Agentic Privacy Discussion
DeCompute 2026
Hosted by Silence Laboratories, this focused session brings together forward-thinking technologists and privacy architects to examine how we can build and deploy AI agents while maintaining robust privacy guarantees and user trust.
Location
San Francisco, California
Date
Wednesday, 29 April
2026
Time
03:00 PM to 04:30 PM
Local Time
KEYNOTE SPEAKERS
Jason Clinton
CISO, Anthropic
Jason joined Anthropic in April 2023 after more than a decade at Google, where he most recently led Chrome infrastructure security working on defense against advanced persistent threats. While at Google, he also worked on ChromeOS and Android Pay. At Anthropic, Jason guides security strategy including detection and response, compliance, physical security, security engineering and IT. Jason promotes the security organization’s work to uphold Anthropic’s Responsible Scaling Policy framework, ensuring that the company has appropriate security safeguards in place for the responsible development and deployment of AI models. He is also the author of “Ruby Phrasebook”.
More speakers to be announced soon
EVENT DETAILS
As agent-based systems become increasingly prevalent, organizations face critical questions about data exposure, user privacy, and maintaining confidentiality in autonomous decision-making processes. This keynote explores how privacy-preserving design principles can be embedded into agent architectures from the ground up—without compromising capability, transparency, or operational effectiveness.
Designed as an intimate discussion, this session creates space for direct engagement with leading perspectives on agentic privacy, including architectural best practices, emerging technical approaches, and practical considerations for organizations deploying agent systems responsibly.
Discussion Themes
Privacy-preserving approaches to autonomous agent design
Data minimization and confidentiality in multi-agent systems
Trust and transparency in agent decision-making
Privacy-enhancing technologies for agent infrastructure
Regulatory and compliance considerations for agentic AI
Practical deployment models for privacy-first agent systems