Webinar Description
Key Takeaways
- Two-part virtual series examining governance challenges for AI agents operating outside traditional enterprise boundaries
- Addresses security risks when AI agents execute code on developer laptops, bypassing VPCs, CI/CD pipelines, and IAM systems
- Designed for technical leaders, DevOps engineers, and security professionals in AI-native enterprises
- Features live demonstrations of Docker’s governance and sandboxing technologies
About the Event
The Docker AI Governance Webinar is a two-part virtual series addressing the governance requirements for AI agents that operate beyond conventional enterprise infrastructure. As AI agents increasingly execute code directly on developer workstations, organizations face visibility and control gaps that traditional security architectures were not designed to handle.
The sessions examine why established governance approaches fall short and explore enforcement mechanisms that operate below the agent layer. Docker’s product and engineering leaders lead the discussions, which include live demonstrations of the company’s governance solutions.
Governance Challenges for AI Agents
The webinar explores limitations of current governance tools, including MCP gateways, LLM gateways, agent mesh architectures, and remote development environments. A central theme is that partial solutions cannot provide consistent policy enforcement when agents run across diverse environments. The sessions argue that true isolation requires establishing security boundaries beneath the agent layer itself.
Technologies Covered
Docker technologies discussed include Docker Sandboxes, MCP Enterprise Gateway, Gordon (Docker’s AI Agent), Model Runner, Hardened Images, Docker Scout, Docker Desktop, Docker Hub, and Docker Offload. The demonstrations focus on how these tools provide oversight and policy enforcement regardless of where AI agents execute.
Who Should Attend
The series targets VPs of Engineering, Solutions Engineers, Product Managers, Security Architects, and DevOps Leads. It is particularly relevant for technology companies and organizations adopting AI-driven development workflows who need to maintain consistent security posture as agent capabilities evolve.