Product Leader, Ex Zalando, Flipkart. 

Zalando

Flipkart

eBay

Aditya Vithaldas

Product, Analytics and Engineering Leader, eCommerce & Fintech. Hands on builder

Build a Proactive Insights Layer for your ecommerce Store

Turn store data into clear, prioritized insights and recommended actions.

Build an insights layer anyone can use

Choose the tools, memory, permissions, checks, and human review needed to make the agent reliable.

Build a reliable AI agent

Pick a high-value workflow where better timing and context lead to a clear next action.

Choose the first ecommerce problem to solve

Leave with a working agentic analytics system on your machine, a polished analysis, and the patterns and frameworks to make it all yours.

Cohort 5

Principal Data Scientist @ Ontra 

Shane Butler

Principal Data Scientist @ Ontra | Ex-Stripe, Nextdoor, PwC, Appfolio

Data Science Leader |Ex-Microsoft

Sravya Madipalli

Data Science Leader@Superhuman (Prev. Grammarly)| Ex-Microsoft, eBay, Nextdoor

Head of Data @ Ontra AI | Ex-LinkedIn

Hai Guan

Head of Data @ Ontra | Ex-Nextdoor, LinkedIn, Pinterest, Meta

Bootcamp 4

Cohort 6

Anyone can get AI to produce analysis now. The hard part is knowing whether it is right.This is a five week, hands on course where you build an agentic analytics system in Claude Code, and then do the thing almost nobody teaches: prove it works.Weeks 1 and 2 you build. You set up your own environment, write your first skill, design and build a multi agent system, integrate it into a production repo, and connect it to your team's tools through MCP.Weeks 3 and 4 you make it trustworthy. You measure reliability across repeated runs, triangulate a question across independent methods of analysis, build ground truth, align an LLM judge to human labels, trace every answer back to the query that produced it, and engineer the context that makes the system correct on your company's metrics.Week 5 you put it to work. You swap the model underneath it, cross check one model against another, and turn the system into value your company can see.Ten live sessions, two hours each, with three instructors in the room. Every recording is yours to keep. Free course retake. Private AI Builders alumni community. No coding background required, no Python or SQL is ever written by you.

Build AI Analysts that do the work and prove the numbers are reliable. No code.

Build a multi agent AI analyst system from scratch

Integrate your system into a production analytics repo

Build an eval suite that proves your analyst is right

Align an LLM judge for work that has no right answer

Engineer the context that makes the system correct

Swap to open source models and triangulate across them

Product managers who are tired of waiting in the data team's queue. Stop waiting. Analyze it yourself.

Data scientists who want to multiply their output. You know how to do the analysis manually. Now automate it.

Engineers who want to make data-driven decisions without hiring a data team.

Stop being the “number explainer.” Build the stories, systems, and credibility to lead with clarity and confidence in the age of AI.

Data & AI Leader, 19yrs of scaling data

Wayfair

Scotiabank

Wunderflats

ZEAL Network SE

Pier Martin

Data & AI leader with 19+ years scaling global teams, Executive coach 

Cohort 10

Cohort 11

Do you lead a data or analytics team and you keep asking yourself:<ul><li>How do I get executives to act on my insights instead of nodding and moving on?</li><li>How do I influence Product, Marketing, and Finance when none of them report to me?</li><li>How do I build real credibility on AI without just demoing tools?</li><li>How do I get my team seen as a trusted partner, not a ticket shop?</li></ul>If those are your questions, you're in the right place. The work is strong. You are just not in the room yet when the decisions get made.Here you fix that by building your own AI Operating System. A working system that keeps supporting you long after the course ends. It remembers every stakeholder you map, drafts in your voice, pressure-tests your decisions before the room, and gets sharper every time you use it. One person, operating like a team.So you turn data into stories executives repeat. You turn AI pilots into business cases that win support. And the system keeps compounding, carrying more of your load as you take on more. You own it for life.

Get in the room with the decisions - taught by a VP who still runs a data team.

How to Make Executives Act on Your Insights

How to Lead AI Change Without the Fear

How to Run a Data Team That Scales

How to Decide What Matters Under Pressure

Folks who are early in their career, focused only on technical execution, or looking to break into data/analytics should not enroll.

This course is NOT FOR everyone

It is designed for data managers, analytics leads, and heads of data already managing teams and facing leadership challenges.

This is NOT a beginner-level technical course

The Overlooked Data Manager: you ship dashboards but get talked over in strategy rooms, and want to be trusted for impact, not output.

The Stretched Head of Data: you lead 5 to 15 people, firefight all week, and need a system that shows control and builds credibility.

