Director of AI Education at A+ Active

Cityblock Health

HashiCorp

The New School

PrismML

Webflow

Jai Bhagat

How to explain AI tradeoffs to leadership

Turn latency, cost, quality, privacy, and safety concerns into decision-relevant options.

Translate technical tradeoffs

Explain what is known, what is untested, and what would reduce risk without pretending the answer is certain.

Frame uncertainty clearly

Use a concise decision brief format for pilots, model choices, and production-readiness conversations.

Recommend a next move

Arming senior leadership teams with the AI literacy, practical skills and strategic acumen needed to guide their companies into the AI era.

September 2026 Cohort

AI Strategist // Trainer // Futurist

Mark Laurence

Founder and lead consultant at generative AI consultancy Ten Past Tomorrow.

NZTE Private August 2026 Cohort

October 2026 Cohort

“We're going to get to AI systems that are better than almost all humans at almost all tasks... That's the thing I think we're quite likely to get in the next two or three years." - Dario Amodei (CEO, Anthropic. However… ”Only 8% of employees reported they feel GenAI is already transforming their organisation.” - Deloitte - State of Generative AI in the Enterprise report, Q4 2025. Quite frankly, the gap between AI advancement and AI adoption that those two stats speak to is just too large. It’s no longer just a gap. It’s a chasm. And add to that… “In organisations where AI is openly embraced, the chance of developing 'AI Experts' and 'AI Practitioners' is halved when direct managers discourage its use, either directly or indirectly.” - Section School - The AI Proficiency Report. Merging those three storylines and you get a headline that says that senior leadership is the bridge that connects AI aspirations to organisational reality, and ultimately the trajectory of its integration at every level. In other words; true organisation-wide AI adoption doesn’t begin with technology or tools. It begins with leadership. AI literate and AI skilled senior leadership.

Close the AI capability gap: Exec-level training for senior leadership teams

Master AI prompting fundamentals

Evaluate and select AI tools strategically

Discover how to truly scale AI usage throughout your business

Develop a 5-step AI transformation roadmap

Lead AI change management

Implement AI governance and privacy practices

Senior leadership teams wanting to collectively, confidently, knowledgeably, skilfully and ethically lead an AI-forward company.

SLT teams who sense AI is far more than a technical challenge, that it demands leaders step forward to lead comprehensive strategic change.

Leadership teams excited by making a genuine commitment to fundamentally reshape their people, processes and businesses.

Eliminate uncertainty in shipping AI features

GenAI Product Builder @ Google, ex-Meta

Marily Nika, Ph.D AI/ML

Senior Data, ML and GenAI Scientist

George Zoto

Senior NLP/AI Scientist

August-2026

“Does it work?”... “Is it good enough?”... “Can we ship it?”...How do you answer these questions for AI products? You’re responsible for “running evals” but what does that mean?How do you choose the right metrics, interpret fuzzy results, and make a confident decision?This course gives you a framework to do just that.<ul><li>Map user value to evaluation (eval) objectives so your metrics aren’t abstract. Define success then translate it into measurable criteria.</li><li>Choose metrics you can actually maintain: capability, safety, UX friction, latency, cost and “does this reduce support tickets or increase activation.”</li><li>Set ship/no-ship thresholds you can defend to leadership.</li><li>Build lightweight workflows that work in real teams: human review where it matters, automation where it lasts, documentation that drives decisions.</li><li>Consider domain constraints (e.g., healthcare safety) and know what to avoid: silent failures, misleading proxy metrics and tests that don’t reflect production.</li><li>Tie everything to ROI: impact vs unit cost, eval coverage vs reliability, and the minimum viable monitoring you need post-launch.</li></ul>Experience AI evals through a case-based approach with a real AI product that we evaluate together.

Acquire and develop a critical skill for product managers who are leading and contributing to AI products.

Make confident ship or hold decisions for AI features

Translate user value into clear evaluation goals

Choose the right metrics for capability, safety, UX, and cost

Set defensible thresholds leadership will trust

Build lightweight evaluation workflows teams can maintain

Navigate domain constraints and avoid common failures

PMs leading AI features, growth, or platform initiatives

PMs who partner with ML teams and want to set evaluation standards

PMs who need to make clear “ship or hold” calls without doing the engineering

Make more cohesive product and design decisions at AI speed with clearer logic, stronger value cases, and better judgment under pressure.

