Ducktober is here - 8 launches in 8 daysSee what's live
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.
9:09
51:02
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
44:21
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
43:57
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
51:58
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
49:02
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
37:22
Sep 16, 2026 • Mehdi Ouazza
One CLI to query MotherDuck, publish Python pipelines, and host dashboards from the terminal. See when it beats the MCP server, and when it doesn't.
Stream
MotherDuck Features
AI, ML and LLMs
Data Pipelines
60:29
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
63:17
Aug 18, 2026 • Jacob Matson
Agentic data engineering in practice: AI agents build dlt ingestion into MotherDuck and a governed Lightdash semantic layer, live in an hour.
Stream
AI, ML and LLMs
Data Pipelines
Ecosystem
52:41
Aug 13, 2026 • Garrett O'Brien
Guides store business context inside your warehouse so AI agents write correct SQL. See how warehouse-native context works in MotherDuck.
Stream
AI, ML and LLMs
MotherDuck Features
52:23
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
1:00:37
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
41:41
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
41:19
Jul 14, 2026 • Jacob Matson, Paul Dudley
Learn when Postgres CDC is worth it, what breaks it (WAL logs, replication slots, schema changes), and see a live Postgres-to-MotherDuck pipeline.
Webinar
Data Pipelines
Ecosystem
AI, ML and LLMs
46:45
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
36:45
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
54:22
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
45:32
Jun 17, 2026 • Doo Shim, Garrett O'Brien
See how MotherDuck Flights lets you build and schedule Python data pipelines with an AI agent — from a single prompt to a running ingest pipeline and live dashboard.
Webinar
Data Pipelines
AI, ML and LLMs
MotherDuck Features
Python
28:00
Jun 2, 2026 • Jordan Tigani
MotherDuck CEO Jordan Tigani on how AI is reshaping the modern data stack, why query latency now matters for agents, and the rise of open data formats.
Interview
AI, ML and LLMs
MotherDuck Features
Ecosystem
1:00:00
May 28, 2026 • Jacob Matson, Daniel Pham
See how e-commerce data teams use LLMs and MotherDuck to go from a plain-language business question to a published, interactive analysis in minutes.
Webinar
AI, ML and LLMs
BI & Visualization
47:05
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
42:00
May 19, 2026 • Jacob Matson, Hugo Lu
Watch an AI agent build a full data pipeline from scratch: ingestion with DLT, orchestration in Orchestra, staging and snapshots in MotherDuck, and a Dive for visual output.
Webinar
AI, ML and LLMs
Data Pipelines
MotherDuck Features
53:19
May 12, 2026 • Mehdi Ouazza, Josh Nakka
PriceMedic replaced Athena and Redshift with MotherDuck. Co-founder Josh Nakka on the 14x speedup, $20K/month savings, and Dives for customers.
Webinar
MotherDuck Features
AI, ML and LLMs
1:02:00
May 7, 2026 • Ryan Boyd, Logan Toskey, Alex Monahan
Watch how an AE and a marketer use AI to analyze their own business data without writing SQL or waiting on a data team.
Webinar
AI, ML and LLMs
MotherDuck Features
Tutorial
46:11
Apr 23, 2026 • Jacob Matson, Peter Chapman
Learn to write effective context for data agents. Covers benchmarks comparing English, SQL, and semantic model formats plus scaling strategies.
Webinar
AI, ML and LLMs
38:23
Mar 17, 2026 • Jerel Navarrete, Jacob Matson
See how MotherDuck's new query_rw MCP tool lets AI agents write back to your data warehouse, creating tables, storing embeddings, and saving views.
Stream
AI, ML and LLMs
MotherDuck Features
SQL
1:00:01
Mar 12, 2026 • Jacob Matson, Ryan Dolley
Jacob Matson covers text-to-SQL accuracy, why data models matter more than LLM choice, the MotherDuck MCP workflow, and Dives on Super Data Brothers.
Interview
AI, ML and LLMs
SQL
MotherDuck Features
1:00:14
Mar 11, 2026 • Ryan Boyd, Jerel Navarrete, Jacob Matson
Learn how to build a conversational AI chatbot for your SaaS product using the MotherDuck MCP server, with scoped data access and streaming responses.
Webinar
AI, ML and LLMs
Tutorial
MotherDuck Features
Jan 27, 2026 • Jerel Navarrete, Jacob Matson
Jacob and Jerel from MotherDuck showcase practical ways to optimize your data warehouse for AI-powered SQL generation. Through rigorous testing with the Bird benchmark, they demonstrate that text-to-SQL accuracy can jump from 30% to 74% by enriching your database with the right metadata.
AI, ML and LLMs
SQL
MotherDuck Features
Stream
Tutorial
0:09:18
Jan 21, 2026 • Mehdi Ouazza
Learn how to use the MotherDuck MCP server with Claude to analyze data using natural language—no SQL required. This text-to-SQL tutorial shows how AI data analysis works with the Model Context Protocol (MCP), letting you query databases, Parquet files on S3, and even public APIs just by asking questions in plain English.
YouTube
Tutorial
AI, ML and LLMs
Jan 21, 2026 • Jacob Matson, Alex Monahan
Jacob and Alex from MotherDuck query data using the MotherDuck MCP. Watch as they analyze 180,000 rows of shipment data through conversational AI, uncovering late delivery patterns, profitability insights, and operational trends with no SQL required!
Stream
AI, ML and LLMs
MotherDuck Features
SQL
BI & Visualization
Tutorial
59:39
Jan 16, 2026 • Ryan Boyd
MotherDuck cofounder Ryan Boyd demonstrates how to close the LLM accuracy gap for business analytics using MotherDuck's MCP server, semantic modeling, and hyper-tenancy architecture for AI agents.
AI, ML and LLMs
Jan 13, 2026 • Jacob Matson, Logan Toskey
Watch us dive into NFL playoff odds and PGA Tour stats using using MotherDuck's MCP server with Claude. See how to analyze data, build visualizations, and iterate on insights in real-time using natural language queries and DuckDB.
AI, ML and LLMs
SQL
MotherDuck Features
Tutorial
BI & Visualization
Ecosystem
Nov 20, 2025 • Jacob Matson
Learn how to turbocharge your Python data work using DuckDB and MotherDuck with Pandas. We walk through performance comparisons, exploratory data analysis on bigger datasets, and an end-to-end ML feature engineering pipeline.
Webinar
Python
AI, ML and LLMs
Nov 19, 2025 • Ryan Boyd
LLMs excel at natural language understanding but struggle with factual accuracy when aggregating business data. Ryan Boyd explores the architectural patterns needed to make LLMs work effectively alongside analytics databases.
AI, ML and LLMs
MotherDuck Features
SQL
Talk
Python
BI & Visualization
Nov 14, 2025 • Jacob Matson, Armin Efendic
AI isn't here to replace data work, it's here to make it better. Watch this webinar to see how Hex and MotherDuck build AI workflows that prioritize context, iteration, and real-world impact.
Webinar
AI, ML and LLMs