EXPLAIN ANALYZE

About EXPLAIN ANALYZE

AI and data news, digested by veterans from the field. Less hype. More signal. Get all show notes here (http://motherduck.com/explain-analyze). Podcast by MotherDuck (https://motherduck.com/)

Publisher

MotherDuck

Category

news · technology

Language

en

Explicit

No

First episode

22 May 2026

Latest episode

9 Sept 2026

Latest episodes

10 episodes in the feed.

1. 

   9 Sept 2026

   AWS Bought DuckLabs and users want their own agents

   AWS bought DuckLabs—the company employing the core team behind DuckDB while DuckDB remains open source. What does the deal mean for AWS, MotherDuck, and the data stack building around DuckDB? In this episode, @mehdio and @dumkydewilde unpack the acquisition, then connect Iceberg and Lance, SQL-first context for agents, Spotify's LLM evaluation funnel, AI-generated data lineage, CodexBar, WalGit, query optimizers, and the fight over whether SaaS products should ship their own agents or let users bring one. All links on https://motherduck.com/podcast (https://motherduck.com/podcast) 00:00 Welcome to EXPLAIN ANALYZE 01:15 Why AWS bought DuckLabs 11:14 Analyze with Iceberg, serve with Lance 16:30 Why your agent should manage context through SQL 22:09 Better experiments with LLM evals 27:26 CodexBar makes AI usage visible 33:06 Architectural lessons for AI-powered data warehouses 38:10 WalGit: one Git server binary, backed by object storage 42:55 Query optimizers: the low-key MVP 47:13 Do users want your agent, or their own? 58:36 Wrap-up #DuckDB #AWS #DuckLabs #DataEngineering #AIAgents #Iceberg #Lance #LLMEvals #MCP #DataPodcast

2. 

   24 Aug 2026

   AGENTS.md vs Skills: MLOps, Evals & Agent Governance with Maria Vechtomova

   Agent code can look productive right up until a dependency changes, an eval misses the real failure mode, or an over-permissioned tool turns a routine task into a security incident. So what does it actually take to operate AI systems responsibly? In this episode, Mehdi, Dumky de Wilde, and Maria Vechtomova connect MLOps and LLMOps to agent evals, MCP governance, regenerated software, security, and the engineering practices that still matter when outputs are non-deterministic. All links and note : https://motherduck.com/podcast (https://motherduck.com/podcast) Chapters: 00:00 Meet Maria Vechtomova 01:01 From MLOps to forward-deployed engineering 01:59 Principles first, Databricks second 06:18 What changes from MLOps to LLMOps 09:10 Deterministic tools for non-deterministic systems 09:50 Who maintains regenerated software? 12:38 Hiring for critical thinking with AI 17:38 MCP skills, files, extensions, and stateless servers 20:43 The missing governance layer for agent tools 24:15 Turning deployment pain into reusable practices 28:44 Testing and evaluating LLM systems 31:59 Why AGENTS.md (http://AGENTS.md) beat skills in Vercel’s evals 40:13 When an agent accidentally hacks Hugging Face 45:00 Skills and the software supply chain 47:53 Consulting that leaves teams stronger 50:42 Wrap-up

3. 

   7 Aug 2026

   AI codes with outdated libraries. Why is this unsolved?

