I am so excited to share that I’ve been elected to the Kubeflow Steering Committee! 🎉
Kubeflow
Kubeflow is an open-source platform that makes artificial intelligence and machine learning simple, portable, and scalable that was originally introduced by Google. Kubeflow is an ecosystem of Kubernetes based components for each stage in the AI/ML Lifecycle with support for best-in-class open source tools and frameworks.

Thank you
I am grateful to the friends, colleagues, mentors, and the Kubeflow community for placing their trust in me. I want to especially thank those that shared such kind words: Yuan Tang, Willem Pienaar, Max Mitchell, Matt Green, Matteo Mortari, Jesse Collins, Eder Ignatowicz, Hao Xu, Christian Zaccaria, Anish Asthana, Edson Tirelli, Shuchu Han, Ross Briden, Antonin Stefanutti, Mark Campbell, Varsha Prasad, and Josh Bottum.
Kubeflow is a vital part of the AI/ML ecosystem, and I’m honored to contribute to its growth and success.

Goals
We are at a critical moment in time for AI/ML. Open-source models have taken center stage, and resilient, scalable infrastructure has become critical to the success of AI. However, infrastructure alone is not enough—tools must inspire excitement and engagement among users.
As a member of the Steering Committee, I will focus on several key items:
Expanding Kubeflow Adoption: increasing awareness, adoption, and engagement through collaborations with enterprises and startups.
Making RAG a first class priority: the AI community has settled on Retrieval Augmented Generation (RAG) as a critical component for production AI. I will work to make this a new focus area for Kubeflow.
Engaging and Empowering AI Engineers: supporting software engineers integrating AI/ML into their products by providing intuitive workflows and intelligent defaults.
Improving the User/Developer Experience for Model Developers/Users: simplifying workflows and enhancing usability to reduce barriers to entry.
Building a more Feature-Complete AI/ML Platform: driving development of critical features to support end-to-end AI/ML workflows.
Improving Documentation: ensuring comprehensive, user-friendly docs and resources for the community.
Strengthening the Community: fostering a vibrant, inclusive contributor and user ecosystem to support Kubeflow’s long-term growth.
Kubeflow is already a robust and scalable platform, but expanding its relevance and audience is essential. By focusing on AI Engineers and Data Scientists, we can ensure Kubeflow not only remains at the forefront of AI/ML innovation but also inspires excitement and engagement among the broader community.
Why this Matters
The AI/ML landscape is evolving rapidly, with open-source tools and scalable infrastructure taking center stage. I believe Kubeflow is at the forefront of this transformation, and together, we can help build the future of production AI using open-source, resilient, and enterprise-grade software.
Join the Fun
If you're building in AI and want to learn about Kubeflow, let’s connect! If you’re not familiar with Kubeflow, now is the perfect time to see how we can help you scale your AI/ML products. Come join our Slack community, a community call, or feel free to reach out to me!
Thank you again to the Kubeflow community for this incredible opportunity. It’s time to build! 🚀
With gratitude,
Francisco 🤠