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Make the Border Is Porous panel an hour and drop the 20-hour wording
The panel with Mimi Flynn, Mark Paulsen, and Peter Smulovics now runs a full hour, so every Americas session after it moves 30 minutes later.
Also fixes the malformed time cell on Fei Wan's session.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01J9z4tBNNnRxcD24cpdC2P7
Copy file name to clipboardExpand all lines: content/en/events/isc-2026.md
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On Thursday, November 12th, InnerSource Summit 2026 will unite the global InnerSource community online for a 20-hour, around-the-world event spanning every timezone! We will be featuring the industry's top speakers, inspiring stories, and cutting-edge ideas shaping the future of collaborative software development.
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On Thursday, November 12th, InnerSource Summit 2026 will unite the global InnerSource community online for an around-the-world event spanning every timezone! We will be featuring the industry's top speakers, inspiring stories, and cutting-edge ideas shaping the future of collaborative software development.
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Discover the Power of InnerSource!
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The bar for contributing to other projects has been lowered, but what does this mean for maintainers?
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In this talk a seasoned InnerSource Officer will bring food for thought on how AI can impact the collaboration style prescribed by InnerSource, for the best of for the worst, and share ideas on how to navigate this ever-changing terrain. We will also look into intrinsic benefits we expect to have with AI, but also, where a human push is still needed.
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What if scaling AI isn't really about adoption, but about what a community creates once people start using it together? Within a large U.S.-based financial services firm, 94% GitHub Copilot adoption and 78% agent-written code were only part of the story. The bigger outcome was turning individual experimentation into repeatable, discoverable patterns through shared skills, prompt, and harness libraries.
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By applying InnerSource principles alongside grassroots engagement, storytelling, and community building, teams could contribute what worked, learn from one another, and build on proven approaches instead of continually starting from scratch. This session explores how AI adoption became a catalyst for a shared collective of knowledge—and how measuring reuse, contribution, and impact can tell a much more meaningful story than adoption alone.
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<tdclass="UTC">UTC 18:30</td>
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<tdclass="UTC">UTC 19:00</td>
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<td class="time">15:00 EST</td>
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<td class="time">15:30 EST</td>
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<tdclass="author w-70"> <b><ahref="#Isaac_Johnson">Isaac Johnson </a></b><br>(Abbott)<br>
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Attendees should walk away with a good handle on how to make a skill and MCP server, and when. More importantly, how we can reliably share with easy to maintain repositories in GIT.
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The sharing aspect of skills truly leads to democratization of Gen AI improvements and drives at the core of Inner Sourcing.
3. How do you get started? Choose one measurable use case, connect a small set of authoritative information sources, define access and ownership rules, launch a simple question-and-answer experience, and create a feedback loop that turns unanswered questions into durable organizational knowledge.
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4. How do you measure success? Track faster answers, increased project reuse, greater contributor participation, fewer repeated questions, and less time spent locating information or experts.
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InnerSource is often associated with opening source code internally so that teams can discover, reuse and contribute to each other's work. But in enterprise software, source code is only one part of what teams need to build and operate a product. There is also a lot of knowledge around privacy, security, compliance, architecture and operational practices that can be difficult for other teams to discover and reuse.
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I have seen this challenge firsthand in privacy engineering. A product may be considered compliant with a privacy requirement, but when a customer, auditor or internal stakeholder asks, "How?", finding the answer can be much harder. The information may be spread across product documentation, architecture decisions, privacy assessments and the people who have worked on the product. This talk explores whether we can apply InnerSource principles such as transparency, discoverability, reuse and contribution to this problem. What if contributors were expected not only to contribute code, but also to make the privacy implications of their work and the "how" behind compliance understandable and discoverable? I will share some ideas for what an InnerSource approach to privacy compliance could look like and invite the community to think about where else InnerSource can go beyond code.
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But when you can build almost anything, the hardest question is no longer *how*. It is *what...and why*.
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In this keynote, Scott Hanselman explores what happens when creation becomes abundant. Through stories, code, and practical examples, he examines the new skills that matter: judgment, taste, curiosity, empathy, and the discipline to understand the problem before generating the solution. The future will not belong simply to those who can build the most. It will belong to those who choose carefully, build responsibly, and create things genuinely worth having together.
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