Skip to main content

Videos and Online Events

Feb 13
YouTube, MCP, AI, ML and LLMs

MCP: Understand It, Set It Up, Use It

Learn what MCP (Model Context Protocol) is, how its three building blocks work, and how to set up remote and local MCP servers. Includes a real demo chaining MotherDuck and Notion MCP servers in a single prompt.

"MCP: Understand It, Set It Up, Use It" video thumbnail

9:09

"DuckLake Performance Optimization: Faster Queries From Your Lakehouse" video thumbnail

64:46

DuckLake Performance Optimization

Oct 27, 2026 • Alex Monahan, Matt Martin

Alex Monahan and Matt Martin, co-authors of O'Reilly's DuckLake: The Definitive Guide, walk through how to make DuckLake queries faster: finding the bottleneck, partitioning and sorting so queries skip files and row groups, tuning Parquet settings together, and keeping the catalog lean.

Stream

SQL

MotherDuck Features

"Behind the Agent: How Hazel Built an AI Coworker for Consumer Brands" video thumbnail

51:02

How Hazel Built an AI Coworker

Oct 21, 2026 • Alex Monahan

Patrik Devlin, co-founder and CTO of Hazel, joins host Alex Monahan to show Hazel in a demo account and walk through the stack behind it: Fivetran and dlt into S3, dbt in MotherDuck, and a separate database for every customer.

Stream

MotherDuck Features

AI, ML and LLMs

Data Pipelines

"Aligned on Numbers: How Our Chief of Staff Builds Internal Data Apps with Agents at MotherDuck" video thumbnail

44:21

Aligned on Numbers: A Chief of Staff's Data Apps

Oct 15, 2026 • Kaitlyn Henry

Zoey Weaver interviews Kaitlyn Henry, MotherDuck's Chief of Staff, as she walks through two internal data apps: an AI token spend tracker built on a Flight and a weekly business review Dive. She explains how Guides, markdown files that define the company's key metrics, keep everyone's numbers consistent.

Stream

MotherDuck Features

AI, ML and LLMs

"Jev for Analytics: 5 Use Cases on Real Data" video thumbnail

43:57

Jev for Analytics: 5 Use Cases

Oct 8, 2026 • Mehdi Ouazza

Mehdi Ouazza uses MotherDuck's prompt_jev() to turn text columns into columns you can GROUP BY. He classifies 100,000 consumer complaints, then walks through five use cases on real data: AI agent logs, Hacker News sentiment, sales calls, and two kinds of job-ad analysis.

Stream

MotherDuck Features

AI, ML and LLMs

"Virtual Workshop: Build a Data Agent in 60 Minutes" video thumbnail

51:58

Build a Data Agent in 60 Minutes

Oct 1, 2026 • Jacob Matson

Jacob Matson walks through a working data chat agent he built: MCP tools, an agentic loop, a tuned system prompt, hard-coded read-only guardrails, and telemetry. He demos it live against a real dataset, walks through the actual codebase, then shows the same backend re-platformed into a Slack bot.

Stream

MotherDuck Features

AI, ML and LLMs

Data Pipelines

"We Classified 100,000 Rows in 40 Seconds: Introducing prompt_jev()" video thumbnail

49:02

prompt_jev(): SQL-Native Text Classification

Sep 29, 2026 • Hamilton Ulmer, Dumky de Wilde, Jacob Matson

MotherDuck's new prompt_jev() function runs text classification directly from SQL using Jev, a decision-focused model from typesafe.ai. In a live demo, Jacob Matson, Dumky de Wilde, and Hamilton Ulmer showed it filtering, disambiguating, and re-ranking real data without leaving SQL. The number they kept coming back to: 100,000 rows classified at 89% accuracy in 40 seconds, compared to 32 minutes and $37.58 for a comparable LLM call.

Stream

MotherDuck Features

AI, ML and LLMs

Data Pipelines

"Do AI Agents Need a Semantic Layer?" video thumbnail

60:29

Do AI Agents Need a Semantic Layer?

Aug 26, 2026 • Alex Monahan, Jacob Matson

Do AI agents need a semantic layer? Evals comparing plain-text context with a Malloy semantic layer show where each wins, and what it costs.

Stream

AI, ML and LLMs

BI & Visualization

SQL

"Trust the agents you build on your data" video thumbnail

52:23

Trust the agents you build on your data

Aug 12, 2026 • Jacob Matson

Learn how to evaluate AI agents that query your data: run text-to-SQL evals with Braintrust and MotherDuck, read traces, and fix failures with context.

