Ohio State University

University Of Georgia (UGA)

Microsoft

Dr. Danny Glassmann

20+ yrs higher ed leadership · Former Dean Ohio/SF State · PhD · AI + belonging

Build an AI Trust Check

Danny Glassmann, Ph.D.

Former Dean · Founder · AI Leadership

Learn how to identify what an AI-generated answer assumes, omits, or overstates before you rely on it.

Spot AI Assumptions

Practice a simple process for tracing claims, checking source independence, and evaluating trustworthiness of evidence.

Check Claims and Sources

Use a practical trust-check workflow to decide what to use, revise, reject, or verify further before acting.

Make the Human Final Call

Gain hands-on mastery of AI research tools and frameworks to deliver trusted insights faster while maintaining the rigor that matters.

June 2026

AI Research Expert | Johns Hopkins PhD

Google

Capital One

Bloomberg

Pinterest

John Whalen, PhD

PhD. O'Reilly author. Host of AI for UX, where I interview AI tool founders.

Schedules alternate to support multiple time zones. This cohort meets 7-9 pm (EDT).

April 2026

July 2026

The researchers I talk to feel two things at once: overwhelmed by the pace of AI, and watching real possibilities open up that didn't exist two years ago.Both are true. AI lets you run 500 interviews across 12 countries in a week. It surfaces patterns across thousands of sessions. It opens research to teams who never had budget for it. Synthetic users let you pressure-test ideas in hours. These are new ways of working.But how do you trust the output? Which tools deliver, and which produce confident nonsense?That's the shift this course is built around: from doing research one study at a time to orchestrating systems that scale. You'll get hands-on with the platforms researchers actually use (Listen Labs, Coloop, Marvin, Synthetic Users), hear from the founders building them, and build the judgment to know what holds up.This is Course 1 of 2 in the Certified Agentic Research Specialist program — your foundation. Course 2, Agentic AI for Research, builds on it. The researchers pulling ahead are orchestrators — conducting research with more reach, impact, and confidence than before.No hype. Just what works.

Create Customer Insights with AI You Can Actually Trust

Conduct AI-moderated customer interviews confidently

Extract insights from 50+ interviews using AI-powered analysis tools

Develop frameworks to assess new AI tools and know when they actually work

Use synthetic users for rapid testing and validation of ideas before launch

Guide your team or organization in adopting AI research tools and best practices

Connect with practitioners navigating AI research together and sharing insights

You've worked with customer insights in some capacity—whether you've conducted research yourself, collaborated with researchers on your team

Experience with customer research or user feedback

This is a practical course with weekly exercises using AI platforms. You'll need time to experiment and apply what you learn.

Willingness to try new tools hands-on

We use tools and prompting techniques that don't require any coding knowledge. If you can write clear instructions, you're ready.

No technical background required

Researchers seeking to deliver insights faster at scale using AI—while maintaining the quality and rigor that makes their work trustworthy.

PMs and research leaders balancing the need for rapid customer insights with concerns about maintaining quality, rigor, and team standards.

Designers seeking practical AI tools to understand users, test concepts, and make evidence-based design decisions with confidence and speed.

We show you what's possible with AI, then take you there.

Founder | Meta/Amazon/Statsig/Tencent

Statsig

Amazon

Boston Consulting Group (BCG)

Tencent Games

Yuzheng Sun, PhD

Prev. Evangelist @ Statsig (Acq. by OpenAI), AI Director @ Tencent; Meta/Amazon

Applied Scientist | yage.ai

Yan Wang, PhD

Applied Scientist @ Samsara | Olympic Torchbearer | Ex Pinterest/Microsoft | Ex Tech blogger with 100k+ subscribers

Cohort 12

Cohort 13

Is this you?<ul><li>Chatting endlessly with an “AI intern” instead of designing the context with clear principles.</li><li>Blaming “hallucinations” when the real issue is poor orchestration.</li><li>Trying to run an entire project from a single, overloaded chat window.</li><li>Treating AI like witchcraft and prompt spells instead of engineering.</li></ul>AI gets better every day. But when it’s time to ship something serious, you don’t yet have a reliable way to make AI show up for you.The problem isn’t AI. It’s how you’re using it. This course exists for that exact gap.AI is a new computing paradigm. To use it well, you have to:<ul><li>Unlearn old patterns</li><li>Install new mindsets and habits</li><li>Build a meta-learning system that can carry your career for the next 20 years</li></ul>That's hard, and we take it seriously. This course is designed to teach you how to fish. On top of lessons and projects, we built two unique tools:<ol><li><a target="_blank" rel="noopener noreferrer nofollow" href="https://youtu.be/dXjcy6XSN_Y">A build platform</a> that consolidates key APIs and lets you deploy your projects with one command—so you can build fast, not fight boilerplate.</li><li><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.superlinear.academy/c/share-your-projects/">A lifetime community</a> where you can share projects, ask questions, and get unstuck long after the course ends.</li></ol>The end of our course is the beginning of your learning, and we will be with you.

