Uploaded May 2025 | Updated September 2026, 3 weeks ago
[2025 - Day 1 - AI Engineering] Dhruv Singh shares insights from building multi-turn AI systems, exploring how errors compound and cascade in agents and RAG chatbots through real-world failure examples. For developers building interactive AI systems, this talk offers valuable perspectives on using "eval agents" tuned on real-world interactions to evaluate and improve agent performance, introducing the new world of trajectory evaluation needed for accurate agent assessment.
ABOUT THE SPEAKER:
Dhruv Singh, Co-Founder & CTO, HoneyHive AI -
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[2025 - Day 1 - AI Engineering] Dhruv Singh shares insights from building multi-turn AI systems, exploring how errors compound and cascade in agents and RAG chatbots through real-world failure examples. For developers building interactive AI systems, this talk offers valuable perspectives on using "eval agents" tuned on real-world interactions to evaluate and improve agent performance, introducing the new world of trajectory evaluation needed for accurate agent assessment.
ABOUT THE SPEAKER:
Dhruv Singh, Co-Founder & CTO, HoneyHive AI -
๐๏ธ GET YOUR TICKET TO AI COUNCIL 2026 ๐๏ธ
Meet the world's top AI infrastructure minds where architects of AI share what works. Three days of high-quality technical talks and meaningful interactions.
โ aicouncil.com/sf-2026
โก FIND US:
X: https://x.com/AICouncilConf
LinkedIn: linkedin.com/company/aicouncilconf
Website: aicouncil.com
![5 Lessons from the Classroom for Evaluating Agents | Dev Interrupted
[2026 - DAY 2 - ANALYTICS & DATA SCI] Education researchers have spent a century figuring out how to build environments where complex, unpredictable systems self-correct through structured feedback. Software engineers building AI agents are solving the exact same problem from scratch and ignoring all of it. This talk bridges that gap. Im a former classroom teacher turned AI engineer, and Ill walk you through five pedagogical frameworks that map directly to eval design patterns for AI agents: backward design (define success criteria before you build), formative assessment (eval continuously, not just at the end), rubric design (multi-dimensional scoring instead of pass/fail), error analysis (categorize failure modes because same symptom doesnt mean same cause), and differentiated feedback (the agent, the user, and the knowledge base each need their own signal channel). What ties them together is back pressure: each framework is a way to capture signal from problems and route it to where it drives change. Thats what makes a system self-correcting instead of just self-reporting. Most AI observability is still about watching systems after the fact. This talk is about designing systems where the eval layer captures back pressure from failures and feeds it back upstream, so the system iterates on itself. Ive built production agents and won hackathons with this approach, and the core insight is simple: the best eval systems arent tests, theyre environments. And nobody knows more about designing those environments than teachers.
SPEAKER:
Andrew Zigler - GTM Engineer, LinearB & Podcast Host, Dev Interrupted
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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 5 Lessons from the Classroom for Evaluating Agents | Dev Interrupted](https://i.ytimg.com/vi/mkuwepBWKsU/mqdefault.jpg)

![From Scaling to Observability Solving Key Challenges for Distributed ML with Ray
[2025 - Day 2 - MLOps & Platforms] Nikita Vemuri shares insights from scaling distributed ML training across thousands of nodes with Ray, exploring the observability challenges of tracking vast amounts of system data in multi-node environments. Whether youre running large-scale ML workloads or building monitoring systems for distributed training, this talk offers valuable perspectives on correlating information across clusters and designing observability stacks that surface relevant insights while maintaining data privacy.
ABOUT THE SPEAKER:
Nikita Vemuri, Software Engineer, Anyscale -
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Website: https://aicouncil.com/ From Scaling to Observability Solving Key Challenges for Distributed ML with Ray](https://i.ytimg.com/vi/nfrmfyoKs6A/mqdefault.jpg)

