RL Nabors makes a case against chat as the permanent UI for agents, arguing it's the "terminal" to the future "iPhone" of rich, interactive experiences. She demonstrates how to build these experiences using web technologies, introducing MCP Apps for in-agent UIs and WebMCP for making existing websites agent-callable, positioning the web platform as the ultimate "infinite canvas".
AI agents are having a moment, and understanding MCP and ADK is key to building them well. Cedric Clyburn and Anna Gutowska explain how MCP powers tool integration while ADK structures reliable multi‑agent systems 🤖. Learn when to use each to build more capable and predictable AI agents.
Pedro Rodrigues from Supabase shares key lessons from building an agent skill to work with Postgres and Supabase. He explains why critical security rules must go in the main skill file, the importance of pointing to living documentation, and how providing opinionated workflow guidance closes the reliability gap for agents in production systems.
MCP Apps transform tools into interactive UI inside hosts like ChatGPT and VS Code. This summary covers the core architecture, the paradigm shift towards a 'new web' of composable UI, and the future of distributing applications in an agent-first world.
A deep dive into building, testing, and iterating on Agent Skills to improve AI agent performance. This workshop covers the core concepts of progressive disclosure, eval-driven development, and practical application using a real-world Supabase and PostgreSQL security scenario.
AI agents can interact with the world through either the Command Line Interface (CLI) or the Model Context Protocol (MCP). This summary explores the trade-offs between the two, highlighting CLI's efficiency for tasks the model is trained on, versus MCP's power of abstraction and governance for more complex, high-level operations.