inspAIre

Design AI-Powered EdTech: Learning Science Foundations

Sabancı Üniversitesi

Neo Skola

Ilkem Kayican Dipcin

15+ yrs in Learning Design, Founder at inspAIre

Turn learning science into product requirements your engineers can build or your vendors must deliver.

The 5-Step Translation Framework

Watch me translate spaced repetition into a feature spec, from simple implementation to AI-enhanced personalization.

Live Demo: Spaced Repetition → Product Spec

Evaluate any AI-powered learning claim using the Learning Science Audit to spot real innovation vs. marketing hype.

The AI Reality Check

Build AI Agents in 4 weeks with proven frameworks that add 6-8+ fig to a business bottom line, no coding required

Cohort 15

On the ground Agentic AI Practitioner

Sara Davison, Agentic AI Practitioner, Speaker, Educator

Co-Founder AI Build Lab 

Tyler Fisk

Cohort 14

Cohort 16

‼️ Revamped 2026 Curriculum! Context Engineering, Orchestration Agents, Agent Design, Evals + More! -------------------------------------------------------------------------------👉👉👉 Build the Skillset That Will Define the Next Era of Work &amp; Become the Agentic AI Practitioner Companies Are Desperately Seeking The Future of Work Is Agentic - The Skills Gap Is Your OpportunityOn one side:📈 82% of leaders plan to use AI agents to scale their teams📈 28% of managers are considering hiring AI workforce managers to lead hybrid teams of humans + agents📈 32% of companies plan to hire AI agent specialists within the next 12–18 months(MS Work Trend Index 2025)On the other side:📉 Only 1% of executives believe their AI investments have reached maturity📉 47% of C-suite executives identify talent skill gaps as the primary barrier to successful AI implementation(Mckinsey, Superagency in the Workplace 2025)Tl;dr:📉Very few people actually know how to do this workThat’s the gap.And for the few of us who know how to design and build AI Agents &amp; agentic systems, that gap is opportunity👉WE TEACH YOU THE FUNDAMENTALS OF OUR AI AGENT &amp; AGENTIC WORKFLOW IMPLEMENTATIONS THAT START AT $25K-6 FIGURES.

The Path To Becoming A 1% Agentic AI Practitioner -  Zero Coding Required

Think Like an Architect, Not an AI User

Master Context Engineering (Not Just Prompt Engineering)

Design Agent Systems Before You Build Them

Build Knowledge Bases That Make Agents Context-Aware

Build & Orchestrate Multi-Agent Workflows

Engineer Safety & Reliability At Scale With Evaluations + HITL

Non tech-professionals wanting to become the 1% AI leaders &amp; operators in the workplace

Consultants and agencies looking to offer AI consulting and implementation services

Entrepreneurs &amp; business owners looking to build businesses as scalable, growth machines

In the last 12 months, AI has shifted from a "tech trend" to a market-decimating force. The old playbook of simply "shipping features" is dead; leaders must now build "Contextual Moats" and defensible strategies. This course bridges the gap between Executive Leadership and AI Strategy. We take the rigor of the #1 Ranked Advanced Product Management curriculum and infuse it with the frameworks needed to win in the age of AI. What You'll Get Out of This Course 1. Define Strategic Leverage (Not Just Features) Stop searching for problems to solve with AI. Start with customer problems and identify where AI creates breakthrough leverage. Master the 4 Sources of AI Leverage: Data, Distribution, Trust in UX, and Learning Loops. Learn to build "Contextual Moats" that endure when the underlying models become commodities. 2. Shift from "Roadmaps" to "Planning in Motion" Traditional planning assumes the environment will cooperate long enough to execute. In AI, that assumption breaks. Learn to build a "Sensing Function"—a structured review of model performance and competitor moves. Move from a unit mindset to a systems mindset, creating roadmaps that adapt to new information without descending into chaos. 3. Architect the Human + Agent Workforce Output can now rise through leverage, not just headcount. This isn't about replacing people; it's about changing the mix of work. Learn to design the "Baton Pass": deciding where tasks are repeatable (Agents lead) and where judgment and novelty matter most (Humans lead). Structure your org to scale impact without scaling headcount at the same rate. 4. Master AI Economics &amp; The "Trust" Metric Powerful models cannot compensate for a weak core value proposition. You will master the new P&amp;L: forecasting inference costs that scale linearly and managing the "Cost vs. Quality" trade-off. You will also learn to measure Trust in UX as a first-class metric, setting tolerances for error and building affordances for user control.