Learn AI for the Next 20 Years, Not the Next 20 Days

Engineer Robust Context to Eliminate Hallucinations

Curate "Sterile" Contexts for Peak AI Performance

Architect Multi-Agent Systems to Conquer Complexity

Define Success Criteria to Transmute from Operator to Manager

Build "White-Box" Evaluation Tools to Visualize Quality

Design Self-Healing Loops for Autonomous Optimization

Software Engineers &amp; Developers Ready to build reliable, scalable AI systems integrated into production workflows.

Technical Product Managers &amp; Strategists Seeking the hands-on knowledge to scope, architect, and guide AI initiatives with confidence.

Data Professionals &amp; Automation Experts Who want to transform proof-of-concept scripts into durable applications that multiply productivity.

From Experiments to Scale: How Leaders Build High-Performing, Trusted AI Systems

Fractional Chief Product and AI Officer

Fanatics

eBay Inc.

Walmart

Upwork

Subha Shetty

AI-first product leader, transformation coach, and advisor to F100 and start-ups

Evals are having a moment - and for good reason. As AI systems move from pilots to production, leaders are confronting a hard truth: performance without trust doesn’t scale and AI drift is real.But evals alone are not the system.This workshop reframes evals within a broader, executive lens: performance + governance = trust at scale. You’ll learn how leading organizations are moving beyond isolated testing toward building AI systems that are measurable, reliable, and continuously improving.Grounded in insights from leading institutions and practitioners such as the WEF, McKinsey, Deloitte, Stanford HAI, and voices such as Dario Amodei, Andrew Ng and more - this session connects cutting-edge thinking to practical execution. This is a highly interactive session. You will:<ul><li>​Work hands-on to design and build your own eval (for an AI or agent use case)</li><li>​Explore how Guardian Agents, KYA (Know Your Agent), and feedback loops enable trust at scale Why This Matters Now The conversation is shifting from What can AI do? to Can this system scale and be trusted? Winning leaders will go beyond the best pilots - they will build high-performance governed AI systems that are continuously improving.</li></ul>

You will walk away with your first (or improved) eval. 
A trust framework with evals, governance, HITL, Guardian Agents and more...

Diagnose AI trust issues more precisely  

Build your first eval or improve an eval 

Map 20+ trust techniques to solving the issue  

Write your Governance policy 

For product/AI leaders scaling systems<ul><li>You run evals but unsure they're measuring the right things</li><li>You need a system to catch AI drift early</li></ul>

For leaders dealing with org trust<ul><li>Stakeholders are skeptical of AI and you can't articulate why</li><li>You're asked to "make AI more reliable" </li></ul>

For leaders moving from pilots to production<ul><li>You're responsible for AI quality and inherited a system with fuzzy measurement infrastructure</li></ul>

Everyone is learning to build AI agents. Few can prove one is safe to deploy.

Ph.D. Scholar, CISSP, CISA, AAIA™, CDPSE

Cyber Pros Training

Centene

ISACA

Trenton Health Team

François B. Arthanas

Agentic AI Governance Practitioner | Ph.D. Candidate, CISSP, CISA, AAIA™, CDPSE

Learn how to govern agentic AI systems before they create risk, fail audits, or get your org in trouble.

Cohort 1

AI agents are not chatbots. A chatbot answers a question. An AI agent retrieves customer records, calls tools, triggers workflows, issues refunds, sends emails, and acts sometimes before a human ever reviews the output.That means the question landing on YOUR desk is different:Can this agent leak PII? → Can it be prompt-injected through a poisoned document? → Can it call the wrong tool or the right tool with the wrong authority? → Can it issue an unauthorized refund? → Who owns the risk? And what evidence proves the controls actually work?Most professionals freeze at this question because they've only ever seen AI governance as policy slides and framework acronyms. They've never actually run an agent risk review end to end.In this one-day sprint, you will. You'll take a realistic enterprise AI agent through the complete practitioner loop scope → risk → control → test → evidence → decision and finish the day having written and defended a real deployment recommendation.You will watch an AI agent get broken live. Then you'll learn exactly how to make sure it never happens on your watch.

In one day, you'll run a real AI agent risk review start to finish and leave able to do it again at work, with the templates to prove it.

Scope a real enterprise AI agen a support agent that can access customer data

Break it: Run a live red-team session against the agent (no coding required)

Turn your findings into a one-page Trust Snapshot leadership can act on

Make the call and defend it in a live mock review board

You do not need to be an engineer. You do not need to know how to code. You do not need advanced AI expertise.

There are no strict prerequisites for this course

If you are curious about AI agents and want a practical way to think about oversight, this workshop will meet you where you are and move you

What you do need is an interest in understanding how AI is changing governance

This workshop is for professionals who know AI agents are becoming important and do not want to get left behind.

It is built for GRC, IT, cyber, privacy, legal &amp; consultants who need to understand how agentic AI changes the governance conversation

You should join this workshop if you want to understand how AI agents create risk &amp; how to contribute meaningful value inside your org

The AI Evaluation Handbook

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

Broad professional audience — content relevant across many roles and functions.

Measuring and evaluating AI model performance, quality, and reliability for production use cases.

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

Establishing policies, ethics frameworks, and oversight for responsible AI use in organizations.