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Go from an empty folder to a fully deployed AI agent using only natural language. This video introduces “vibe coding,” a powerful technique to build applications from scratch using the Gemini CLI.
Follow along with Sita and Amit as they demonstrate how to scaffold a new AI agent with the Agent Development Kit (ADK) in plain English. You’ll then learn “Context Engineering,” the secret sauce for moving your agent from a prototype to production. See how to provide documentation, coding standards, and feature requirements to guide the AI in generating high-quality, maintainable code.
Finally, watch as they deploy the entire agent to Google Cloud Run with a single command.
Stick around for the “Eng Talk” segment, where Amit and Sita answer top community questions:
– Is RAG obsolete with million-token context windows?
– How do you manage context overload?
– What metrics should you use to track context retrieval?
– What are the best tips for token optimization?
Chapters:
0:00 – Introduction
0:34 – Core Concepts
3:39 – Setting up Gemini CLI in VS Code
5:05 – Loading ADK Documentation for the Agent
7:03 – Vibe coding an Expense Tracker from Scratch
11:36 – Refactoring Code into Tools and Models
16:10 – Debugging Python code with Gemini CLI
25:15 – Why You Need Context Engineering
26:36 – Creating Context Files: Gemini.md, PRD, & Summary
32:02 – Building Advanced Features with Context Engineering
35:52 – Preparing for Cloud Run Deployment (Docker & Server)
37:44 – One-Command Deploy to Google Cloud Run
39:30 – Recap
40:48 – Community questions
45:55 – Resources
Resources:
Learn more about the Agent Development Kit → https://google.github.io/adk-docs/
Install the Gemini CLI → https://github.com/google-gemini/gemini-cli
Code from this tutorial → https://github.com/amitkmaraj/expense-tracker-agent
A2A Protocol official site → https://a2a-protocol.org/latest/
Subscribe to Google for Developers → https://goo.gle/developers
Products mentioned: Google ADK, Gemini CLI, Google AI Read More Google for Developers
