Uploaded August 2026 | Updated September 2026, 3 weeks ago
Join Gemini Enterprise Agent Ready (GEAR) for the latest agent resources here. β https://goo.gle/3Srblgl
Access the source code on GitHub β https://goo.gle/4g8TC5t
AI agents are becoming major consumers of the web, but today's websites are built for humans, not machines. WebMCP changes that. In this video, Hugo Zanini, a Google Developer Expert in AI, shows how to expose typed tools directly inside web pages so AI agents can act reliably, quickly, and at a fraction of the token cost.
Watch along and learn:
* The agent shopping problem and why current approaches like screenshot-scraping fall short.
* How WebMCP works to expose contextual tools directly through simple browser APIs.
* A live demo of "Happy Coffee" (a React-based developer portal) showing Gemini in action searching catalogs and analyzing quality checks.
* WebMCP for Local Agents, demonstrating how local workflows can leverage web UIs to accelerate development.
Watch more How I built my agent β youtube.com/playlist?list=PLIivdWyY5sqLseBL8iUmVbdd_h30C4oEo
π Subscribe to Google Cloud Tech β https://goo.gle/GoogleCloudTech
Speaker: Hugo Zanini
Products Mentioned: WebMCP, React, Gemini
Join Gemini Enterprise Agent Ready (GEAR) for the latest agent resources here. β https://goo.gle/3Srblgl
Access the source code on GitHub β https://goo.gle/4g8TC5t
AI agents are becoming major consumers of the web, but today's websites are built for humans, not machines. WebMCP changes that. In this video, Hugo Zanini, a Google Developer Expert in AI, shows how to expose typed tools directly inside web pages so AI agents can act reliably, quickly, and at a fraction of the token cost.
Watch along and learn:
* The agent shopping problem and why current approaches like screenshot-scraping fall short.
* How WebMCP works to expose contextual tools directly through simple browser APIs.
* A live demo of "Happy Coffee" (a React-based developer portal) showing Gemini in action searching catalogs and analyzing quality checks.
* WebMCP for Local Agents, demonstrating how local workflows can leverage web UIs to accelerate development.
Watch more How I built my agent β youtube.com/playlist?list=PLIivdWyY5sqLseBL8iUmVbdd_h30C4oEo
π Subscribe to Google Cloud Tech β https://goo.gle/GoogleCloudTech
Speaker: Hugo Zanini
Products Mentioned: WebMCP, React, Gemini




![How to design a multi-agent system that skips the LLM
Github repo β https://goo.gle/race-condition
Previous episode β https://goo.gle/marathonagent
A thousand AI agents run a marathon, and almost none of them ever call the LLM.
In this multi-agent system deep dive, Casey West breaks down the one architectural decision behind Race Condition: a 1000-agent system built on Googles Agent Development Kit (ADK).
The question every AI engineer is wrestling with: when do you let an LLM decide, and when do you just write the code in a multiagent system? We trace one decision end to end, planning a marathon route, then show how the same idea (skip the LLM where you dont need it) scales to a thousand agents running on deterministic code.
What youll learn:
* When to use an LLM vs deterministic logic
* The before_model_callback trick, keep the agent, skip the model
* Why route planning is deterministic (NP-hard + the Spine & Sprout algorithm)
* How 1,000 autopilot runners make 0 LLM calls
* Where the tokens actually go (the AI decides, the code runs)
* Scaling 1,000 stateless sessions with Redis
Chapters
00:00 - Intro: 1,000 AI agents that dont call the LLM
00:41 - When should an agent use an LLM?
01:02 - [Demo] Planning a marathon route
01:59 - Why Google Maps cant route a marathon
05:08 - Why the LLM Is the wrong tool (NP-hard)
05:40 - The deterministic spine & sprout algorithm
06:58 - Using AI Studio to choose the algorithm
09:00 - The trick: Skip the LLM with a callback
12:26 - before_model_callback β the reveal
17:50 - Autopilot runners: 1,000 agents, 0 LLM calls
21:31 - How many tokens? Where they actually go
23:28 - The second cost: Session state & redis
29:05 - Wrap up
More resources:
Google Agent Development Kit (ADK) β https://goo.gle/3PItVzL
Google ADK Community (Redis session service) β https://goo.gle/4ugzmUw
Agent Runtime β https://goo.gle/4nXDhnX
Google Cloud Memory Store β https://goo.gle/4nXxBtT
Agent2Agent Protocol (A2A) protocol β https://goo.gle/4u5x8HF
Casey West on LinkedIn β https://goo.gle/4dXnsJr
Annie Wang on LinkedIn β https://goo.gle/43GCXAo
Watch more Hands on AI β https://www.youtube.com/playlist?list=PLIivdWyY5sqKnJOvP89yF8t9mWuzMTcbM
π Subscribe to Google Cloud Tech β https://goo.gle/GoogleCloudTech
#AIAgent #GoogleADK #Gemini #MultiAgentSystem #AgenticAI #GoogleCloud
Speakers: Casey West, Annie Wang
Products Mentioned: Google Agent Development Kit, Gemini API, Agent Runtime, Google Cloud Pub/Sub, AlloyDB, Agent2Agent Protocol How to design a multi-agent system that skips the LLM](https://i.ytimg.com/vi/Fzd0BWMH65s/mqdefault.jpg)





