Joe Cheng is the CTO of Posit and the creator of Shiny. He joins Michael and Hadley to talk about why he almost walked away from AI work entirely over ethics concerns and what it takes to lead a team that didn't necessarily choose you. Plus, why saying yes to everyone is a worse strategy than it sounds. Bonus: Hadley calls out Joe's people-pleasing in real time.

What's inside:

• Joe's 2012 self-doubt spiral that accidentally created Shiny
• Why Joe almost quit working on AI entirely
• The "loaded guns" problem with releasing AI tools
• Hadley's blunt leadership style vs. Joe's people-pleasing
• Nobody actually wanted to make Joe CTO?
• Joe's take on curiosity, duty, and fear as motivators

Caitlin Colgrove is the CTO of Hex, the data workspace for building and sharing data projects using SQL and Python that somehow counts a Sweetgreen chef as a power user. She joins Michael, Hadley, and Isabel to talk about what AI agents actually get wrong in data work (it's not the hallucinations, it's supreme overconfidence), why data teams aren't going anywhere, and how she thinks about building products for humans and agents at the same time.

What's inside

• What Hex's Context Studio does, and why it's a data team's new job
• More code is now written in Hex by agents than by humans
• "My job is to vouch for the correctness of the answer" — redefining the data team
• The vibe-coded CEO PR is coming for your data team (if it hasn’t already)
• Soulsborne games as couple's therapy, aka, the Elden Ring co-op report

Alex Hillman built one of America's first co-working spaces, wrote a business book in tweets, and recently handed his inbox to a Claude Code agent — not to draft emails, but to notice when a friendship is going cold. In this episode, Alex, Michael, Wes, and Hadley dig into marketing for people who hate marketing, what 20 years of email reveals about your relationships, and why the hardest part of AI-assisted coding was always before you wrote a single line.

What's inside: 

• Marketing is really just listening at scale
• Building a 20-year relationship database from your sent folder
• "Hot rod vs. plumbing" — the two kinds of software you build now
• What early internet and the AI boom have in common
• The case for reading 20-year-old engineering books with a coding agent
• Karaoke philosophy as a framework for community building

Mike Bostock made D3 when the browser was still a joke. He built bl.ocks when people needed somewhere to share their work. Now he's building Observable — reactive notebooks with an AI that actually looks at what it made. In this episode: the three-GIF bar chart that launched 25 years of viz, why open source needs both intrinsic and extrinsic motivation, and why an agent that can't see its own output is likely to be confidently wrong.

What's Inside

• The 1998 visualization library that could only make bar charts
• Why D3 hit #3 on GitHub, and what killed the gallery
• What spreadsheets got right that notebooks ignored for years
• "The agent can lie with text, but not with code"
• Why Observable scrapped canvases and went back to notebooks
• The penguin dataset that exposes AI
• Strength training, tennis mind games, and a resurrected Stanford game

Paige Bailey is a developer relations engineering lead at Google DeepMind. She's a geophysicist-turned-AI-engineer who was once told by her professors that building open-source libraries was a waste of time. We talk about her path from planetary science to TensorFlow, why statisticians have a hidden edge in the age of AI, and what it means to be a curious generalist when the cost of building software is approaching zero. Bonus: installing solar-powered silent-film birdhouses as street art in San Francisco.

What's inside

• From planetary science to TensorFlow, before it was GPU-capable
• Geophysicists as early GPU adopters
• The professors who said open-source wasn’t “real science”
• Building silent-film birdhouses as San Francisco street art
• Hiding Gemini API tests inside whimsical side projects
• The right-tool-for-the-job case for mixing AI models
• Why “taste” is the skill that matters when code costs nothing

Vincent Warmerdam has been the first full-time hire at a startup, a spacey punster who accidentally got himself a job, a bartender at an Amsterdam comedy theater, and a Dutch bike tour guide — and he'll tell you all of it was career development. Now doing DevRel at Marimo, Vincent makes the case for reactive notebooks, Lego-brick widgets, and why "number go up" is not a data science strategy. Also: chickens die. The model doesn't know. This matters more than you think.

