Boston University

Quickbase

Ahold Delhaize

Purdue Global

Seth Forbes

Founder & Organizational Data Strategist, Ex-Senior SaaS Analyst @ Quickbase

How to Build Strategic Judgment in Analytics

Crossville

Ex-Senior Analyst @ Quickbase

We get a data request, fulfill it, and move on with our lives. But is that really the best way?

Diagnose the Order-Taker Trap

In reality, data teams are often far from the realities of the business. Keeping them separate is a disservice.

Examine the Disconnect Holding Data Teams Back

With AI absorbing execution, we'll explore the skills required to start driving business strategy.

Shift from Reacting to Influencing

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

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 5

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 9

Cohort 10

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.

Cohort 3

Stripe

Nextdoor

PwC India

Ontra

AppFolio

Microsoft

eBay

Grammarly

Superhuman

LinkedIn

Pinterest

Cohort 2

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.

After completing this course, you’ll move from being “told to lead AI” to leading with clarity, credibility, and results.

Data & AI Executive, Board Member

Fredy Diaz

Data & AI leader, board member, mentor, US Marine

Summer 2026

Fall 2026

Executives and managers are being asked to “have an AI strategy” without clear definitions, approve tools and pilots without confidence they’ll deliver value, balance innovation with risk and governance, and explain AI decisions to boards, auditors, and stakeholders, all without breaking trust or the budget.This course shows you how to lead through that ambiguity.You’ll learn how to define AI strategy in terms executives and boards actually care about, decide where AI should not be used before problems arise, right-size talent without overhiring or creating bottlenecks, evaluate tools objectively without becoming dependent on vendors, and choose projects that can survive procurement, politics, and operational reality. You’ll also learn how to communicate AI clearly, when the stakes are high and scrutiny is real.By the end of five weeks, you’ll have an executive-ready AI strategy, a practical roadmap, and a clear briefing you can use immediately.This course is built for leaders who are done with pilot purgatory, shiny tools with unclear ROI, and strategy decks that collapse at implementation. If you’re responsible for AI outcomes, this course will give you the confidence to deliver.

Lead AI strategy with confidence without getting lost in tools, pilots, or hype

Define AI Strategy with Measurable Outcomes

Build the Right AI Talent & Operating Model

Select Tools That Deliver Real Value

Prioritize High-Impact AI Projects

Communicate your AI Strategy

Senior Executive or Deputy (C-Suite, SES, VP, Director)

AI, Data, or Digital Leader (CDAO, Head of AI, Product, IT, or Innovation)

Business or Program Leader Owning AI Outcomes

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

Introduction to Strategic Judgment and Analytics

Seth Forbes' Professional Background and Experience

Real-World Examples of Analytics Mishaps and Miscommunications

Understanding and Avoiding the Order-Taker Trap

The Importance of Trust and Strategic Partnership in the AI Era

Defining Strategic Judgment and Essential Critical Thinking Skills

Practical Framework for Structuring Data Requests and Upcoming Course

Q&A: Addressing Forecasting and Strategy Challenges in B2B Sales

Data scientists who apply statistical and ML techniques to extract insights from data.

Getting promoted, navigating job transitions, and advancing to the next level in your career.

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

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

Persuading stakeholders, presenting ideas, and getting buy-in across an organization without formal authority.

Business analysts defining requirements and bridging business and technical teams.

How to Build Strategic Judgment in Analytics

What you'll learn

Why this topic matters

You'll learn from

Seth Forbes