Uploaded June 2026 | Updated September 2026, 2 weeks ago
[2026 - Day 1 - AGENT INFRASTRUCTURE] Agents are great, but they place difficult requirements on the underlying infrastructure they run on: (1) they need to be strongly isolated (eg, within a VM); (2) they need to start up as quickly as possible (ideally in milliseconds) and put to sleep when not used; and (3) they require massive scale (eg, millions of them for even a single provider/product). Using standard infra to run sandboxes at this level of scale can result in eye-watering cloud-infra bills. And attempting to start sandboxes in milliseconds is an unsolved challenge.
In this talk we’ll cover our years-long journey aimed at severely optimizing and increasing the efficiency of how workloads are deployed on the cloud, beginning with research and OSS work. Along the way, we’ll cover the basics of virtualization and isolation primitives (e.g., virtual machines, microVMs, containers, isolates) and their performance and security trade-offs. With that in place, we will describe how we leveraged the research and OSS work to build a virtualization system that can start any workload in a few milliseconds, and cram up to 1M+ such lightweight VMs into a single, off-the-shelf server, allowing for millions of strongly-isolated agents to be hosted in a rack, rather than an entire data center. Finally, we will show a brief live demo of this in action.
SPEAKER:
Felipe Huici - CEO & Co-founder, Unikraft
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[2026 - Day 1 - AGENT INFRASTRUCTURE] Agents are great, but they place difficult requirements on the underlying infrastructure they run on: (1) they need to be strongly isolated (eg, within a VM); (2) they need to start up as quickly as possible (ideally in milliseconds) and put to sleep when not used; and (3) they require massive scale (eg, millions of them for even a single provider/product). Using standard infra to run sandboxes at this level of scale can result in eye-watering cloud-infra bills. And attempting to start sandboxes in milliseconds is an unsolved challenge.
In this talk we’ll cover our years-long journey aimed at severely optimizing and increasing the efficiency of how workloads are deployed on the cloud, beginning with research and OSS work. Along the way, we’ll cover the basics of virtualization and isolation primitives (e.g., virtual machines, microVMs, containers, isolates) and their performance and security trade-offs. With that in place, we will describe how we leveraged the research and OSS work to build a virtualization system that can start any workload in a few milliseconds, and cram up to 1M+ such lightweight VMs into a single, off-the-shelf server, allowing for millions of strongly-isolated agents to be hosted in a rack, rather than an entire data center. Finally, we will show a brief live demo of this in action.
SPEAKER:
Felipe Huici - CEO & Co-founder, Unikraft
👉 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
![Benchmarking AI Agents Against Realistic Analytical Tasks with ADE-bench
[2026 - DAY 2 - CODING AGENTS] There are many benchmarks that attempt to measure how well LLMs and AI agents can write SQL queries or do complicated statistical analysis. But as most practitioners know, this is only a small part of our job. Before we can write a query, we have to figure out the business context behind the question. We have figure out which tables to use in a messy database. We have to make subjective decisions about vaguely defined problems. All of this makes benchmarking analytical agents difficult.
We built a new benchmark—ADE-bench—that aspires to do exactly that. It gives agents complex analytical environments to work in and ambiguous tasks to solve, and measures how well they perform.
In this talk, well share how we built the benchmark, the results of our tests, a bunch of things we learned along the way, and what we think is coming next.
The benchmark harness is open source, and can be found here: https://github.com/dbt-labs/ade-bench
SPEAKERS:
Benn Stancil - Founder, Mode (acquired by ThoughtSpot)
Jason Ganz - Director, DX + AI, dbt Labs
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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.
FIND US:
Website: https://aicouncil.com/
LinkedIn: https://www.linkedin.com/company/aicouncilconf/
X: https://x.com/aicouncilconf Benchmarking AI Agents Against Realistic Analytical Tasks with ADE-bench](https://i.ytimg.com/vi/wLZLmGcGQZs/mqdefault.jpg)
![Revolutionize AI Engineering with AutoGen
[2025 - Day 1 - AI Engineering] Marck Vaisman shares insights from Microsofts AutoGen, an open-source framework for building AI agent systems that transforms complex AI workflows into seamless processes. This talk offers valuable perspectives on accelerating project timelines, boosting model accuracy, and cutting costs through powerful automation, essential for teams looking to revolutionize their AI projects and take intelligent solutions to the next level.
ABOUT THE SPEAKER:
Marck Vaisman, Global AI Solutions Architect, Microsoft -
🎟️ 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
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X: https://x.com/AICouncilConf
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Website: https://aicouncil.com/ Revolutionize AI Engineering with AutoGen](https://i.ytimg.com/vi/xMjVBaxPHco/mqdefault.jpg)
![Causal Inference Methods for Bridging Experiments and Strategic Impact
[2025 - Day 1 - Data Science & Algos] Wenjing Zheng shares insights from connecting A/B test results to real-world business decisions at Roblox, exploring causal inference methods that bridge the gap between clean experimental measures and messy strategic choices. Whether youre attributing business growth to product launches or generalizing experiment results to broader populations, this talk offers valuable perspectives on building a common measurement language that connects local experimental results to global business impact.
ABOUT THE SPEAKER:
Wenjing Zheng, Data Science Manager, Roblox -
🎟️ 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/ Causal Inference Methods for Bridging Experiments and Strategic Impact](https://i.ytimg.com/vi/xlgY5f3OHmA/mqdefault.jpg)
![The Modern Data Stack Lost the War: Stop Building more DataFrame APIs | OpenAI
[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 doesnt matter anymore: Agents and AI-first developers couldnt 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.
FIND US:
Website: https://aicouncil.com/
LinkedIn: https://www.linkedin.com/company/aicouncilconf/
X: https://x.com/aicouncilconf The Modern Data Stack Lost the War: Stop Building more DataFrame APIs | OpenAI](https://i.ytimg.com/vi/xp1wC3nx94Q/mqdefault.jpg)
![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
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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
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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.
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)