Lead the AI Transformation. Don't just witness it

Course syllabus

You'll have 5 hours of class split into two 2.5-hour modules. Each module consists of 60% lecture-style learning and 40% hands-on group exercises. Don't worry about missing a class—you can make up missed classes in a future cohort, and you'll receive the recordings right away.

Saturdays

The capstone project allows you to go through the end-to-end lifecycle of developing a major feature for a consumer company like Facebook, Google Maps, or Amazon, and present it in a product review meeting to the VP of Product at Shopify.

Weekly Capstone Projects (Optional)

We will spend about 20 hours on the core course material plus about 6 hours on Q&amp;A. Timings for each session have been chosen based on what works best for most product people in practice. Recordings for all modules will be made available for you to watch in your Maven account.

Optimized for very busy schedules of PMs / Execs / Managers.

Course schedule

Ambitious Senior PMs, GPMs, &amp; VP Level Leaders: Leaders who are responsible for product success and need to crystallize their skills to lead

Founders &amp; Executives: Those who realize that "be first to market" is no longer enough and need a strategy that provides a durable advantage

Note: This course is not for early-career PMs or those looking for a basic introduction to prompt engineering. This is a strategy and leader

Who is this course for

What you’ll get out of this course

Understand the non-obvious factors that lead to AI product success and how to think strategically when every competitor has access to the same APIs.

Master the AI Leader's Mindset
 

Learn to recognize when your data is a true moat versus when it isn't, and develop specific strategies to build durable competitive advantages that go beyond fragile tech differentiation.

Build Defensible "Contextual Moats"

Implement a proven system to take AI features from Discovery to Design, Develop, and Deploy—ensuring you ship real solutions, not just demos.

Execute with the 4D AI Method

Master the art of forecasting inference costs that scale linearly with usage and optimize the "Cost vs. Quality" trade-off to ensure profitability, not just hype.

Navigate AI Economics & Unit Economics

Build high-conviction roadmaps for high-risk, high-reward AI bets that account for uncertainty and rapid technological change.

Develop Strategic AI Roadmaps

Communicate complex AI product proposals with clarity and precision to secure executive support and cross-functional excitement.

Drive Strategic Alignment & Stakeholder Buy-In

Structure your AI initiatives for scale from day one by defining metrics that matter in a probabilistic world and avoiding the trap of endless experimentation.

Escape "Pilot Purgatory"

Align engineering, design, and data science teams on a unified vision and learn to lead effectively in an AI-first organization.

Lead Cross-Functional AI Teams

Gain insights from guest speakers including Joff Redfern (Ex-CPO Atlassian), Amit Fulay (Generative AI Leader), and Surojit Chatterjee (Ex-CPO Coinbase).

Learn from Elite Product Leaders

Complete a hands-on capstone where you develop and present the end-to-end lifecycle of a major AI feature for a consumer company, applying everything you've learned in a product review format.

Ship a Real AI Product Strategy

In the AI age, nothing matters more than Strategic Leverage. Architect it. Scale it. Master it. Win.

