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Videos and Online Events

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

51:58

2026-10-01

Build a Data Agent in 60 Minutes

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

2026-09-29

prompt_jev(): SQL-Native Text Classification

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

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

54:22

2026-06-18

DuckDB's agent moment (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

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

60:41

2026-04-09

Zero-Latency Analytics in Your Application with Dives

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

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

55:29

2026-04-02

All About DuckLake: The O'Reilly Book

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

"Shareable visualizations built by your favorite agent" video thumbnail

1:00:10

2026-02-25

Shareable visualizations built by your favorite agent

You know the pattern: someone asks a question, you write a query, share the results — and a week later, the same question comes back. Watch this webinar to see how MotherDuck is rethinking how questions become answers, with AI agents that build and share interactive data visualizations straight from live queries.

Webinar

AI ML and LLMs

MotherDuck Features