Amplitude AI Analytics

Validate Your Idea with Data Before You Build

Miro

LEGO®

Microsoft

Elena Avramenko

15+ yrs in Product & Marketing, award-winning founder, 100+ new product launches

Run your idea through a 5-question diagnostic that exposes the validation steps most builders skip.

Diagnose whether you're about to “vibewaste”

Lock in your WHO, PAIN, PROMISE, and the riskiest assumption that has to be true to make each next decision clear.

Write a sharp, testable bet on your idea

Walk the 14-day arc from sharp bet → ICP → interviews → Lovable prototype → Amplitude signals.

See the full path from bet to evidence-based verdict

Learn from a world-leading expert how to design and analyze trustworthy A/B tests to evaluate ideas, integrate AI/ML, and grow your business

Author of best-selling A/B testing book

Airbnb

Amazon

Dr. Ronny Kohavi

Technical fellow and VP at Microsoft & Airbnb, co-author of A/B testing book

9 March 2026

1 June 2026

Through multiple real examples of well-run experiments and stories from Microsoft, Amazon, and Airbnb, you will see the humbling reality that we are terrible at assessing the value of ideas.Trivial changes can be surprisingly useful, whereas large efforts often fail. Accelerate innovation by building Minimum Viable Products (MVPs) and features, and make the organization more evidence-based and humble as it adopts and learns to use evidence from the gold standard in science—the controlled experiment.You will understand the challenges in designing and running trustworthy randomized controlled experiments (A/B tests), including the importance of the Overall Evaluation Criterion (OEC), scaling, common pitfalls, and Twyman's Law. We cover cultural challenges, institutional memory, maturity model, observational causal studies, offline evaluation, AI/Machine learning and triggering, build-vs-buy trade-offs, challenges, and requested topics. The Advanced Topics course is designed as a technical follow-on: <a target="_blank" rel="noopener noreferrer nofollow" href="https://bit.ly/AdvancedABFS">https://bit.ly/AdvancedABFS</a>

Empower your organization to be data-driven and innovative

Internalize the humbling reality: we are poor at assessing the value of ideas

Understand the key advantages and limitations of A/B testing

Learn how to design metrics and the Overall Evaluation Criterion

Learn how to design trustworthy A/B tests

Learn about the cultural challenges

Learn about the relationship to AI and Machine Learning Modeling

Data science managers and scientists will be able to design and interpret the experimental results in a trustworthy manner

Program managers focused on growth, revenue, conversions, and prioritization will understand how to provide the org with robust clear metric

Engineering leaders will be able to make organizations more data-driven and efficient with fewer severe incidents through A/B tests

Master GenAI-powered human-centered design process using the Make it Toolkit for behavioral-informed product and service design.

Managing Partner - Customer Centric LLC

Citi

mPulse

Humana

McKesson

Majid Al Futtaim

John Gusiff

Managing Partner at Customer Centric LLC, Certified Maven Instructor

Insights Architect, Consultant CX/UX/MR

Caterpillar

Everwise Credit Union

Aditya Birla Group

Mahnaz Hajesmaeili

Podcast Host SWARM and GenAI Prototyping Expert

Cohort 2

Cohort 3

✨ Course OverviewApply Behavioral Science to Your Design Sprints with the Make It ToolkitMost design sprints focus on features. This course goes deeper 🔍.You’ll learn a proven step-by-step process for running a Behavioral Design Sprint—combining behavioral science 🧠 with the Make It Toolkit 🛠️ and GenAI-powered methods 🤖 (always with Human in the Loop 👤).By the end, you’ll know how to:🎯 Translate business challenges into behavioral challenge statements🗺️ Map user journeys through the lens of the Five Laws of Behavior🧩 Spot and prioritize hidden barriers to progress💡 Generate behavioral design interventions that actually change behavior📐 Prototype solution concepts through sketches, storyboards, journey maps, and simple mockups — turning ideas into tangible, testable outputsYou’ll work on real case studies (🏥 healthcare, 🎓 education, 💰 financial services) so you can practice applying these tools in contexts that matter.⚡ This isn’t theory. It’s a hands-on, case study–driven experience designed to help you uncover hidden barriers, generate stronger solutions, and leave with validated hypotheses ready for prototyping.👉 Reserve Your Spot Today – Limited Seats Available

Apply Behavioral Science to the Design Sprint process using the Make it Toolkit

Frame Behavioral Challenges Clearly

Map & Diagnose the Behavioral Journey

Ideate using 15 Make it Strategies + Tactics

Formulate Behavioral Design Hypotheses

Prototype Solution Concepts

Apply GenAI-Powered Methods with Human Oversight

Design Sprint facilitators looking to better align teams on more focused customer outcomes via a behavioral challenge statement.

