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| OSA Con 2026 - The Anti-Hype Conference For Open Source Analytics & AI
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| With Lisa Cao (Developer Relations - Open Source, Databricks), Wei-Chin Call (Staff Emerging Products Manager, Grafana Labs), Jason Smith (Staff Customer Engineer, Google), Aditi Pandit (Principal Engineer, 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 Software Foundation), Brandon Wilcox (Director of Engineering, 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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