Satyajeet Salgar

Director of Product, Google AI

Joff Redfern

Frm. CPO at Atlassian and VP of Product  Linkedin

Amit Fulay

Vice President of Product, Uber

Cohort 4

Cohort 5

The Leadership Crisis No One Talks AboutIt's 2:47 AM and you're staring at the retention dashboard. Again. Your "AI-enhanced" feature launched to fanfare three months ago... great press, executive excitement, promising initial adoption. Now you're watching 73% of users abandon it after the first session. Tomorrow's executive product meeting is focused on exactly this: the design problem causing the retention cliff. You need to present research findings and lead a strategy discussion that could reshape your entire approach to AI. This isn't just about fixing a feature, it's about defining what AI design leadership looks like. Why This Moment MattersYour credibility was built on predictable delivery. For years, you shipped experiences that worked consistently. Now you're pioneering something entirely new, and that positions you to lead the industry standard. The paradigm has fundamentally shifted: Traditional UX Design:- Deterministic systems with predictable, consistent experiences- One-way interaction where users experience a fixed interface- Success measured by users completing intended paths AI Systems:- Non-deterministic learning systems where every interaction changes future behaviour- Bi-directional adaptation where both human and AI evolve through each encounter- Success measured by the quality of the evolving relationship﻿ 54% of people don't trust AI systems despite 61% of respondents using them daily. (University of Melbourne and KPMG, 2025) That retention cliff isn't a failure; it's feedback. Users sense the mismatch between predictable tools and learning entities. You're uniquely positioned to solve what no one else has figured out yet. The OpportunityThe leaders who master relationship design first won't just solve their retention problems; they'll become the case study everyone else studies.This is your chance to define what trustworthy AI design looks like, rather than follow standards someone else sets. A Leadership Transformation in Three MovementsThis intensive journey rebuilds your leadership approach for the relationship design era: 1. Leading Through UncertaintyHow to guide teams building systems that learn and adaptCommunicating AI value to executives without overpromisingMaking decisions about technologies you're still mastering 2. Building Trust-First TeamsEstablishing design processes for non-deterministic systemsCreating quality standards for evolving AI relationshipsDeveloping team capabilities in trust signal design 3. Scaling Relationship DesignImplementing frameworks that work across your entire organisationMeasuring success in dynamic, learning systemsBuilding competitive advantage through trustworthy AI ﻿For Design Leaders Under PressureDesigned for leaders who must deliver AI transformation while maintaining team confidence and executive credibility—who recognise that relationship design isn't just a new methodology, it's the fundamental shift that determines whether your organisation leads or follows. Whether you're currently:A UX Design Leader orchestrating team transformationA UX Research Leader scaling insights through AIA Strategic Design Leader defining AI-enhanced experiencesWhat unites our participants is their recognition that leading AI adoption requires something more nuanced than traditional management approaches. The Essential Leadership Outcomes You emerge with:Frameworks to guide teams building learning systems you can't fully predictLanguage to communicate AI value without technical BS to executivesProcesses that maintain quality while embracing non-deterministic outputsMetrics that prove relationship design delivers measurable business impactA network of leaders defining the standards everyone else will follow Most importantly, you join a community of leaders pioneering this emerging discipline; professionals who understand that the most valuable AI systems won't be those with impressive technical specifications, but those designed with profound understanding of human trust dynamics. A Limited ExperienceLimited to fifteen participants per cohortFocused on meaningful exchange and personal attentionA deliberate practice developed through engagement with fellow leaders "The leaders who recognise this shift first won't just survive the transition—they'll define what relationship design looks like for everyone else." ** This course can you considered as an Add-On to the Human-Centred AI : Building AI Systems People can Trust. https://maven.com/ai-flywheel/human-centred-ai

Lead with Trustworthy AI: Design, Innovate & Inspire

Weekly LIve Ethics Lesson 90 minute sessions where we unpack 1 ethical principle in depth and have peer to peer conversation.

Thursdays - Live Workshops

You'll be given<ul><li>&lt; 60 min of e-learning modules per week</li><li>practical exercises</li><li>micro-habits to apply learnings directly to your AI use in your daily work</li></ul>

Self paced learning 

You have access to BONUS lessons to build your personal AI literacy - this optional session is a group coaching opportunity for any questions or challenges you have using AI for your own work.

