Enterprise HRIS & Quality Leader
Data Quality & AI Risk Specialist


Get to know your instructor and fellow PMs, BAs, and Product Owners
Understand the structural reasons documents pass review with hidden gaps, and where AI changes the equation
Take a moment to connect with your instructor and classmates
Hands-on: craft AI prompts that interrogate requirements, surface assumptions, and flag missing acceptance criteria in real documents
Take a moment to connect with your instructor and classmates
Extend the framework to progress reports and change requests; the documents most likely to obscure delivery risk
Leave with a tailored, reusable checklist and prompt library matched to your project context
Connect with your instructor and classmates before you go

HRIS Manager with 25+ years in systems, data, and analytics


CEO of an AI-driven, IP-generating, quality-focused company



PMs, BAs, and Product Owners who are the last line of defense before a document moves to execution and want to be confident in that role
Stakeholders who approve project documents regularly but lack a structured method for knowing what to look for
Delivery leads who have experienced late-stage surprises caused by gaps that were present at sign-off but never caught.
Live sessions
Learn directly from Sue Lhymn, Ph.D. & Laura Harris, Ph.D. in a real-time, interactive format.
Hands-on verification practice
Work through real document examples with AI tools at each step; leave with prompts you can use immediately
Verification prompt library
A ready-to-use collection of AI prompts for requirements, status reports, and change requests
Lifetime access
Return to recordings and materials whenever you need a refresher
Community of peers
Stay connected with a cohort of practitioners facing the same approval challenges
Certificate of completion
Share your new capability with your employer or on LinkedIn
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
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Be more efficient in working with stakeholders through customer focus, process and risk-based thinking.
Reduce ambiguity by defining requirements and expectations clearly.
Continuously improve by managing requirements, processes, and controls consistently.
Your focus on customer orientation, continuous improvement, process thinking, and risk-based thinking is especially relevant right now, particularly for people working in AI and other fast-moving technical spaces where strong outcomes depend on strong systems.
As someone working at the intersection of data, AI, and organizational performance, I found this talk to be a valuable reminder that quality is not just about end results; it is about the strength of the processes that produce them.

Dylan Collier
$225
USD