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| OSA Con 2026 - The Anti-Hype Conference For Open Source Analytics & AI
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| With Lisa Cao (Dev Relations - Open Source, Databricks), Wei-Chin Call (Emerging Products, Grafana Labs), Jason Smith (Customer Enggr, Google), Aditi Pandit (Principal Enggr, IBM), Alex Merced (Head of DevRel, Dremio), Heather Meeker (Roman Shaposhnik), David Morrison (Founder - Research Scientist, Applied Computing Research Labs), Patrick McFadin (Principal Advisor, McFadin Data & AI Advisory), Felicitas Pojtinger (Head of Research And Development, Loophole Labs), Matthew Topol (Founder, Columnar / Apache S/w Foundation), Brandon Wilcox (Dir. Engg, Gamebeast). |
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Nov 02 (Mon) @ 09:30 AM
FREE
| | AWS Builder Loft, 525 Market St, Courtyard Entrance, SF
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For in-person attendees: Please register here as well as on AWS Builder Loft page to secure your spot: https://events.builder.aws.com/ReRbol
2026 is the year agentic AI finally works, & it's changing open source analytics.
OSA Con 2026 brings together engineers, architects, & builders working at the intersection of open source data infrastructure & AI. No vendor pitches or 10x AI miracles. Just deep technical talks from great engineers building stuff that works.
We'll get into AI workloads & data management, agents building & operating analytic platforms, & analytics powering autonomous actions, alongside what's happening in real-time analytics, shared data lakes, & emerging open-source architectures.
Nov 2 AWS Builder Loft, San Francisco + Online [Free to attend / Limited in-person capacity]
Speakers
See their abstracts at osacon.io
Lisa Cao - Databricks: Getting AI agents to write better Apache Spark pipelines
Wei-Chin Call - Grafana Labs: Benchmarking AI agents that debug your dashboards
Jason Jay Smith - Google: Serverless eventing for simpler, scalable AI data pipelines
Aditi Pandit - IBM: Inside the Presto C++ engine: production experience, performance & the 2026 roadmap
Alex Merced - Dremio: Building the Open Agentic Lakehouse for data + AI
Heather Meeker, Roman Shaposhnik (Panel discussion): Whose Code Is It Anyway? AI-generated code, ownership & open-source licensing
David Morrison - Applied Computing Research Labs: 10 infrastructure dashboards you can't build with Grafana
Patrick McFadin - McFadin Data & AI Advisory: Why we're still paying rent on our own data-and where lock-in is moving
Felicitas Pojtinger - Loophole Labs: Building legacy-free RISC-V Kubernetes clusters with ClickHouse
Matthew Topol - Columnar / Apache Software Foundation: What it really takes to run ADBC in production
Brandon Wilcox - Gamebeast: Building AI-powered LiveOps & analytics for gaming
MORE COMING SOON
What to Expect
Deep technical sessions from engineers building & running analytics platforms in production
AI agents, model evaluation, real-time analytics, data lakes, & modern open-source infrastructure
Architecture, performance, scalability, reliability, & cost-without the vendor pitches
Meet engineers, architects, maintainers, & open-source contributors building the next generation of data systems
Who Should Attend
Data engineers & analytics engineers
Platform engineers working on data infrastructure
Architects & technical decision-makers designing analytics systems
Anyone interested in the intersection of analytics, AI, & modern data platforms
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