Staging environment
Shane Butler
Sravya Madipalli
Hai Guan
Free Lesson

Validate Claude Code Analytics Output

Part of The AI Evaluation Handbook

60 min
Jun 17, 2026 11:00 AM

What you'll learn

Run a 4-layer validation on any AI analysis

Check structure, logic, business rules, and segment-level reversals before trusting the output.

Define evidence that supports a ship decision

For each step, specify what evidence would justify ship, iterate, or stop, and what “evidence” is misleading.

Catch errors AI analysis gets wrong

Learn the specific failure modes where AI confidently produces wrong answers and how to spot them.

Re-derive findings to confirm correctness

Use Claude Code to approach the same question a different way to measure both capability and reliability

Why this topic matters

AI analysis tools are confident even when they are wrong. Most people eyeball the output and move on. This lesson teaches a 4-layer validation stack so you can catch structural errors, logic mistakes, violated business rules, and hidden segment reversals before the wrong number hits a stakeholder deck.

You'll learn from

Shane Butler

Shane Butler

Principal Data Scientist at Ontra

Sravya Madipalli

Sravya Madipalli

Senior DS Leader (Ex-Microsoft)

Hai Guan

Hai Guan

Head of Data at Ontra, Ex-LinkedIn

Previously at Stripe, Nextdoor, PwC

Stripe
Nextdoor
Ontra
PwC India
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