Uploaded June 2026 | Updated September 2026, 2 weeks ago
[2026 - DAY 3 - LIGHTNING TALK] After more than a decade of limited innovation, the modern data stack is still slow, fragmented, and painfully repetitive. Every new dataframe library promises better ergonomics or performance, yet converges on the same API with the same limitations. The failure isn’t execution or scale, it is ignoring that appearance doesn't matter anymore: Agents and AI-first developers couldn't care less about how an API looks today. In this talk we’ll examine why the dataframe paradigm keeps reproducing itself, why it consistently underdelivers, and why the data stack’s biggest problems were never going to be solved at the API layer first. Princess Leia once put her trust into Obi-Wan Kenobi - what if we did the same with simple Python functions? Could we defeat the evil empire of DataFrame APIs?
SPEAKER:
Leonhard Spiegelberg - Member of Technical Staff, OpenAI
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ABOUT AI COUNCIL:
AI Council brings together the brightest minds in data to share industry knowledge, technical architectures and best practices in building cutting edge data & AI systems and tools.
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X: https://x.com/aicouncilconf
[2026 - DAY 3 - LIGHTNING TALK] After more than a decade of limited innovation, the modern data stack is still slow, fragmented, and painfully repetitive. Every new dataframe library promises better ergonomics or performance, yet converges on the same API with the same limitations. The failure isn’t execution or scale, it is ignoring that appearance doesn't matter anymore: Agents and AI-first developers couldn't care less about how an API looks today. In this talk we’ll examine why the dataframe paradigm keeps reproducing itself, why it consistently underdelivers, and why the data stack’s biggest problems were never going to be solved at the API layer first. Princess Leia once put her trust into Obi-Wan Kenobi - what if we did the same with simple Python functions? Could we defeat the evil empire of DataFrame APIs?
SPEAKER:
Leonhard Spiegelberg - Member of Technical Staff, OpenAI
👉 Sign up for our "No BS" Newsletter to get the latest technical data & AI content: aicouncil.com/newsletter
ABOUT AI COUNCIL:
AI Council brings together the brightest minds in data to share industry knowledge, technical architectures and best practices in building cutting edge data & AI systems and tools.
FIND US:
Website: aicouncil.com
LinkedIn: linkedin.com/company/aicouncilconf
X: https://x.com/aicouncilconf
![More Than Query Future Directions of Query Languages, from SQL to Morel
[2025 - Day 2 - Analytics & BI] Julian Hyde shares insights from the evolution of query languages, exploring what we want from modern data languages and introducing Morel, which combines functional programmings type system with declarative query efficiency. This talk offers valuable perspectives on extending SQL and replacing todays data frameworks, particularly relevant for engineers working across data engineering, data science, analytics, and mathematical optimization domains.
ABOUT THE SPEAKER:
Julian Hyde, Senior Staff Engineer, Google -
🎟️ GET YOUR TICKET TO AI COUNCIL 2026 🎟️
Meet the worlds top AI infrastructure minds where architects of AI share what works. Three days of high-quality technical talks and meaningful interactions.
→ https://aicouncil.com/sf-2026
⚡ FIND US:
X: https://x.com/AICouncilConf
LinkedIn: https://www.linkedin.com/company/aicouncilconf/
Website: https://aicouncil.com/ More Than Query Future Directions of Query Languages, from SQL to Morel](https://i.ytimg.com/vi/xwFsXVyMAN0/mqdefault.jpg)


![Trillion is the New Billion: Managing Really Large Multimodal Datasets for AI | LanceDB
[2026 - DAY 2 - AI ENGINEERING] Most AI problems are really data problems. AI workloads bring with them ever larger amounts of data from multiple modalities (e.g., text, images, audio, video, sensor data). If you were indexing say, the internet, you need to solve a number of new data infra challenges:
1. Storing large blobs and avoiding copying them over and over during processing
2. Dealing with much larger table sizes: trillion rows with a capital T
3. Supporting workloads like Search, Curation, and Training directly from your dataset instead of having to move data to/from point-solution systems
4. Dealing with *really* distributed pipelines: what happens when your storage, CPUs, and GPUs are with different clouds / vendors?
