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Want to Become an AI Council Speaker?

Speaker applications have been extended to January 30, 2026. Share the stage with engineers and technical leaders building the future of AI.

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Data-Council-Day-One-2025-72

Experts Defining the AI Frontier

AI Council features the technical pioneers shaping the AI ecosystem.

Hannes Mühleisen
Hannes Mühleisen
Co-Creator of DuckDB
DuckDB Labs
Hannes Mühleisen
Co-Creator of DuckDB
DuckDB Labs
Co-Creator of DuckDB DuckDB Labs
Naveen Rao
Naveen Rao
VP of AI
Databricks
Naveen Rao
VP of AI
Databricks
VP of AI Databricks
Denis Yarats
Denis Yarats
Co-Founder & CTO
Perplexity
Denis Yarats
Co-Founder & CTO
Perplexity
Co-Founder & CTO Perplexity
Aaron Katz
Aaron Katz
Co-Founder & CEO
Clickhouse
Aaron Katz
Co-Founder & CEO
Clickhouse
Co-Founder & CEO Clickhouse
Ryan Blue
Ryan Blue
Creator of Apache Iceberg, Member of Technical Staff
Databricks
Ryan Blue
Creator of Apache Iceberg, Member of Technical Staff
Databricks
Creator of Apache Iceberg, Member of Technical Staff Databricks
Ethan Rosenthal
Ethan Rosenthal
Member of Technical Staff
Runway
Ethan Rosenthal
Member of Technical Staff
Runway
Member of Technical Staff Runway
Mike Driscoll
Mike Driscoll
Co-Founder & CTO
Rill Data
Mike Driscoll
Co-Founder & CTO
Rill Data
Co-Founder & CTO Rill Data
View all speakers

Take the Stage at AI Council

Join a lineup of world-class builders and tech leaders presenting real frameworks and insights to the most technical AI community in the world.

Technical Depth

TECHNICAL DEPTH

We look for talks that go beyond surface-level overviews. Show us your architectural decisions, tradeoffs and reasonings behind your approach.

Prouction Insights

PRODUCTION INSIGHTS

Theory is easy; shipping is hard. We want to hear what you learned building systems that actually run at scale.

GenAI Applications

INNOVATIVE APPROACHES

If you've solved an infra or tooling problem in a novel or unexpected way, this is the audience that will appreciate it.

Evaluation Criteria: Talks are judged on technical rigor, speaker expertise, and relevance to our audience of builders.

 

Vendors are welcome, but talks should be presented by an engineer to explain how your product/tool is built, not simply a product walkthrough. For sponsored workshop opportunities, please contact community@aicouncil.com

Why Speak at AI Council?

 
Lightning Talks

Publish Strong Ideas

When you speak here, you're getting validation from peers who can tell the difference between substance and fluff. That credibility carries weight for both you and your company.

Data Science & Algos

Join an Elite Network

AI Council features past speakers from OpenAI, Anthropic, Databricks and more. If selected, you'll also get access to our exclusive VIP parties to make real connections with founders and industry leaders.

Amplify Your Impact

Amplify Your Impact

Your talk is professionally recorded and published online. Share it with leadership, use it to build credibility or let it spark conversations about your work for years to come.

Past AI Council Talks

Ideas That Become Industry Standard
Data-Council-Day-One-2025-231

Billion-Scale Vector Search on Object Storage

Simon Hørup Eskildsen, Co-Founder, turbopuffer

Mickey Liu, Software Engineer, Notion

the-future-of-data-engineering

The Future of Data Engineering in a Post-AI World

Michelle Ufford Winters, Distinguished MTS - Data & Analytics, eBay (ex- Netflix, GoDaddy, Noteable)

naveen-rao-1

Data Meets Intelligence: Where the Data Infra & AI Stack Converge

Naveen Rao | VP of AI, Databricks

George Mathew | Managing Director, Insight Partners

charles-frye-modal

What Every Data Scientist Needs To Know About GPUs

Charles Frye, Developer Advocate, Modal Labs

 

