AI Red Teaming for Leaders: Break It Before It Breaks You
Noelle Russell
AI Exec, former Amazon, Microsoft, IBM
AI Is Powerful. But Can You Trust It? Learn How to Test Before You Adopt.
AI is changing how we work, make decisions, and do business. But as organizations move quickly to adopt AI, many overlook a critical question: What happens when AI gets it wrong?
From inaccurate information and biased responses to security vulnerabilities and unexpected behavior, AI systems introduce risks that aren't always easy to recognize. Red teaming takes a proactive approach to AI safety by intentionally challenging systems to uncover weaknesses before they become real-world problems.
In this masterclass, you'll go beyond the concept. You'll learn the four layers where AI systems fail, the six attack patterns red teams use to find those failures, and then you'll spend a full hour breaking a live AI assistant yourself, in a team, with a scorecard. You'll leave knowing how to write a finding that gets acted on, how a red team hands its work to a governance board, and exactly what to test first on Monday.
Whether you're a business leader, professional, entrepreneur, or AI enthusiast, you'll gain a practical understanding of how to question AI outputs, identify warning signs, and approach AI adoption with greater confidence.
What you’ll learn
Move beyond simply using AI to confidently identifying risks, challenging AI responses, and making smarter, safer AI decisions.
Map hallucinations, bias, jailbreaks, and data leaks to the Human-AI Experience, System Prompt, Model, or Infrastructure layer.
Recognize risks such as prompt injection, inaccurate information, biased outputs, and potential exposure of sensitive data.
Practice prompt injection, persona hijacking, context manipulation, data extraction, bias probing, and boundary pushing in a live lab.
Document what you tried, what happened, how severe it is, which layer owns the fix, and the one-sentence change that closes it.
Leave with a 10-question readiness checklist, a testing cadence, and a plan for who finds, who decides, and what you test first on Monday.
Workshop agenda
When AI Gets It Wrong: The Five Failures and the Four Layers
A live demo of a custom GPT breaking in three minutes, the five ways AI fails, and the four-layer safety framework that tells you where each failure starts. Ends with a failure autopsy in pairs.
How Red Teams Work: The People, the Method, and Your First Attack
What red teaming is and how it differs from QA and security testing, who belongs on the team, and the six attack patterns. You’ll run your first three prompt injections on a sample GPT.
Red Teaming Lab: Break a Hardened AI Assistant Layer by Layer
Teams of four attack a hardened HR assistant GPT in four rounds, one per layer, logging every attempt on a scorecard with severity ratings. Then a debrief on the worst findings and what they share.
From Findings to Governance: Report, Brief the Board, Set the Cadence
Write a finding that gets acted on, meet the governance board that owns the safety system, brief a mock board on your worst lab result, and leave with a testing cadence and a readiness checklist.
Learn directly from Noelle
Noelle Russell
6× Microsoft MVP who has trained millions of leaders in responsible AI.
Who this workshop is for
Leaders and decision-makers responsible for evaluating AI tools, managing risks, and supporting safe AI adoption in their organizations.
Entrepreneurs & builders developing or using AI-powered solutions who want to recognize vulnerabilities and improve safety and reliability.
Professionals and AI learners who want to understand AI risks, evaluate responses, and use AI more confidently and responsibly.
What's included
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
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