Probabl invites you to their event
About this event
Every step up the AI curve buys speed. Every step also opens a new way to lose control.
Most data science teams sit somewhere between copilot-assisted coding and agents that run whole loops on their own. The productivity gain is real. So is the cost: statistical rigour that quietly erodes, models that look great until production, sensitive data drifting into places it shouldn't, and tooling that locks you in.
On September 29, Yann Debray, Chief Product Officer at Probabl, walks through where teams actually stand today, where the control gap opens, and what it takes to adopt agents in data science on your own terms.
Yann Debray is Chief Product Officer at Probabl, the company stewarding scikit-learn (200M+ downloads a month). Based in Paris, he leads the product as Probabl builds the methodology and validation layer between AI coding tools and production. He previously led MATLAB Online at MathWorks, worked at Scilab, and has written on Python, MATLAB, and Claude Code.
Data scientists, ML engineers, and DS leads who are using or evaluating AI coding tools for modelling work, and want the speed without giving up control of what ships.
It's live, and the Q&A is the part a replay can't give you. Come with the question you've been arguing about internally.
📅 Tuesday, September 29 · 6:00pm CEST / 12:00pm EDT · 45 mins
🎁 Live attendees only: at the end of the session we'll open a limited number of 30-minute Tabular AI diagnostic slots, a working session on how your team uses agents and TFMs today, and where the gaps are.
Probabl is the Tabular AI company by the creators of scikit-learn. After standardizing how the world does machine learning, we're enabling enterprise data science teams to adopt AI with confidence.