2026 Technical Tracks
Inference Systems
This track explores the systems and infrastructure powering real-time multimodal AI—from audio and video to vision, speech and mixed-modal interfaces. Talks focus on accelerating inference, reducing latency, scaling new modalities, and designing next-generation model-serving pipelines. Perfect for engineers building the frontier of interactive AI experiences.
AI Engineering
AI Engineering covers the practical workflows, tools and methodologies for evaluating, monitoring and improving AI systems in production. Topics include eval frameworks, observability stacks, guardrails, prompt testing and reliability engineering. For practitioners who keep AI systems correct, safe and performant in the wild.
AI Security & Safety
Dive deep into security, red-teaming, privacy, safety frameworks and governance for modern AI systems. Expect highly technical sessions on identifying vulnerabilities, mitigating model-level risks and building defensible enterprise AI. The right place for anyone serious about safe, trustworthy and compliant AI deployment.
Agent Infrastructure
Breaks down the architectures, planning systems, memory representations and tool-use loops that make agents work. Talks highlight emerging platforms, orchestration layers and runtime environments for agentic workflows. Ideal for developers building the next generation of intelligent, autonomous systems.
Coding Agents & Autonomous Dev
This track focuses on agents that write, modify and ship software: autonomous PR systems, IDE-integrated agents, code execution sandboxes and fully automated development flows. Sessions explore how coding agents collaborate with humans, reason over large repositories and safely produce production-grade code. For builders at the intersection of AI and software engineering.
Model Systems
Model Systems covers the full lifecycle of model development: pre-training pipelines, fine-tuning strategies, adapters, distillation, small-model architectures and RLE-adjacent techniques. Talks emphasize efficiency, scaling laws, post-training improvements and practical engineering around model quality. Designed for teams building or adapting their own custom models.
Data Engineering & Databases
This track examines the data infrastructure that fuels modern AI—vector databases, retrieval engines, pipelines, feature stores and storage systems. Talks highlight how teams architect data layers for speed, quality and relevance across multimodal and agentic workloads. Essential for everyone who believes great AI starts with great data.
Applied AI
Applied AI explores how intelligence-rich products are built by AI-driven engineering teams. This track focuses on the dual power of Applied AI: solving real-world user problems through the application of AI and radically accelerating the build process itself through use of AI-native tools. We explore how new AI-driven design and coding tools are lowering the barrier to entry, enabling lean teams to tackle complex challenges. This is for the founders and engineers harnessing this advantage to build powerful, intelligence-rich applications that were previously impossible to ship and doing this faster than ever before.
Analytics & Data Science
This track covers experimentation, causal inference, statistical modeling, testing frameworks and data-driven decision systems. Sessions explore how teams measure model performance, validate behavior, run controlled experiments and generate actionable insights. Perfect for data scientists building the analytical backbone of data & AI-driven organizations.
Lightning Talks
A rapid-fire showcase of cutting-edge ideas, tools, experiments, and prototypes across the entire AI Council ecosystem. These fast, high-density sessions surface emerging concepts and bold technical work that doesn’t fit anywhere else. Come ready to learn something new every few minutes.

 

Apply to Speak Today

 

(Even if you just have an idea, we want to hear from you).

Wes McKinney: The Future Roadmap for the Composable Data Stack

Wes reviews the progress we have made in the last 10 years developing composable, interoperable open standards for the data processing stack

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Dhruv Singh: Strategies for Assessing LLMs in Real-World Applications

Dhruv discusses practical solutions that will unlock faster iteration & more safety in GenAI, such as using tiny evaluators in an online setting & making efficient use of human feedback offline.

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DJ Patil & Joey Gonzalez: Why it Takes Billions

DJ Patil and Joey Gonzalez discuss how to navigate the AI landscape with OpenAI, Google, Nvidia and Everyone Else with Billions to Spare

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Dan Mejia & Michael Bullington: the Journey to FigJam AI

Learn about the unique development process of FigJam AI, from the inception at a hackathon to fine-tuning for specific use cases.

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Pete Hunt: Why You’ve Been Thinking About the Wrong DAG the Entire Time

Pete explains how declarative orchestration goes beyond improved developer ergonomics: it has profound consequences for the entire data platform.

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Jordan Tigani: Big Data is Dead

Jordan makes the case that the era of Big Data is over. Now we can stop worrying about data size and focus on how we’re going to use it to make better decisions.

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