Webinar

AI, ML and LLMs

SQL

Ecosystem

"BI Is Having a Midlife Crisis" video thumbnail

1:00:37

BI Is Having a Midlife Crisis

Jul 28, 2026 • Jacob Matson, Ryan Dolley

Jacob Matson and BI analyst Ryan Dolley on whether AI can replace your BI tool, what it actually solves, and what still needs governance.

Interview

BI & Visualization

AI, ML and LLMs

"Writing robust data pipelines with AI" video thumbnail

41:41

Writing robust data pipelines with AI

Jul 22, 2026 • Mehdi Ouazza

AI writes data pipelines in seconds, but green isn't correct. Build robust data pipelines with AI: eyes on data, foundations, tests, and contracts.

Webinar

Data Pipelines

AI, ML and LLMs

MotherDuck Features

"What Makes a Great Data Viz? DiveMaxxing Winners Revealed" video thumbnail

46:45

What Makes a Great Data Viz? DiveMaxxing Winners Revealed

Jun 24, 2026 • Hamilton Ulmer, Brittany Rosenau, Zack Mazzoncini, Jacob Matson

What makes a great data visualization in the AI era? Three viz experts judge the DiveMaxxing winners and break down what separates great from busy.

Webinar

BI & Visualization

AI, ML and LLMs

"From Source to Dashboard: Real Pipelines with Flights" video thumbnail

36:45

From Source to Dashboard: Real Pipelines with Flights

Jun 23, 2026 • Jacob Matson

Watch an AI agent build a data pipeline end to end in MotherDuck Flights: ingest, transform, and schedule it, then wire it into a live Dive dashboard.

Webinar

AI, ML and LLMs

Data Pipelines

MotherDuck Features

BI & Visualization

"DuckDB's agent moment (Jordan Tigani)" video thumbnail

54:22

DuckDB's agent moment (Jordan Tigani)

Jun 18, 2026 • Jordan Tigani

Jordan Tigani helped build BigQuery, then left to bet that most data isn't actually big. Three years later, the agent era is making his case for him. In this conversation on The Analytics Engineering Podcast, he and host Tristan Handy talk about how MotherDuck and DuckDB fit together, why a single-node database makes more sense than you'd think for agents, and what it would actually look like to have a swarm of agents managing your data.

YouTube

AI, ML and LLMs

Interview

"Data Engineering Is AI Engineering" video thumbnail

47:05

Data Engineering Is AI Engineering

May 26, 2026 • Jacob Matson

Jacob Matson refactors a real NBA app with AI agent teams, revealing how data engineering patterns like DAGs and wave planning map directly to agent orchestration.

Webinar

AI, ML and LLMs

Data Pipelines

"Zero-Latency Analytics in Your Application with Dives" video thumbnail

60:41

Zero-Latency Analytics in Your Application with Dives

Apr 9, 2026 • Alex Monahan, Garrett O'Brien

BI tools were never built to be app interfaces — they're rigid, clunky, and add complexity to your user experience. Dives offer a different approach: interactive data apps you create with natural language that can be embedded directly into your applications. In this session, Alex Monahan walks through how to build a Dive and embed it in your app, with help from AI agents. You'll learn how to create interactive visualizations with natural language queries, embed Dives into your app with a secure sandbox, set up the auth flow so your users get read-only access without exposing credentials, and choose between server-side and dual execution with DuckDB-Wasm. Whether you're building customer-facing analytics or internal tools, this webinar shows you the full workflow from query to production-ready embed. See how Claude Code + Dives can get you from zero to a working data app fast.

Webinar

MotherDuck Features

BI & Visualization

App Development

"What's New in DuckDB 1.5!" video thumbnail

58:00

What's New in DuckDB 1.5!

Apr 7, 2026 • Alex Monahan, Jacob Matson

Alex Monahan and Jacob Matson walk through DuckDB 1.5's biggest features including the VARIANT type, redesigned CLI, built-in GEOMETRY, and faster joins.

Webinar

"All About DuckLake: The O'Reilly Book" video thumbnail

55:29

All About DuckLake: The O'Reilly Book

Apr 2, 2026 • Alex Monahan, Matt Martin

Matt Martin and Alex Monahan, coauthors of O'Reilly's DuckLake: The Definitive Guide, discuss what DuckLake is, how it simplifies lakehouse architecture, and why it replaces file-based metadata with a SQL database. Includes a live Q&A and the release of Chapter 1.

Webinar

Ecosystem