![AI: too good to be true, too bad to be useful | TypeSafe AI
[2026 - DAY 1 - INFERENCE SYSTEMS] Why are some AI applications too good to be true and others total bunk? What is the reason behind the massive gap between over-promise and under-deliver? Lets talk about LLM history, mystery, and optimization to figure out where the f**k is all the automation.
SPEAKER:
Diogo Almeida - Co-founder and CEO, TypeSafe AI & Co-inventor of ChatGPT
๐ 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 AI: too good to be true, too bad to be useful | TypeSafe AI](https://i.ytimg.com/vi/o-y1HJ6buGQ/mqdefault.jpg)
![DuckDB Co-Creator Hannes Mรผhleisen on Why Single-Node Beats Distributed
[2025 - Day 1 - Data Eng & Infra] Hannes Mรผhleisen shares insights from co-creating DuckDB, exploring how this in-process analytical engines small footprint and high per-core efficiency unlocks creative data interaction possibilities. For engineers building data pipelines or deploying analytics anywhere from servers to small devices, this talk offers valuable guidance on leveraging DuckDBs vectorized processing and larger-than-memory capabilities for previously impossible use cases.
ABOUT THE SPEAKER:
Hannes Mรผhleisen, Co-Creator, DuckDB
๐๏ธ GET YOUR TICKET TO AI COUNCIL 2026 ๐๏ธ
Meet the worlds top AI infrastructure minds where architects of AI share what works. Three days of high-quality technical talks and meaningful interactions.
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Website: https://aicouncil.com/ DuckDB Co-Creator Hannes Mรผhleisen on Why Single-Node Beats Distributed](https://i.ytimg.com/vi/o53onmgnQDU/mqdefault.jpg)
![Why dbt Acquired SDF Building true SQL Comprehension
[2025 - Day 1 - Data Eng & Infra] Elias DeFaria shares insights from building SDFs multi-dialect SQL compiler that resolves proprietary SQL dialects into unified logical plans, exploring the breakthrough technology now powering dbt following the acquisition. This talk offers valuable perspectives on normalizing complex dialects and unlocking developer experience improvements in data governance and cost optimization, especially relevant for teams working with cross-engine workflows or building analytics infrastructure.
ABOUT THE SPEAKER:
Elias DeFaria, Staff Product Manager, dbt | Former Co-Founder & VP Product, SDF -
๐๏ธ GET YOUR TICKET TO AI COUNCIL 2026 ๐๏ธ
Meet the worlds top AI infrastructure minds where architects of AI share what works. Three days of high-quality technical talks and meaningful interactions.
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X: https://x.com/AICouncilConf
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Website: https://aicouncil.com/ Why dbt Acquired SDF Building true SQL Comprehension](https://i.ytimg.com/vi/oE8I2VQsKn4/mqdefault.jpg)
![AGI is Already Here (But Its Not What You Think)
[2025 - Day 3 - GenAI Applications] Joseph Gonzalez and Chenggang Wu share insights from redefining AGI through compound AI systems that compose LLMs with data and tools, exploring how orchestrating multiple models creates intelligence that rivals human capabilities. Whether youre building AI-powered workflows or developing general-purpose agents, this talk offers valuable perspectives on creating systems that outperform humans in both accuracy and efficiency while being notably faster.
ABOUT THE SPEAKERS:
Joseph Gonzalez, Professor, Head of AI, UC Berkeley / RunLLM
Chenggang Wu, Co-Founder & CTO, RunLLM -
๐๏ธ GET YOUR TICKET TO AI COUNCIL 2026 ๐๏ธ
Meet the worlds top AI infrastructure minds where architects of AI share what works. Three days of high-quality technical talks and meaningful interactions.
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X: https://x.com/AICouncilConf
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Website: https://aicouncil.com/ AGI is Already Here (But Its Not What You Think)](https://i.ytimg.com/vi/oSKV_c2ddWA/mqdefault.jpg)
![AI Launchpad 2025: NAO
[2025 - Day 1 - AI Launchpad] Claire Gouze and Christophe Blefari share insights from Nao, an AI code editor specifically designed for data teams, exploring how to streamline fragmented analytics engineering workflows across multiple tools. This session offers valuable perspectives on creating unified environments tailored to data professionals unique modeling needs, addressing productivity challenges from constant context switching between IDEs, CLIs, data warehouse UIs, documentation sites, and BI platforms.
ABOUT THE SPEAKERS:
Claire Gouze, Co-Founder & CEO, NAO
Christophe Blefari, Co-Founder, NAO -
๐๏ธ GET YOUR TICKET TO AI COUNCIL 2026 ๐๏ธ
Meet the worlds top AI infrastructure minds where architects of AI share what works. Three days of high-quality technical talks and meaningful interactions.
โ https://aicouncil.com/sf-2026
โก FIND US:
X: https://x.com/AICouncilConf
LinkedIn: https://www.linkedin.com/company/aicouncilconf/
Website: https://aicouncil.com/ AI Launchpad 2025: NAO](https://i.ytimg.com/vi/oyJziKnpElo/mqdefault.jpg)

![Building a Data Native Agent: Cortex Code | Snowflake
[2026 - DAY 2 - WORKSHOP] We built Cortex Code to solve the context gap in AI development by engineering the industrys first data-native coding agent that is deeply coupled with the underlying data platform. We architected a system that directly interfaces with Snowflakes metadata, compute, and governance layers, giving the agent real-time environment awareness of table structures, operational semantics, and security.
In this session, we will dive into how we constructed this context-aware reasoning loop, utilized open standards like MCP and agents skills for extensibility, and solved the challenge of delivering an agent that accelerates complex data engineering and ML workflows while remaining secure-by-design. We will also share our experiences with benchmarking and optimizing Cortex Code on public and internal benchmarks.
SPEAKER:
Umesh Unnikrishnan - AI Research Lead, Snowflake
๐ 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 Building a Data Native Agent: Cortex Code | Snowflake](https://i.ytimg.com/vi/pV3hybzf31A/mqdefault.jpg)