   @mehdio  (https://studio.youtube.com/channel/UCiZxJB0xWfPBE2omVZeWPpQ) and Dumky work through a round of data and AI news, starting with Analytics Tycoon, a browser game where you run a data team on a fixed budget and lose trust points every time a cron job breaks. Then the uncomfortable stuff: Python 3.15 is at release candidate while 3.10 is still the number two download and goes end of life in two months, your agent keeps writing 3.11 because it does not know what day it is, Stripe is reportedly circling OpenRouter for 10 billion dollars, and data modeling turns out to be very much alive once you try to replace it with a context layer. Subscribe + all links: motherduck.com/podcast (http://motherduck.com/podcast) Hosts: Mehdi Ouazza (@mehd-io) and Dumky de Wilde (@dumkydewilde) CHAPTERS 00:00 Cold open 00:33 Analytics Tycoon: the data team as a strategy game 06:46 Python 3.15 is coming and 3.10 is about to die 14:07 If nobody blogs about it, will your model know? 15:20 Agent Craft and Agents View: maps for your agents 19:18 Stripe in talks to acquire OpenRouter 23:20 Google's next chapter and the shrinking AI moat 30:19 Is data modeling dead? Daniel Beach weighs in 35:10 Hard to eval is a product smell 39:57 Cloudflare OS and the return of internal tools 43:02 Supabase publishes public evals for AI agents 44:21 Superlogical: Hashimoto builds a multiplexer 48:47 That is a wrap #ExplainAnalyze #MotherDuck #DataEngineering #DuckDB #Python #AIAgents #LLMEvals #DataModeling #OpenRouter #CloudflareOS #Tmux #DataPodcast

4. 

   28 Jul 2026

   The Safest Bet in AI Is Hardware !

   Is the safest bet in AI the hardware underneath it? Show notes: https://motherduck.com/explain-analyze (https://motherduck.com/explain-analyze) Mehdi Ouazza and Jacob Matson unpack Meta's reported $10B compute lease talks with Anthropic, why AI labs are becoming infrastructure customers, and what it means for data and AI builders. Then they get into graph-shaped context for agents, removing AI slop from writing, reproducible development environments, AMD's Anthropic bet, Domo's acquisition and the future of standalone BI, lakehouse vs. warehouse, leadership bottlenecks, tldraw's isRecord saga, and loop engineering. EXPLAIN ANALYZE is the MotherDuck podcast where the hosts bring data and AI stories the others have not seen, then work through them together. 00:00 (https://www.youtube.com/watch?v=XG7po7pT-iw) Welcome to EXPLAIN ANALYZE 01:02 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=62s) Meta's potential $10B compute lease with Anthropic 04:13 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=253s) Graph context for agents 10:23 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=623s) Removing AI slop from writing 18:33 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=1113s) Why “it worked on my machine” still happens 25:45 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=1545s) AMD commits up to $5B to Anthropic 27:26 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=1646s) Domo acquired: the end of standalone BI? 31:29 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=1889s) Where data engineering is heading 33:15 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=1995s) Lakehouse vs. warehouse 37:30 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=2250s) Leadership becomes the bottleneck 41:10 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=2470s) tldraw and the isRecord saga 46:07 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=2767s) Loop engineering: goals, stop criteria, and timers 50:03 (https://www.youtube.com/watch?v=XG7po7pT-iw&t=3003s) Thanks for watching

5. 

   1 Jul 2026

   AI is relearning everything databases already knew ft. Stephanie Wang

   AI is moving inside the database, and it keeps hitting problems databases already solved. Stephanie Wang (staff engineer at MongoDB, founding engineer at MotherDuck) joins Mehdi and Jacob Matson to dig into Snowflake's Cortex AISQL and why AI inside SQL is really a query-optimization and cost problem, the compute crunch pushing RAM and inference prices up, RadAgents and Sakana's Fugu model router, open weights vs open development, and the "elephant and goldfish" method for designing before you let AI write the code. All links and full show notes: motherduck.com/explain-analyze (http://motherduck.com/explain-analyze) 00:00 Intro and guest intro (Stephanie Wang) 01:35 Cortex AISQL: AI operations native to SQL 10:14 SpaceX rents out idle compute for AI inference 12:11 Compute is the new database engine for AI 13:43 DRAM price hikes and the margin squeeze 18:40 Local AI models and sandboxing agents 22:39 RadAgents: multi-agent reasoning for radiology 27:34 Sakana Fugu and dynamic model routing 30:12 Open weights vs open development 33:43 The elephant and goldfish: design before you code 42:07 MPP: machine-to-machine payments for agents 46:56 Wrap-up

6. 