In this talk we will dive into detail on why its challenging to manage trillion scale wide tables with multimodal data. Well see why existing data infra doesnt support new these data types, workloads, or scale. And well do a quick under the hood peek at how Lance format and LanceDB solves these problems at a foundational level. Zooming out, well cover how LanceDB fits into the existing data stack alongside Iceberg. Finally, well talk through our roadmap and show you the big improvements were working on in 2026.
Whether youre looking to do large scale search or building the next frontier model, this will help you scale easier, get to production faster, and save on infra cost.
SPEAKER:
Lei Xu - Co-founder & CTO, LanceDB
👉 Sign up for our No BS Newsletter to get the latest technical data & AI content: https://aicouncil.com/newsletter
ABOUT AI COUNCIL:
AI Council brings together the brightest minds in data to share industry knowledge, technical architectures and best practices in building cutting edge data & AI systems and tools.
FIND US:
Website: https://aicouncil.com/
LinkedIn: https://www.linkedin.com/company/aicouncilconf/
X: https://x.com/aicouncilconf Trillion is the New Billion: Managing Really Large Multimodal Datasets for AI | LanceDB](https://i.ytimg.com/vi/z01r8DYsY0I/mqdefault.jpg)
![How Product and Research Build Together at the Frontier | Hex
[2026 - DAY 1 - WORKSHOP] What do you build when underlying model capabilities keep changing every few weeks? How do you balance long-horizon bets with the pressure to deliver value now? What even is product management in 2026? In this practical, AMA-style conversation, Hex’s AI research and core product leads will share what they’ve learned building agentic products together at the frontier: how product and research challenge each other, make decisions under uncertainty, what has worked (and what hasn’t), and how they turn fast-moving capabilities into complex products that people actually use.
SPEAKERS:
Izzy Miller - AI Research Lead, Hex
Olivia Koshy - Core Product Lead, Hex
👉 Sign up for our No BS Newsletter to get the latest technical data & AI content: https://aicouncil.com/newsletter
ABOUT AI COUNCIL:
AI Council brings together the brightest minds in data to share industry knowledge, technical architectures and best practices in building cutting edge data & AI systems and tools.
FIND US:
Website: https://aicouncil.com/
LinkedIn: https://www.linkedin.com/company/aicouncilconf/
X: https://x.com/aicouncilconf How Product and Research Build Together at the Frontier | Hex](https://i.ytimg.com/vi/zFrf7YWqWYM/mqdefault.jpg)

![OramaCore: A Search Database with LLMs Built In
[2025 - Day 3 - Lightning Talks] Issac J Roth shares insights from building OramaCore, a database with multiple LLMs and a JavaScript engine running in the same GPU-powered process, exploring why this architecture creates the ultimate platform for agentic AI applications. For developers creating SaaS Copilots and answer engines, this fast-paced talk offers valuable perspectives on the construction, algorithms, and performance optimizations behind this newly open-sourced database designed specifically for AI workloads.
ABOUT THE SPEAKER:
Issac J Roth, Co-Founder & CEO, Orama -
🎟️ GET YOUR TICKET TO AI COUNCIL 2026 🎟️
Meet the worlds top AI infrastructure minds where architects of AI share what works. Three days of high-quality technical talks and meaningful interactions.
→ https://aicouncil.com/sf-2026
⚡ FIND US:
X: https://x.com/AICouncilConf
LinkedIn: https://www.linkedin.com/company/aicouncilconf/
Website: https://aicouncil.com/ OramaCore: A Search Database with LLMs Built In](https://i.ytimg.com/vi/zwO6p8J9LLU/mqdefault.jpg)