Empowering OSS maintainers in the age of AI
This talk addresses how we attempt to manage the changes to Open Source Maintainership resulting from the Agentic AI approach within the Apache Software Foundation. The Apache Way is About People — AI should free maintainers to do stuff that matters, not replace them; it should empower maintainers in the Age of AI.
Building Resilience: The Next Decade of Open Source
Over 25 years, open source has become vital digital infrastructure. However, its future relies on human resilience, not just code. To combat burnout, funding gaps, and new regulations, we must move beyond old methods and address sustainability through global policy, security, and community health.
OSS Security: Lessons from 10+ Years at Apache Solr
How are security decisions big and small made in a distributed open source community? Come find out at this session where users will gain insights and examples (both good and bad) to take back to their own projects.
Mentoring In Open Source in the Age of AI
Open source mentorship changed overnight with AI tools. Contributors submitted polished code they couldn’t explain, making learning harder to assess. This talk shares what we learned mentoring Outreachy contributors—what failed, what worked, and what we’re still figuring out.
How to Survive the Vortex of LLM Change
The LLM ecosystem changes faster than most teams can adapt. This talk shares our experience and the practical lessons we’ve learned while building an intelligent search product in a world where models, tools, and best practices constantly evolve.
OpenSearch Software Foundation: 1 Year of Open Governance
In this presentation, we will talk through moving a major open source project into a foundation and the benefits of open governance, and a vendor-neutral home has proven through a sustained growth in community contributions.
AI in the physical world: from observation to discovery
In 2026, AI is moving beyond digital tasks into the physical world. It increasingly interacts with instruments, experiments, and real-world data. Physicists stand at this frontier, using deep learning, LLMs, and agents to analyze nature itself. What have we learned about AI when it meets reality?