   19 Jun 2026

   AI is turning all data viz into JavaScript ft. Yan Holtz

   Yan Holtz, the data viz educator behind data-to-viz.com (http://data-to-viz.com) and the R/Python/D3 graph galleries, joins Mehdi and Alex for a full episode on data visualization in the age of AI. AI has basically solved the "how do I write the code" problem, which makes the "what makes a good chart" problem matter more than ever - and it's quietly pushing all serious data viz toward JavaScript and D3, even for R and Python people. We get into picking the right chart before writing a line of code, whether dashboards are dying in favor of agents, why D3.js went from the hardest tool to the default, an agent that grades its own charts against the Tufte test, why Shiny and Streamlit may no longer be the right call, the token cost of data work, and whether a chat box is even the right tool to design a visualization. Subscribe + all links: motherduck.com/explain-analyze (http://motherduck.com/explain-analyze) Yan's website : https://www.data-to-viz.com/ (https://www.data-to-viz.com/) Yan's social : https://www.linkedin.com/in/yan-holtz-2477534a/ (https://www.linkedin.com/in/yan-holtz-2477534a/) Chapters 00:00 Welcome + guest intro (Yan Holtz) 01:29 data-to-viz.com (http://data-to-viz.com): choosing the right chart 07:58 BI is dead, long live BI: dashboards vs agents 17:09 ninejs: interactive ggplot2 charts in Python 20:01 Teaching an AI agent to make beautiful charts 29:20 D3.js: infinite flexibility, now AI-writable 36:24 Shiny: the right tool in the age of AI? 42:02 Token economics: data is token-hungry 46:33 Data visualization in the age of AI 49:37 Outro #DataViz (#DataViz) #DataVisualization (#DataVisualization) #D3js (#D3js) #JavaScript (#JavaScript) #BI (#BI) #DuckDB (#DuckDB) #AI (#AI) #MotherDuck (#MotherDuck) #ExplainAnalyze (#ExplainAnalyze)

7. 

   13 Jun 2026

   Data infra is printing money. Is it sustainable?

   Infrastructure keeps winning the funding while SaaS bleeds — but is it sustainable when AI agents spin up databases that die in days? Mehdi and Jacob Matson dig into Supabase's Series F, local AI on personal chips, DuckDB turning up everywhere (MariaDB, MondayDB HTAP), Anthropic's "data is not software" claim, and a wave of people building software just for themselves. Show notes & links : https://motherduck.com/explain-analyze (https://motherduck.com/explain-analyze) ➡️ Follow Us LinkedIn: https://linkedin.com/company/motherduck (https://linkedin.com/company/motherduck) X/Twitter : https://twitter.com/motherduck (https://twitter.com/motherduck) Blog: https://motherduck.com/blog/ (https://motherduck.com/blog/) 00:00 — Intro: who's on today 00:48 — Supabase's Series F: SaaS vs infrastructure 05:14 — Local AI: NVIDIA's chips for personal computers 09:28 — MondayDB 3: HTAP for a trillion-table system 14:10 — A DuckDB storage engine for MariaDB 18:14 — Anthropic: "data is not software" 24:12 — Delba on feedback loops and less agent babysitting 29:20 — Tristan Handy: I built a (very small) agent swarm 32:54 — Home-cooked apps: software just for you 38:01 — DoomBench: can your database run Doom? 40:41 — A C documentary: languages in the AI era 44:28 — Wrap-up

8. 

