Oauth

How to Pass Context in an Agentic AI Flow

How to Pass Context in an Agentic AI Flow

Grant Miller contrasts the static, single-application context of traditional OAuth with the dynamic, multi-system nature of agentic AI. He explains that agentic flows, involving orchestration, multiple agents, and LLMs, require a more sophisticated approach than simple prompt engineering. The video introduces 'context engineering' as the key strategy, which involves managing the entire system state, user context, and task history to optimize AI interactions and deliver accurate, context-aware responses.

Identity for AI Agents - Patrick Riley & Carlos Galan, Auth0

Identity for AI Agents - Patrick Riley & Carlos Galan, Auth0

This session from Okta and Auth0 introduces a comprehensive framework for securing AI agents, covering identity establishment, delegated API access via Token Vault, user consent for risky operations using Asynchronous Authorization (CIBA), and integration with MCP servers.

Production Ready AI Agents

Production Ready AI Agents

Sam Partee, CTO of Arcade, explains the critical gap between AI agents that gather context and those that take secure, real-world actions. He introduces Arcade as a middleware platform that solves complex challenges like user authorization, fine-grained permissions, and token management, enabling developers to build scalable, enterprise-ready agents.