The New Data Leader: just promoted from IC, strong technically but light on storytelling and presence, ready to lead in the AI era.

Transform from consumer of analytics to independent operator - asking sharp questions, validating answers, shipping decisions.

Stripe

Nextdoor

PwC India

Ontra

AppFolio

Microsoft

Grammarly

Superhuman

LinkedIn

Pinterest

Cohort 3

Cohort 4

As AI reduces the value of deep domain silos, the people who thrive will be the ones who can work across disciplines and ship. Analytical independence - the ability to validate your own ideas and make data-informed decisions - remains the missing skill in most builders' toolkits.AI can conduct the analysis, but it can't tell you what to ask or whether the answer makes sense. That requires analytical judgment.This course teaches you to think like a senior Product Data Scientist. You'll learn the frameworks used at FAANG companies to frame problems, choose the right metrics, diagnose root causes, execute the analysis, and turn insights into decisions.-&gt; <a target="_blank" rel="noopener noreferrer nofollow" href="https://join.slack.com/t/dataneighbor/shared_invite/zt-3ox4drc3r-3g0ptSthytkgv0sD6ovvqg">Join AI Builders Slack Community!!</a> &lt;-What makes this different: No SQL. No stats lectures. Five weeks of hands-on real scenarios. You'll build end-to-end, metric specs, deep dives, experiment plans, stakeholder readouts.The result: You become analytically self-sufficient. The last dependency removed from your toolkit. Make data-informed decisions in hours, not weeks.

Ask Better Questions, Make Faster Decisions - with AI as Your Analyst

Frame Problems Like a Senior Data Scientist

Design Metrics That Actually Drive Decisions

Diagnose Root Causes Without Guessing

Design Experiments That Ship

Turn Analysis Into Action With AI as Your Copilot

Synthesize Insights and Prioritize for Impact

Product Managers, engineers, and operators who need analytical independence and frameworks to measure success and drive decisions.

Designers and researchers stepping into strategy roles who need to quantify impact, run experiments, and influence with data-driven insights

Data professionals who want to frame better questions, delegate technical execution to AI, and drive impact with agentic analytics tools.

See your venture clearly, find what is holding it back, and choose the next move—so AI creates leverage instead of more work.

Systems Architect · Founder, Sysdom AI

THE WORLD BANK GROUP

Carnegie Mellon University

Han Kay

Systems Architect · Carnegie Mellon (MISM) · Triple Master's (MBA, MS) · 30+ yrs

Cohort 1

AI gives founders two possible futures. It can multiply company capacity—or multiply the coordination work returning to the founder. If you're building an AI-native or agentic company, adding agents is the easy part. The harder problem is turning their output into leverage without becoming the integration layer for every handoff, decision, and next move. The missing layer is the system the agents operate inside. That is Systems Intelligence.This four-week working lab turns Systems Intelligence into founder practice. Across four focused 90-minute sessions, you will map your venture, identify the active constraint beneath the surrounding noise, commit one bounded next move, and complete a founder-directed operating cycle.Sysdom.ai is the included, supported working environment. It organizes venture context across the Product/Service, Customer, Cash, and Skills Engines, preserves evidence, and records the chosen move. You remain responsible for direction, consequential decisions, and approval boundaries.Leave with a clearer venture state, explicit decision boundaries, one completed cycle, and a repeatable way to increase agent capacity without increasing founder coordination.

AI amplifies everything. Including what’s broken.

See your venture as one system

Build an evidence-backed venture map

Find the constraint behind the noise

Choose one bounded next move

Set founder and agent decision boundaries

Start a guided operating cycle

Bring research, a prototype, operating signals, prior decisions, or a serious plan. No website, revenue, or technical setup required.

Bring one real venture—and some evidence

Founders building a venture who feel complexity outpacing their mental model. You have pieces but no unified operating system.

Founders who hit their first real bottleneck and realized working harder isn't solving the structural problem underneath.

Founders whose AI tools and agents produce more output while every important decision and handoff still routes back through them.

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

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

AI for GTM

Sales

Customer Success

GTM Engineering

Everyone

Founders

Operators

Data Scientists

Business Analysts

User Researchers

Project Managers

HR Professionals

Sales People

Lawyers

Finance

Investors

Real Estate

Educators

Creators

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

Engineers and engineering leaders who build, deploy, and scale software systems.

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

Building autonomous AI agent systems that take actions, use tools, and orchestrate multi-step workflows.

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

Build a Proactive Insights Layer for your ecommerce Store

What you'll learn

Why this topic matters

You'll learn from

Aditya Vithaldas