Jun 15, 7:30 AM – 3:30 PM (UTC)
As Agentforce, Claude Code, MCP, & conversational interfaces make solution development faster than ever, success increasingly depends on knowing what to build—and what not to build. Join this interactive workshop to learn how to define effective AI use cases, design trusted data architectures, and reduce delivery risk through better business, data, context, and architecture decisions.
AI is making it easier than ever to build the wrong thing faster.
The challenge is no longer the speed of development. It is knowing what to build, what not to build, and why and how to design solutions that can avoid predictable adoption risks.
Many AI initiatives struggle because teams start with technology instead of business outcomes, underestimate data quality and security concerns, or design architectures that cannot scale beyond a pilot.
In this interactive workshop, we will work through a practical framework for:
Defining effective business use cases
Designing trusted solution and data architectures
Identifying integration architecture, data quality, and security risks that can impact adoption and success
This is a collaborative working session—not a product demo or hands-on configuration workshop. Come prepared to participate, share ideas, and challenge assumptions.
Architects, Consultants, Admins, Business Analysts, Product Owners, Data Leaders, and anyone responsible for turning AI ambitions into measurable business outcomes.
To maximize discussion and interaction, participation is limited to 18 attendees. We will release 22 registrations to account for normal attrition.
Please register only if you are reasonably confident you can attend. If your plans change, kindly cancel your registration so another community member can participate.
PeerNova, Inc.
SVP, GM and Data Strategist
Monday, June 15, 2026
7:30 AM – 3:30 PM (UTC)
VML
CONTACT US