What's inside

• How a spacey pun accidentally launched Vincent's career
• Why Marimo's constraints make it better for LLMs, not just humans
• The gorilla hiding in your dataset — and why the model missed it
• Vibe coding vs. notebooks: three cells at a time as a discipline
• Widgets as Lego bricks: reusable, composable, criminally underused
• Cognitive debt, confirmation bias, and sycophantic data science
• Why natural intelligence is still, actually, a pretty good idea

Benn Stancil built Mode Analytics, spent a decade in the data trenches, and now writes some of the sharpest, funniest essays in the data world. On The Test Set, he talks about the cultural shift from Nate Silver to Rick Rubin why AI might kill the analytics dashboard, and what happens when a thousand startups all build the same thing. Plus: boy bands as a model for collaboration, and why the best creative work starts with cheating.

What's inside: 

• Why the modern data stack was basically big data 2.0
• The cultural flip from Nate Silver to Rick Rubin
• Gas Town, tar pits, and the AI startup zero-sum game
• Software is becoming content, and that changes things
• Benn's creative process: Lorde lyrics, Codenames, and cheating
• The boy band as a model for small-team collaboration
• BI is (mostly) dead, and vibes might replace SQL

dbt Labs CEO Tristan Handy drops into The Test Set to map the fault lines between the data science world and the enterprise data world — and explain why analytics engineers are basically pissed-off data analysts who decided to organize the bookshelf. We get into SQL's glow-up, the community magic of dbt Slack, what AI agents mean for data warehouses, and why everyone's building iOS apps with Claude now.

What's inside:

• What analytics engineers *actually* do
• SQL's journey from deeply unsexy to indispensable
• How dbt turned source control into a source of truth
• Building a tech community without the RTFM energy
• AI agents on your data lake: permissions get personal
• Will LLMs kill the open-source package ecosystem?
• Edible gardening, welding dreams, and digital dysphoria

Nell Thomas has spent two decades in data — from equity research to the DNC to Facebook to leading a 400-person data org at Shopify. She walks Michael and Wes through the modern data stack role by role, gets honest about what AI is and isn't changing about data work, and admits the semantic layer has been her greatest leadership failure. Plus: Sneakers gets the respect it deserves.

Episode Notes
What does it actually look like to run data infrastructure for millions of merchants while the entire industry reinvents itself in real time? Nell Thomas (VP of Data, Shopify) talks vibe-coded dashboards, political campaign data scarcity, blameless postmortems, and why no one should be locking in on an AI strategy just yet. Recorded live in Times Square.

What’s Inside

• Mapping the modern data stack, role by role
• Why data quality is still the #1 problem
• What "good scrutiny" looks like on a data team
• Vibe coded dashboards and the trust problem
• Shopify's MCP for their data warehouse
• The throwaway tech problem in political campaigns
• Why the semantic layer is so damn hard
• Sneakers!

Phillip Cloud has been shaping the Python data ecosystem since the early pandas days — and he has *opinions*. Now a principal engineer at NVIDIA leading the Ibis project, Phillip talks about how he stumbled into open source via an eye movement lab, why he prefers his coding agents cold and emotionless, and what happens when you ask an LLM for woodworking trig. Plus: terminal user interfaces, the file hierarchy standard hot take nobody asked for, and the pineapple-on-pizza hill he's willing to die on.

Episode Notes

Phillip Cloud (NVIDIA, Ibis project) joins Michael Chow, Wes McKinney, and Hadley Wickham to talk about his path from eye movement labs to pandas core team, why developer productivity tools have quietly gotten amazing, his brutally honest take on coding agents, and what it would actually take to impress him. Also: VisiData love, NixOS evangelism, and yard work as therapy.

What’s Inside

• From eye movement labs and MATLAB to pandas core team
• Column multi-indexes: the feature nobody likes but Phillip needed
• Why your command line tool better have a sweet TUI
• VisiData: the terminal data tool you're sleeping on
• Are we writing code for humans or for agents now?
• Phillip's AI skepticism journey: Cursor, Claude Code, and frustration
• The Numba CUDA test suite port that would finally impress him