Data Council AI 2026 | SF

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Real Industry Intelligence

For over a decade, Data Council AI has gathered the engineers behind breakthrough AI & data systems. Our community consists of the researchers who have solved training at scale, the architects optimizing inference pipelines and the engineers shipping models to millions of users.

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Technical Attendees

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Speakers

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Office Hours

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Hands-On Workshops

Powered by AI's Leading Companies

Data Council AI 2026 - SAN FRANCISCO

About the Venue

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San Francisco Marriot Marquis

780 Mission St San Francisco CA March 25 - 27 2025

Speakers Who Ship Code, Not Slides

Past Data Council AI speakers aren't just talking figureheads - they're the engineers & scientists building production systems, the architects handling billion-parameter inference and the technical experts solving AI's hardest challenges.

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Matei Zaharia

Co-Founder & CTO

Databricks

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Jake Brill

Head of Product, Integrity

OpenAI

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DJ Patil

Former U.S Chief Data Scientist & Investor

GreatPoint Ventures

Lukas Biewald

Lukas Biewald

Founder & CEO

Weights & Biases

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Joseph Gonzalez

Professor & Co-Founder

UC Berkeley & RunLLM

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Paige Bailey

AI Dev Relations Lead

Google DeepMind

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Denis Yarats

Co-Founder & CTO

Perplexity

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Michele Catasta

President & Head of AI

Replit

CFP for 2026 announced this fall!

CFP for 2026 announced this fall!

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Beyond the Slides Conference

Technical Deep-Dives
Engineering Office Hours
Hands-On Workshops
Events & Networking

Subscribe for Updates

Technical Deep-Dives

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Get direct insights on production systems and architectural decisions from technical leaders. Our hand-selected speakers don't just present — they pull back the curtain on real implementations, complete with performance metrics and hard-learned lessons.

Engineering Office Hours

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A Data Council AI exclusive! Our signature office hours get you dedicated time with speakers for in-depth discussions in a small group setting. Meet your heroes face-to-face, debug your architecture challenges, expand on strategies and discuss the future of AI with the leaders building it.

Hands-On Workshops

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Build alongside the maintainers of production AI systems. These aren't just tutorials—they're intensive technical sessions where you'll implement real solutions with guidance from the people who architected them.

Events & Networking

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Get access to dozens of exclusive community-curated events where engineering discussions continue in fun, low pressure environments where the real connections happen. From our Community Drinks & Demos night to founder dinners to firesides, you won't want to miss out!

2026 Technical Tracks

Comprehensive coverage across the AI and data stack

AI Engineering

This track goes deep into the skills and toolchain every AI engineer must know to build, deploy and scale AI systems. Example topics covered include model selection & evaluation, RAG, vector & graph search, fine-tuning, agent orchestration, data prep and testing/deployment/monitoring. Learn how to build robust, scalable AI systems using the latest tools in AI engineering.

Data Engineering & Infra

Data Engineering & Infrastructure focuses on modern data engineering workflows, storage systems, design patterns and more. Themes in this track are centered around the most important pieces of the data pipeline workflow: data-ops, data quality, ingest & ETL/ELT, monitoring, metadata, streaming and other issues pertaining to the modern data stack.

AI Applications

This track explores the practical applications of GenAI across industries. We discuss how orgs can innovate in content creation, automation, customer engagement, and product development. Sessions will delve into real-world case studies of AI architectures, best practices for integrating GenAI into existing workflows and the ethical considerations surrounding its use.

Data Science & Algos

The Data Science & Algorithms track is focused on helping data science professionals be more effective in their role. We discuss helpful algorithms, modern research and data science frameworks & methodologies that can be useful in data science functions across the enterprise.

Foundation Models

Focuses on the rapidly evolving landscape of foundation models, such as large-scale language models, multimodal models, and AI systems that serve as the backbone for a wide range of AI applications. Sessions will discuss how model providers think about their customers; how AI developers can use their tools and APIs to build incredible experiences. This track will also feature a debate on where value lies: at the model layer, or beyond.

Analytics & BI

The Analytics & BI track focuses on tools and techniques for data analysts, covering topics such as Business Intelligence (BI), customer analytics, A/B testing and data visualization. You’ll learn about how top teams are solving their analytics challenges and discover the best new tools in the process.

AI & Data Culture

Data Culture is a place for data leaders to share stories and insights on how they have built vibrant, cross-functional, and collaborative spaces for their teams. Whether you are building a data team from scratch, establishing a strong data culture within your organization or rallying a global network of developers around your software, you’ll have plenty to learn from our speakers who have done it all.

Lightning Talks

The Lightning Talks track is composed of 15min, bite-size sessions from various startups sharing lessons learned & best practices of their fast-growing companies. You can learn about new tools & approaches that startups use, cutting-edge open source projects, and data teams' lessons learned from supporting their company growth.

Databases

This track dives into the evolving world of databases, covering both traditional relational systems and emerging database technologies designed to handle the complexities of modern & unstructured data. Topics will include the latest trends in database architecture, performance optimization, distributed databases, and data management for AI and analytics workflows. Attendees will learn how to design, scale, and secure databases to meet the demands of high-performance applications, data-driven decision-making, machine learning & AI. This track is ideal for database engineers, data architects, and anyone interested in mastering data infrastructure in today’s dynamic tech landscape.

MLOps & Platforms

This track focuses on the engineering behind existing and novel machine learning systems, frameworks and tooling. You’ll learn about topics such as data preparation, feature engineering, model quality & monitoring, ml-ops, and best practices in generalizing ML workflows.

What Industry Leaders Are Saying

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Pedram Navid, Head of Developer Relations

“Data Council is better than any conference I’ve ever been at because the talks are a higher caliber than anything I’ve ever experience, and the people here are just second to none.”

Charles Frye

Charles Frye, Developer Advocate

“The people who work on the tools that you use every day, the people you admire, they’re there. They want to share what they’ve been working on.”

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Ryan Boyd, Co-Founder

“Data Council is great because it provides an intimate setting for interacting with other folks in the data industry, whereas other conferences you may not know anyone you meet in the hallways.”

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