Product managers wanting to make sure the products and services they design are behavioral informed and more likely to succeed.

Designers wanting to have better context around the users they are designing for and the specific behaviors that need to be influenced.

AI lets you build fast  >>> The real risk is building the wrong thing.

15+ years Product&Marketing, 100+ MVPs 

Cohort 4

Cohort 5

Vibe-coding tools like Lovable and Claude let you go immediately from idea to prototype. What used to take weeks now takes hours. That sounds like an advantage — but it's created a new problem: vibewasting - building fast without clarity or a plan.Building the wrong thing faster just gets you to the wrong place sooner😉.Most vibe-coders skip the one step that determines whether any of it is worth it: validation. They start building the moment they have an idea — before they've talked to a single customer, before they know if the pain is real, before they know if anyone would pay.This workshop fixes that. In 2 hours you'll build a clear plan for the next 14 days — giving you much more confidence in your idea and helping you justify further investment of time and money. We'll start by writing a sharp bet on your idea, define exactly who your first customer is, and design interview questions that surface real pain. You'll also create a Lovable prompt that specs the tiniest version worth building - something you can vibe-code in an hour and put in front of real people to validate. You leave with a 14-day validation plan, ready to test before you invest weeks building the wrong thing.

A first-time founder or side-project builder with a business idea who wants to test it before spending weeks vibe-coding the wrong thing.

A vibe-coder who has already built something that didn't get traction and wants a structured approach before starting their next idea.

A professional or domain expert who spotted a problem in their industry and wants to validate it as a business before learning to build.

 In one day, validate YOUR AI Opportunity & leave with a 90-day plan.

ICF MCC · MBA ESSEC · 6,500+ sessions 

Judith Glory

ESSEC MBA · ICF MCC · Executive Coach · 6,500+ sessions

Stop debating about AI. In one day, validate your opportunity and leave with a 90-day plan.

The pressure to act on AI is real. But most leaders are making decisions based on hype, vendor pressure, or fear of being left behind — not on evidence.The result is predictable: pilots that fade, budgets wasted on tools that never get used, and leadership teams that keep debating instead of deciding.This workshop exists because there is a better way. In one structured day, you apply a proven framework to your team's specific reality — not AI in general, not someone else's use case. You evaluate what you do today. You identify where AI could genuinely help. You name every risk and price it. And you make a clear go or no-go call you can stand behind.Not every team should move forward with AI right now. If your numbers say no, this workshop will tell you that clearly — and give you the conditions under which yes becomes the right answer. A No-Go decision backed by data is worth more than a yes driven by pressure.

Managers and leaders navigating the AI moment who need clarity, not inspiration — and a plan they can defend to senior leadership team.

Team managers, VPs, and senior leaders who sense the AI opportunity but need evidence to act — or to confidently say not yet.

Leaders responsible for team output who are ready to validate their AI opportunity once and for all — no tech background needed.

The Agent-Powered Super IC

Agentic AI

Coding with AI

AI Workflows

Claude Code

OpenClaw

Vibe Coding

AI Evals

AI Transformation

RAG & Search

AI for PMs

AI for Engineers

AI for Designers

AI for Marketers

AI for Founders

Product Sense

Product Discovery

User Research

Prototyping

Growth

Analytics

Tech Foundations

Strategy

Influence

Leadership

Career Growth

Machine Learning

LLM Ops

Context Eng

Security

System Design

Figma

Design Systems

Visual Design

Design Strategy

Automation

Content Marketing

Demand Gen

Go-to-Market

Product Marketing

Positioning

Social Media

Brand

B2B Marketing

SEO & AEO

AI for Leaders

AI Governance

Communication

Management

People Operations

Exec Presence

Storytelling

Goal-setting

Personal Brand

Fundraising

Everyone

Operators

Data Scientists

Business Analysts

User Researchers

Customer Success

Project Managers

HR Professionals

Sales People

Lawyers

Finance

Investors

Real Estate

Educators

Creators

Product managers who drive strategy, development, and launch of products.

Startup founders building new businesses, from MVP to scale.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Using data and metrics to measure performance, run experiments, and inform decisions.

Conducting user interviews, surveys, and usability studies to understand customer needs and validate decisions.

Identifying opportunities and validating what to build through customer research, experimentation, and prioritization.

Finding and validating product-market fit — identifying underserved markets, testing hypotheses, and iterating to fit.

Validate Your Idea with Data Before You Build

What you'll learn

Why this topic matters

You'll learn from

Elena Avramenko