---
title: "Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google"
url: https://daily.dev/posts/building-agent-interfaces-lessons-from-chrome-devtools-mcp-for-agents-michael-hablich-google-v9gqworuu
source_url: https://www.youtube.com/watch?v=_B4Pv9ttFgY
type: video:youtube
source: "AI Engineer"
published: 2026-06-05T17:26:47.764Z
updated: 2026-06-07T17:44:58.978Z
tags: ["automation", "ai-agents", "google-chrome", "mcp", "prompt-engineering"]
reading_time: 22
upvotes: 1
comments: 0
language: en
---

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# Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google

**[AI Engineer](https://daily.dev/sources/aidotengineer)** · 22 min read · 1 upvotes · 0 comments

## Summary

Michael Hablich, Chrome DevTools PM at Google, shares four engineering lessons from building Chrome DevTools for AI agents via MCP. Key insights include: treating agents as a distinct user class with different cognitive bottlenecks than humans; measuring interface efficiency using 'tokens per successful outcome'; returning semantic summaries instead of raw data to avoid blowing context windows; decomposing monolithic tools into granular ones with clear descriptions; implementing error recovery playbooks and proactive detours for agent self-healing; and maintaining deliberate trust boundaries (friction by design) to prevent prompt injection and unauthorized access across three tiers of agent deployment environments.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=_B4Pv9ttFgY>

## Similar posts on daily.dev

- [Chrome DevTools for agents](https://daily.dev/posts/chrome-devtools-for-agents-i2pxfjajj) · iO tech\_hub · 1 upvotes · 0 comments

---

Tags: [#automation](https://daily.dev/tags/automation), [#ai-agents](https://daily.dev/tags/ai-agents), [#google-chrome](https://daily.dev/tags/google-chrome), [#mcp](https://daily.dev/tags/mcp), [#prompt-engineering](https://daily.dev/tags/prompt-engineering)

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