Episode 3 of the AI Agent Bake Off: 'Build a GTM Agent for Founders'

Source: Dev.to

The Prompt

Using #Gemini and #ADK build a GTM Agent for Founders that is both MultiModel (beyond text) and MultiAgent (not just an AI wrapper).

The Setup

And that is what our three teams signed up for — 1 developer, 1 Googler, an AI Studio API Key, and Google’s Agent Development Kit (ADK).

The Knowledge Base

We also provided them with a Go‑To‑Market open‑source repo to give them a head‑start:

https://github.com/goabego/ai-gtm-playbook

And that’s all we gave them (okay, also lunch and plenty of coffee). The learnings were bountiful: from context‑stuffing best practices to quick A2A deployments (more on that later).

What will you see in this episode?

We structured the video in three parts: Day of challenge, Demos, and Judges deliberation.

The Day Challenge

On the day of shooting we surprised our teams with a mini 2‑hour hackathon to push their agents to the limit with six distinct tests—whoever completed the most wins the challenge.

Full challenge details: https://gist.github.com/goabego/d7e3ff6897c6891f315030cdbda80ec5

The Demos

Next you will see the details of the teams building their AI agents using ADK. You will learn about ADK Web, Gemini, sub‑agent architectures, tactics to manage context, and more. Below is an example of one team’s architecture diagram (all open source and available below).

The Judges

Perhaps the favorite part was the Q&A between the judges and our teams. In this episode we had Ivan (AI DevRel at Google Cloud), Shubham (AI Product Manager @ Google Cloud), and Annie (AI DevRel at Google Cloud). They asked questions, shared thoughts, and selected a winner.

Want a more interactive viewing experience?

We created an even more educational experience with cards, code snippets, and useful links. Try it out here: ai-agent-bakeoff.com – you can ask questions and we will answer. We also added the open‑source content there for easier learning.

All contestants’ source code and architecture diagrams are available in the first card on the web app.

Key Learnings in the WebApp

In the WebApp we dive deeper into the following insights from the game show, including but not limited to:

• Build standardized MCP servers using Python and Google’s ADK.
• Implement discovery and execution handlers for seamless tool integration.
• Connect agents to enterprise databases using the MCP Toolbox.
• Enable collaboration between different AI frameworks using A2A.
• Harness Gemini 3 Pro for advanced multimodal agent reasoning.
• Deploy agents to production via Vertex AI and GKE.
• Rapidly prototype and visualize agent flows using ADK Web.
• Scale adoption using the open‑source AI GTM playbook.
• Optimize performance by using sub‑agents to bypass context rot.