A product discussed on AI Engineer.

Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google
Jun 5, 2026 · 22:38
Michael Hablich, product manager for Chrome DevTools at Google, presents four engineering lessons from building agent interfaces, centered on the Chrome DevTools MCP server. He introduces the metric 'tokens per successful outcome' to measure interface fuel efficiency, contrasting it with raw JSON trace files that blew through context windows. The team improved error messages, like adding 'Cannot navigate back, no previous page in history' to enable agent self-healing without human intervention. They decomposed a monolithic `debug_webpage` tool into 25 focused tools, but then faced a discoverability problem solved by auditing tool descriptions for intent. Hablich defends keeping autoconnect friction to prevent prompt injection, citing the 'lethal trifecta' of agents with tool access, data access, and internet access, and outlines three security tiers for browsing agents.

Your Coding Agent Just Got Cloned And Your Brain Isn't Ready - Rustin Banks, Google Jules
Jul 25, 2025 · 13:40
Rustin Banks, an AI product manager at Google Labs, shares how Jules, Google's asynchronous coding agent powered by Gemini 2.5 Pro, enables developers to shift from sequential coding to orchestrating many parallel agents. He demonstrates real-world use on a conference schedule website, adding tests with Jest and Playwright simultaneously, implementing features like Google Calendar integration and AI summaries, and running accessibility audits. Banks argues that success requires clear verification criteria, creating 'disagreement' with agents to ensure correctness, and a robust merge/test framework. He notes that in its first two weeks, Jules generated 40,000 public commits, and emphasizes that agents-as-a-service in the cloud allow infinite scalability and development from any device.
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