Product & Design Leader at Owtcome

Owtcome

Krasi Bozhinkova

Cohort - May 2026

Cohort - Oct 2026

AI has made building faster, but product success hasn't gotten easier.Teams are now making more product-shaping calls with less time, more pressure, and incomplete evidence. The challenge is no longer just whether a single decision is right, but whether many fast decisions still add up to a coherent product direction.This course teaches a repeatable Product Judgment System for that challenge: how to clarify the critical user need that should guide decisions, build the value case, define the trust conditions, find where growth breaks, and choose the right product move when conditions change.It is built for PMs, designers, and product leaders whose product thinking needs to hold up when AI creates more ideas, more prototypes, more pressure, and less time to wait for certainty.You’ll leave with practical decision tools to apply judgment where it matters most: choose which user need deserves focus, pressure-test weak value cases, decide what deserves momentum, protect trust, and know what must change when the market shifts.The goal is to help you keep product decisions coherent under pressure and prioritize the work that will drive adoption, retention, trust, and business outcomes.

Apply a Product Judgment System for better decisions at AI speed

Create clarity before weak logic becomes a shipped product

Build the value case when the evidence is still incomplete

Define the trust conditions that keep product decisions coherent

Fix what blocks growth and choose the right response

PMs, designers, and cross-functional leaders with 3-5 years of experience, working through ambiguity, trade-offs, and business outcomes.

Level of experience

Bring one live product, feature, or strategic decision to apply the course directly to your own context.


What to prepare

This course is designed for practitioners who want to make better product decisions in AI-shaped markets, not to teach a specific AI tool.

No technical AI background required

Mid-to-senior PMs who need to make harder product decisions fast and connect the value case to adoption, trust, and growth.

Designers expanding their influence who need sharper language to connect design decisions to product and business outcomes.

Product-minded engineers and cross-functional leads stepping into ownership who need to make hard product calls with incomplete evidence.

Defend a real decision on camera with AI removed, scored twice, and learn the practice that keeps your judgment sharp.

Exec Coach to Google, PayPal, the NFL

Google

Amazon

PayPal

U.S. Army

Joshua Miller

Master Certified Exec Coach to Google, PayPal, Amazon | LinkedIn Top Voice

Cohort 1

Your output has never been faster. And somewhere in the last year, you noticed you could not fully explain a decision you had just made. Not the outcome. The reasoning underneath it.Most leaders respond by promising to read the output more carefully. That does not work, because you cannot detect this in yourself. People rate their own understanding highly right up until someone asks them to explain it out loud.That is Cognitive Atrophy. You did not lose intelligence. You stopped using the one capability your role rests on.AI can analyze, model, and recommend. It cannot sign its name. When the call goes wrong, nobody asks the model. They ask you. And the problem is not that your calls are wrong. It is that you have lost the ability to tell.Leaders who cannot explain their reasoning stop being handed the decisions that matter. Nobody says why. It just stops.In four weeks, you defend a real decision on camera with AI removed, scored in week one before any instruction and again in week four. You leave with proof, not notes.Every other course on decision-making is assessed using the tool. This one is assessed with it gone.

Every other course teaches deciding with AI. This proves you can without it.

Answer the follow-up you never prepared for because AI answered it first

Form your own position before the tool has framed it for you

Interrogate AI output that is persuasive and confidently wrong

Catch your own erosion while it is still reversible

Name the assumption your decision rests on, without notes

Defend a real decision with the tool removed, scored twice

Senior Executives and VPs<blockquote>The board will ask how you got there. "The analysis supported it" is not an answer anyone accepts twice. </blockquote><h3></h3>

Directors and Senior Managers<blockquote>AI made everyone's output look the same. Judgement is the only thing left that gets you promoted. </blockquote>

Founders and CXOs<blockquote>No one will ever ask you to explain a call. You find out you were wrong when the company does. </blockquote>

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.

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

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.

Executive communication — presenting to boards, writing memos, running all-hands, and high-stakes messaging.

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

How to explain AI tradeoffs to leadership

What you'll learn

Why this topic matters

You'll learn from

Jai Bhagat