I built a team of AI Agents with Nano Banana (it’s I-N-S-A-N-E)

About this video

• Video Title: I built a team of AI Agents with Nano Banana (it’s I-N-S-A-N-E)
• Channel: David Ondrej
• Speakers: David Andre
• Duration: 00:30:31

Overview

This video demonstrates how to build and utilize a team of AI agents powered by Google's Nano Banana model. The presenter, David Andre, highlights Nano Banana's advanced image editing capabilities, its foundation on Gemini, and its potential for creating multi-agent systems. The tutorial covers setting up a development environment, generating images, implementing multi-image support with a Flask app, and debugging common errors, ultimately showcasing a functional application for image generation and editing.

Key takeaways

• Nano Banana's Capabilities: Nano Banana (Google Gemini 2.5 Flash image preview) is presented as a groundbreaking AI model excelling in image editing with high consistency and reliability, going beyond simple image generation.
• Multi-Agent Systems: The core opportunity lies in building multi-agent systems where each agent is powered by Nano Banana, enabling complex workflows and applications.
• Development Environment Setup: The video provides a step-by-step guide using Cloud Code, including setting up environment variables, installing dependencies, and managing Python environments with Conda.
• Iterative Development & Debugging: The presenter emphasizes an iterative approach to AI development, breaking down projects into smaller stages and using AI agents (like Cloud Code and Codex) to debug errors and improve the codebase.
• Free Access and Cost: The video explains how to use Nano Banana for free via OpenRouter and discusses the low cost of the paid API, making advanced AI image generation accessible.
• Application Showcase: A functional application is built, demonstrating image generation from prompts, multi-image variations, and image editing, culminating in a visual tree-like UI for managing image assets.