Product Leader, Ex Zalando, Flipkart. 

Zalando

Flipkart

eBay

Aditya Vithaldas

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

Build versus buy in a world where everybody is a builder

Apply five checks: expertise, business focus, scope, reliability and differentiation.

Know how to assess whether a capability is worth building

Factor in integration, maintenance, incident coverage and the core work your team would postpone.

Compare the ongoing costs of building and buying

Use evidence to align builders and ROI owners on the choice, operating ownership and success criteria.

Draft a shared build, buy, combine or defer recommendation

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.

Turn a recurring task into a two-minute AI run

Founder, AI Over 50 · ex-Google Director

Brett Bouchard

Ex-Google Director, 20+ yrs in tech, Founder of AI Over 50

Cohort 1

A Skill is a recipe for work that repeats. Your steps, your standards and a good example, written once. Your AI runs it the same way every time on whatever you hand it next. It's a document you own, so it works in ChatGPT, Claude, Gemini or whatever comes next.It stops the re-explaining. No more retyping instructions or living in one long chat that slowly forgets. You hand off the chores that never go away, and you get expertise you don't have on tap: a second opinion, an editor in your voice, a checker for confidential work. One student, a realtor, built a Skill that values a home from recent nearby sales, after a paid app gave him a number he knew was wrong.You leave with two things: a library and the ability to build more. A set of ready-made Skills to use the same day, plus the Skill Builder, which interviews you and writes the Skill, so you can build any Skill you need after the workshop. In the session you build two: a Decision Brief together, and one of your own for real work.You'll learn it from someone who runs on it. 20+ years in tech, including Google, and I run my own solo business on these same Skills every day. Built for people over 50, no hype.

Go from retyping the same instructions to Skills that do your recurring work, plus the know how to build any Skill your work needs.

Build a Skill for a task that never goes away

Get a second opinion on any decision, built on your criteria

Build any Skill you need, long after the workshop

Take your Skills to any AI you use

Start with a library of ready-made Skills

Someone who already uses AI and wants the next level of productivity: a system that does real work, not one-off answers.

A solo or small business owner, or a consultant, with weekly tasks worth handing off.

Anyone weighing Level 1 who wants to see how I teach, and build something real with the material, before committing.

By the end you'll have a benchmark for your job, a small model measured against a big one, and a cost sheet that says what it's worth.

Developer Relations, PrismML

Jai Bhagat

Owns a GB10, has spent $4,000 renting models, and prices AI work live.

Expertise into products people pay for

Nicole Mercede

Went from billing hours to owning what she produces; runs the pitch week.

If you do knowledge work for a living, a large share of your week is one judgment call made over and over with slightly different inputs: triage the inbox, categorize the request, decide how the company should answer, write it in the house voice, log it, report on it. Nicole used to bill that kind of work at $85 an hour for about twenty-five hours a week, roughly eight thousand dollars a month of labor that a general-purpose model can already do most of, and that a small specialized model might do better and cheaper. This cohort exists to find out whether that's true for your job, on hardware you control, and what it would be worth if it is.I'll be straight about what this is: an experiment with a method, not a guaranteed outcome. I own an NVIDIA GB10 and I've spent about $4,000 of my own money renting frontier models, so I know what each rung costs, but I don't yet know how far a small model trained on your domain gets on Apple Silicon or the GB10. We find out together over three Fridays, with a benchmark that's allowed to tell us no. If the answer is no, you leave knowing it with the numbers attached, which is a result I'd pay for.

Your expertise is worth more as a model than as hours

Build a benchmark for your own job

Train a small model and read its result honestly

Pick your bet and price it

Leave with a pitch or a decision

Bring one job you know well and a laptop; most recent ones can run a small model, and I run the heavier jobs on my GB10.

No GB10, and no engineering degree, required

Knowledge workers whose week is mostly one repeatable judgment, and who would rather sell the model than keep selling the hours.

Founders and domain experts who know a corner of healthcare, education, or public infrastructure better than any model does.

Builders who can already run and fine-tune a model but have never had to defend its unit economics or name who would pay for it.

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

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.

Executives and senior leaders who set strategy, lead teams, and drive organizational outcomes.

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

Setting strategic direction, making high-stakes decisions, and translating vision into execution.

Developing intuition for what makes a great product — evaluating ideas, understanding user needs, and making tradeoff decisions.

Build versus buy in a world where everybody is a builder

What you'll learn

Why this topic matters

You'll learn from

Aditya Vithaldas