Intro to Claude Code Analytics
A live, hands-on half-day. Walk in with zero Claude Code experience. Walk out running real analytics on your own machine.
Hosted by AI Analyst Lab — Shane Butler, Sravya Madipalli, and Hai Guan
How Agentic Analytics Works
Live end-to-end walkthrough
Watch a full agentic analytics workflow run end-to-end in Claude Code. From stakeholder question to final chart. No highlight reel. The whole thing, live, with the work shown at every step.
Set Up Your Claude Code Environment
Hands-on installation
Install Claude Code on your machine. Configure your account. Get authenticated. Verify everything's working. We stay with you until it does. Nobody leaves stuck on the install step.
Run Your First End-to-End Analysis
Build it live with us
Clone the open-source AI Analyst repo. Point it at a real dataset we provide. Watch it frame the question, pull the data, build the chart, write the narrative. Debug live with us when it doesn't go right the first time.
Publish Your Work + Live Office Hours
Ship and ask anything
Post your first chart from the analysis to LinkedIn (or save it to your portfolio). Then stay for live Q&A about your specific use case. Bring the data problem you've been trying to solve. We'll work through it together.
The Transformation
Wednesday morning vs Wednesday afternoon
What changes between walking in at 7 AM and walking out at 10 AM.
Before — Wednesday morning
- ✕You've watched a few demos, never actually run it
- ✕Claude Code isn't installed on your machine
- ✕You wonder if this is actually real for someone like you
- ✕No portfolio piece to show what you can do
- ✕Stuck after the install step every time you've tried
After — Wednesday afternoon
- →Claude Code installed and running on your machine
- →The AI Analyst cloned, configured, and producing output
- →You've shipped a real, end-to-end analysis
- →A chart on LinkedIn that proves it
- →A room of people you can keep building with
Your Hosts
Meet your instructors
Three practitioners with a combined 40+ years building data and AI systems at the companies you know.
Shane Butler
Principal Data Scientist, AI Evaluations · Ontra
Previously at Stripe · Nextdoor · AppFolio · PwC
Shane is a Principal Data Scientist at Ontra leading AI evaluation strategy for product development in legal tech. He brings 10+ years of experience in product data science, causal inference, and measurement across B2B SaaS and consumer products from roles at Stripe, Nextdoor, AppFolio, and PwC. His work focuses on practical methods for evaluating AI features in production, connecting offline quality signals to real user and business outcomes. He co-hosts the Data Neighbor podcast interviewing product, data, and engineering leaders shaping next-generation analytics in AI-driven landscapes.
Sravya Madipalli
Senior Manager, Data Science · Superhuman
Previously at Microsoft · eBay · Nextdoor · Grammarly
Sravya is a Senior Manager of Data Science with 14+ years helping teams make better decisions with data. She has built and led data science and product analytics teams at Microsoft, eBay, Nextdoor, and Superhuman, collaborating closely with product, engineering, marketing, and leadership. Her expertise spans experimentation, metrics design, modeling, analytics, and translating complex user behavior into clear, actionable insights. She mentors data scientists and non-data partners to think analytically, ask sharper questions, interpret results confidently, and make decisions despite imperfect data. She brings real-world big-tech analytical frameworks adapted for modern teams using AI as a copilot.
Hai Guan
Senior Director / Head of Data · Ontra
Previously at LinkedIn · Nextdoor · Pinterest · Meta
Hai has spent 16+ years teaching data professionals, PMs, designers, and leaders to think analytically. At Nextdoor, LinkedIn, Pinterest, and Meta, he built and scaled data teams transforming how companies make product decisions. His teams drove projects that doubled user acquisition, scaled products to IPO, and launched business units becoming growth engines. He has mentored hundreds of non-data professionals to ask better questions, interpret results confidently, and make decisions without waiting for an analyst.
Who This Is For
Built for the people who keep getting stuck
PMs and Product Leaders
Tired of waiting on data teams. Want to run your own analyses.
Designers and Researchers
Want to back your work with data without learning SQL from scratch.
Engineers and Operators
Comfortable with code. Want to use AI to do real analytical work.
Founders and Solo Builders
No data team. Need to make data-informed calls. Fast.
One ask: if you sign up, you're committing to actually showing up Wednesday morning. We're putting our time in. We need yours too.
Wednesday, June 10 · 7am - 10am PT
If you'd actually show up, we want you in the room.
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