The GitHub Universe 2026 schedule just dropped, and it’s full of exciting sessions, demos, and panels covering the potential of AI-powered development.

If you haven’t registered yet, here’s what you need to know. This two-day event brings together some of the greatest minds in tech, with experts from companies like AMD, Figma, NVIDIA, Coinbase, Anthropic, and OpenAI leading our sessions. They’re covering everything from delegating real work to Copilot and measuring AI at enterprise scale to fine-grained security for MCP servers. You’ll also have the chance to chat with the GitHub team one-on-one, get your questions answered, and even pick up some career advice.

Did we mention the Ship & Tell sessions where teams show what they’ve built, and partner booths where you can demo the latest tech?

When: October 28-29
Where: Fort Mason Center, San Francisco, CA

One thing first: register before August 19 and save $300 with Early Bird passes. Prices go up after that, so if Universe is already on your list, now’s the moment. The best part? You can stack savings with our group discounts.

Here’s a sneak peek of some of the sessions we have planned. You can jump to the full agenda right here. Be sure to mark your favorites to build your own personal calendar.

Find your flow

Some of the best moments at Universe happen heads-down: working through a real problem, configuring something on your own machine, and walking out with a project you can actually use. This year’s catalog leans into that with learnings you can take straight back to your repositories.

A few sessions to start with:

Stop prompting, start delegating: Configure Copilot to own the work
Ken Muse, GitHub; Mickey Gousset, GitHub
Learn how the right Copilot configuration turns AI into something you can trust with complex tasks. Layer Copilot’s full stack onto a TypeScript app, and you’ll leave with a working project and a clear sense of which capability fits which task, so you can delegate more and prompt less.

Inside GitHub Copilot’s coding harness: Optimizing across every model
Julia Kasper, Microsoft
Shipping a coding agent that works across OpenAI, Claude, Gemini, and whatever drops next week takes a harness. See the evaluation framework the GitHub Copilot team uses to test and optimize its agent across every model: reproducible benchmarks, thousands of autonomous coding tasks, and LLM-graded assertions that catch regressions before users do.

Stop waiting on your own pull requests: GitHub stacked pull requests in practice
Sameen Karim, GitHub
Stacked pull requests let you split changes into smaller, dependent pull requests that move through review efficiently while preserving the full picture. This demo builds a stack with the GitHub CLI, reviews it on github.com, and merges each pull request as it’s ready—so you leave with a workflow you can use tomorrow.

Find your people

Hallway conversations, a question that reframes your whole approach, the engineer who already solved the thing you’re stuck on. This year’s agenda is filled with sessions for exactly that. Plus, hallway tracks, partner booths, and Ship & Tell sessions where teams show what they’ve actually built.

A few sessions worth your time:

Building AI fluency at UPS
Jared Hatfield, UPS
Getting developers to try GitHub Copilot is simple; getting them fluent with it—using agents to plan, write, and ship real work—is the harder challenge. See how UPS moves developers from awareness to fluency, why motivation and measurement matter as much as the tooling, and where to focus first at enterprise scale.

Code is the easy part: Building Home Assistant in the open
Franck Nijhof, Open Home Foundation
“Building in the open” usually means one thing: code on GitHub. But the hard work starts long before code—ideas, UX, design, architecture, the roadmap itself. At Home Assistant, every step happens in the open across 20,000 contributors and a dozen GitHub organizations. See how the Open Home Foundation runs its whole roadmap with issues, projects, and discussions, including the harder parts, like being wrong in public, fixing it in public, and proving you don’t have to be technical to contribute.

I made my Octolamp think with GitHub Copilot CLI hooks
Beatris Mendez Gandica, Nuevo Foundation
What if your desk lamp could show when GitHub Copilot CLI is thinking? Using the native hooks system, Beatris Mendez Gandica made hers breathe green when the agent works, go white when idle, and blink red on errors. No prompting tricks, just system-level lifecycle events driving a physical light via the WLED API. In this session, you’ll see how Copilot CLI hooks work under the hood, and leave knowing how to write your own for any use case.

Build what’s next

Want to know what’s on the horizon? These are the talks that pull back the curtain on where AI-assisted development is heading.

The view from the labs: What’s next for AI-assisted development
Cara Phillips, Anthropic; Rohan Varma, OpenAI; Kate Catlin, GitHub
The people building frontier AI models see where capabilities are heading before anyone else. This interactive panel brings leaders from Anthropic, OpenAI, and other labs that power GitHub Copilot together for a candid look at the next two years of AI-assisted development, and what it means for you.

Open pull requests, don’t merge them: Fine-grained authorization for hosted MCP servers
Nick Taylor, Pomerium
Hosted MCP servers hand every agent everything its human can do: OAuth in, broad scope out, one global toggle. But what if an agent should open a pull request and leave the merge to a reviewer? See a pattern that works today: an identity-aware proxy that adds per-identity authorization in front of any hosted MCP server with no changes upstream, demonstrated live with Copilot doing exactly that.

From writing code to managing agents: Scaling 50+ services at GitHub
Anjuan Simmons, GitHub
GitHub’s Lifecycle team traded hand-coding fixes across 50+ services for an agentic pipeline where AI agents classify issues, research codebases, write implementation plans, and open draft pull requests automatically. Get the real lessons and numbers from running it at GitHub’s own scale: how it was built with GitHub Actions and Copilot, where automation pays off most, and why engineers still deliberately write some code by hand.

Cast your vote!

Three breakout sessions are heading to Universe this year, but we need your help deciding which one makes it to the main stage. Read through the descriptions, then cast your vote before August 21. Whichever session wins will also be available on demand, so even if you can’t join us in person, your vote shapes what you’ll get to watch later.

Session 1: Why sketching in code matters more in the age of AI
Qianqian Ye, Processing Foundation / University of Southern California; John Maeda, GitHub
AI can generate clean, working code from a short prompt, so the real question now is how to understand what’s been made. Qianqian Ye draws on teaching creative coding at USC and leading p5.js to show why sketching and thinking in code builds the intuition to shape systems, not just prompt them.

Session 2: Still open: How AI reshaped open source
Angie Jones, Agentic AI Foundation; David A. Wheeler, The Linux Foundation; Priya Pahwa, Django Software Foundation
Open source is being stress tested. While AI has accelerated contributions, it’s also raised hard questions about quality, governance, and the power of community when bots can contribute at machine scale. In this session, you’ll learn why AI makes open source more essential than ever.

Session 3: The human side of AI: How building community drove 94% Copilot adoption
Brittany Istenes, Independent
What if scaling AI isn’t about better models, but better human connection? A large U.S.-based financial services firm hit 94% Copilot adoption and 78% agent-written code, and the driving force was community, not tooling. In this session, you’ll discover how grassroots engagement, storytelling, and innersource made AI something developers actually wanted to use and build together.

Cast your vote

Learn more

Want to get even more out of your GitHub Universe experience?

When you register, you can add a Day of Learning pass for $50, which includes access to a full day of learning at GitHub HQ plus one GitHub Certification exam voucher.

Already have your agenda planned? You can also purchase a GitHub Certification exam voucher as a standalone add-on for $30 and validate your skills after the event.

See you in SF!

Explore add-ons >

The post Your guide to GitHub Universe 2026 is here: The schedule just launched! appeared first on The GitHub Blog.

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