Try it now. ⬇️

GitHub commissioned and funded this evaluation by @ArtificialAnlys. Full results and methodology: