GitHub

The Complete Guide to WebMCP — Tara Agyemang, Google Chrome

Jun 11, 2026 · 21:34

Tara Agyemang from the Google Chrome team introduces WebMCP, a proposed web standard that replaces brittle DOM scraping with structured tools for AI agents. She explains two implementation paths: the declarative API (adding HTML attributes to forms) and the imperative API (registering custom JavaScript tools). A live demo shows a concert ticket purchase completed in three tool calls: search, open page, purchase. WebMCP is in early preview on Chrome 146, with an eval CLI and inspector extension available for testing.

Your Attention Is the Bottleneck, Not Your Agents — Zack Proser, WorkOS

Jun 11, 2026 · 25:17

Zack Proser from WorkOS argues that human attention, not agent speed, is the real bottleneck in AI-assisted coding. He proposes a sustainable stack: signal layers to filter Slack and Linear, voice-first flows at 184 wpm, remote control of agents from a phone to leverage diffuse thinking, and weekly self-improvement passes over JSONL conversation history. He also integrates an Oura ring via MCP so Claude can nudge him about sleep, emphasizing balance over burnout.

Self Driving Products: Product Signals to Pull Requests — Joshua Snyder, PostHog

Jun 10, 2026 · 15:39

Joshua Snyder of PostHog explains how they're building a pipeline that turns product signals—errors, Slack messages, session replays—into automated pull requests. He reveals that off-the-shelf embedding models cluster signals by structural similarity, so they embed LLM-generated queries instead. He argues specificity determines whether the agent produces a useful PR, with error tracking being immediately actionable while Slack and replay usually are not. He advises starting with costly agents to discover patterns, then collapsing expensive steps into one-shot calls.