Building Interactive UIs in VS Code with MCP Apps — Marlene Mhangami & Liam Hampton, GitHub

This talk explores strategies for effectively integrating and managing third-party tools within AI agent workflows, specifically focusing on Multi-Call Protocol (MCP) servers. It addresses the common challenges of generic tool descriptions, unexpected agent behavior, and potential performance degradation or security risks when using off-the-shelf tools. The presentation outlines a framework of five best practices to tailor these tools for specific use cases, ensuring agents perform as intended and applications remain stable.

This talk explores how to move beyond traditional code coverage metrics to ensure true functionality testing, especially in the context of AI-assisted development. It argues that while AI can increase code output, its true productivity gains are amplified by clean codebases and robust testing. The presentation introduces Playwright as a tool for end-to-end browser testing, demonstrating how it can be integrated with AI agents to accelerate development workflows, particularly within a test-driven development (TDD) framework.

This talk explores the evolution of generative UI for Multi-Component Platform (MCP) applications, moving beyond static components to more dynamic and collaborative interfaces. It posits that current AI models are capable of generating sophisticated UI code, prompting a re-evaluation of how users interact with AI-powered applications. The core thesis is that the future of generative UI lies in collaborative experiences rather than just component-based outputs.

This talk introduces Chrome DevTools for Agents, a purpose-built debugging tool for AI agents, drawing parallels to the widely used Chrome DevTools for human web developers. The core thesis is that agents, as a distinct user class, require specialized interfaces and debugging capabilities to overcome their limitations, such as processing vast amounts of data or understanding complex tool descriptions. The presentation emphasizes engineering lessons learned from building and deploying this tool, focusing on effectiveness, efficiency, discoverability, and trust.

This talk explores how to effectively guide AI agents when they interact with complex products like Superbase. It argues that while agents are capable of many tasks, they require specific guidance to handle novel situations, security protocols, and optimized workflows. The presentation introduces the concept of "skills" as a method to provide this guidance, demonstrating how they improve agent performance and safety, particularly when integrated with tool-calling capabilities.