Optional - AI Help Office Hours

UX &amp; Design Directors : Balancing executive AI demands with your team's creative integrity and fear of replacement.

UX Research Leaders : Scaling research with AI whilst preserving methodological rigour and meaningful human insights.

Service Design Leader : Reimagining end-to-end experiences with Human+AI interactions whilst maintaining human agency and trust.

You'll leave being able balance innovation with user trust, giving you confidence to lead AI initiatives that executives support.

1. Strategic AI Roadmap for Design Teams

Master proven design patterns that increase user trust in AI features by 30%. You'll learn exactly where transparency, human oversight, and error correction mechanisms create measurable improvements in adoption and retention.

2. Trust-Building Design Patterns 

Transform your designers from AI-overwhelmed to AI-empowered with frameworks that show exactly where AI enhances rather than threatens creativity. You'll restructure workflows that boost productivity whilst preserving your team's unique human value.

3. Team Transformation to AI-Enhanced Operations

Establish yourself as your organisation's trusted authority on Trustworthy AI design. You'll master the language, metrics and case studies that convince skeptical stakeholders, positioning you as the strategic bridge between technology and human experience.

4. Leadership Positioning Strategy

The live weekly sessions we unpack 1 ethical principle using a real world case study of an AI implementation that went wrong. Having peer-to-peer discussions and practice applying the ethical principle to a new case study. Allowing you to practice applying in safe space.

5. Real-World Implementation of AI Ethical Principles

Design leaders are under pressure -  expected to adopt AI, guide teams through change, protect creativity, and build trust at scale.

Riley Coleman

Nov 

February 2026

How to think through AI problems end-to-end: scoping, debugging, and knowing when to pivot.

ML Engineer with 10+ years of experience

Hugging Face

DataRobot

Contextual AI

Snowflake

Snorkel AI

Rajiv Shah

Enterprise AI veteran: Shipping AI to production, with clarity and humor

Pilot Cohort

AI Problem Framing is to AI practitioners what System Design is to software engineers and Product Sense is to PM. This is the foundational thinking skill that separates senior from junior.--🚨 Pilot cohort: February 16 – March 20, 2026 - limited to 25 students. 🚨This is the first run of the course, that means:• Never before published material, you see it first!• Smaller cohort = more direct access to me• Pilot pricing won't last---What you get:🔄 The Loop, a 5-step framework you'll use to think through every AI project🧑‍🏫 Live sessions and office hours where you can bring your real problems📊 Access to 200+ case studies, the largest collection of AI reframing examples📋 Production-ready checklists for RAG, Forecasting, GenAI🎥 Lifetime access to all recordings---This course is for you if:• Your AI works in demos but fails in production• You've spent months on a model only to realize you solved the wrong problem• Stakeholders ask for solutions that feel wrong, and you can't explain why• You're leading AI initiatives but came from engineering or product (not ML)You'll learn from 200+ AI failures in 5 weeks. You gain years of experience and recognize the scars.

Most AI fails from bad framing, not bad models. Learn to fix that.

Frame AI problems right the first time

Diagnose what's actually broken

Own the problem, not just the solution

Steer your team past expensive mistakes

We focus on framing and strategy, not explaining what models or training means. Basic vocabulary lets us go deeper faster.

You understand what AI/ML is at a conceptual level

Real experience gives you context. The frameworks click when you can map them to projects you've actually built or managed.

You've worked on or led AI projects in some capacity

This is about decision-making, not implementation. You'll learn what to build and why, not how to code it.

No coding during the course; frameworks for thinking, not tutorials

Engineers who can build AI but want to master outcome engineering: knowing what to build, not just how

Building RAG, agents, or ML models? Let's get your demos into production! Learn the thinking that makes the difference.

Tech Leads and Engineering Managers who need to evaluate AI/ML proposals and catch bad ideas early