Define Your AI Development Strategy and Build Predictable, Secure Agents at Scale

The Challenge:

Organizations are caught in an AI development paradox. Business teams are “vibe coding” bespoke no-code agents in silos, while engineering teams are bogged down in complex custom pro-code integrations. This fragmentation creates massive security risks, operational inefficiencies, and a new era of shadow IT. To achieve true scale, leaders need a unified roadmap that matches the right tool to the right problem.

What You Will Learn:

• The AI Builder Spectrum: Unpack the differences between no-code (Workspace Studio, Gems), low-code (AI Studio, AntiGravity), and pro-code (Vertex AI SDKs, custom GCP models).
• Matching Problem to Tool: A repeatable framework to decide when to empower citizen developers and when to deploy full-stack engineering resources.
• Governance by Design: How to enforce Acceptable Use Policies (AUP) and security controls across all levels of the builder landscape.
• Live Multi-Tier Build Demo: See a live, step-by-step progression of an agent starting as a simple no-code prototype and transitioning into a governed pro-code deployment.

Who Should Watch?

• IT Directors & Security Admins: IT professionals looking to curb “shadow AI,” protect proprietary data, and establish strict Model Armor and DLP controls over employee-built integrations.
• Operations & Change Management Leads: Leaders focused on driving safe, company-wide AI adoption, organizing citizen developers, and boosting operational efficiency.
• Citizen Developers & Line-of-Business Managers: Non-technical business users looking to leverage Gems or Workspace Studio to automate daily tasks, but wanting guidance on scaling safely.
• Software Engineers & AI Architects: Developers looking to see how to quickly transition quick, “vibe-coded” prototypes into robust, production-grade custom builds in GCP.