   5 Jun 2026

   DuckDB breaks the lakehouse ? ft. Daniel Beach

   Daniel Beach (Data Engineering Central) joins Mehdi and Dumky for a tour through the open lakehouse renaissance, AI-native data agents, and the slow grind of getting humans out of the orchestration loop. We cover the catalog commits feature in Delta + Unity Catalog + DuckDB (multi-writer lakehouse without Spark), Cloudflare's new unified data platform and their AI agent Skipper, ADBC quietly replacing JDBC/ODBC, Aaron Francis launching SoloTerm, Addy Osmani on the orchestration tax, Mitchell Hashimoto getting a 40x speedup with an agent in a loop. Subscribe + all links: motherduck.com/explain-analyze (http://motherduck.com/explain-analyze) 👋 Hosts Mehdi Ouazza —  @mehdio  (https://studio.youtube.com/channel/UCiZxJB0xWfPBE2omVZeWPpQ) Dumky de Wilde Guest: Daniel Beach (Data Engineering Central) —  @dataengineeringdan  (https://studio.youtube.com/channel/UCtgwwr7rPOqdBv2U4t_gBkg) Check out Daniel Beach's work on https://dataengineeringcentral.substack.com/ (https://dataengineeringcentral.substack.com/) ➡️ Follow Us LinkedIn: https://linkedin.com/company/motherduck (https://linkedin.com/company/motherduck) X/Twitter : https://twitter.com/motherduck (https://twitter.com/motherduck) Blog: https://motherduck.com/blog/ (https://motherduck.com/blog/) 00:00 Cold open · who's on today 01:43 Catalog commits · Delta + Unity Catalog + DuckDB 10:46 Cloudflare unified data platform · Skipper agent 17:53 Education in the age of AI · language as interface 24:39 ADBC · the next-gen database connection 30:17 SoloTerm · the terminal in the browser 38:56 The orchestration tax · Addy Osmani 40:38 Mitchell Hashimoto · an agent in a loop 45:50 Databricks Zerobus · streaming into the lakehouse 47:06 Outro #DuckDB #DataEngineering #Lakehouse #DeltaLake #UnityCatalog #Cloudflare #AIagents #ApacheArrow #ADBC #MotherDuck

9. 

   29 May 2026

   161k GitHub stars in 4 months with 65 lines of Markdown

   Mehdi (DevRel) and Dumky (Developer Experience) at MotherDuck run through ~10 links from the world of data and AI. This one keeps circling back to a single theme: as AI makes everything easier to produce, the hard part becomes telling the real signal from the slop, whether that's music, GitHub stars, or your data warehouse answers. All links: motherduck.com/explain-analyze (http://motherduck.com/explain-analyze) : subscribe there to get every new episode by email with full notes! 0:00 — Intro 0:43 — AI slop on Spotify? 6:00 — A skill file with 161k GitHub stars 11:30 — Up and Down the Ladder of Abstraction 17:00 — GitHub Actions are the new email scam 24:00 — The chat box is dying 30:00 — Slow tech: Kindle, TRMNL, Fitbit 37:00 — From Vibes to Evals 43:00 — The AI paradox (via Lenny's Podcast) 51:40 — Wrap up

10. 

    22 May 2026

    Bun Drops Zig, Claude Raises Prices & Is Vibe Coding Killing Open Source?

    First episode. Bun ditches Zig for Rust, Anthropic pulls the rug on pricing, agents are rewriting how databases work, and open source maintainers are drowning. Mehdi and Alex pick apart the AI tooling wars and why your brain feels fried. Show notes : https://motherduck.com/explain-analyze/ (https://motherduck.com/explain-analyze/) 00:00 Introduction to the Podcast and Bun's Rewrite 03:10 The Shift from Zig to Rust in Bun 05:52 AI's Impact on Programming Languages 08:11 Database Optimization for AI Agents 10:44 The Role of Time Travel and Transactions in AI 13:40 Claude's Goal-Oriented Approach to AI 16:22 The Importance of Agency in Software Development 19:19 The Future of BI Tools and Customization 22:01 Codex Plugin for Cloud Code 25:10 The Convergence of AI Models 26:45 Navigating Vendor Lock-in 28:39 The Future of Pricing Models 29:53 HTML vs Markdown in Development 35:46 The Impact of AI on Open Source Contributions 41:13 The Future of Open Source in an AI World 49:47 Mental Health and AI Usage

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