🚀 From Napkin Sketch to data-driven real-estate advisor Agent in Under 40 Minutes? 🚀
Can a coding agent really work autonomously on complicated problems without human intervention? I decided to put Google’s new Antigravity 2.0 and Gemini 3.5 to the test: The Napkin Challenge. 📝
The goal: Build and deploy a real estate investment advisor - based on real-world data, starting with nothing but a rough sketch on a napkin.
The Result? With the right context, yes!
I used:
Antigravity 2.0 & Gemini 3.5: Architect and execute the plan
Agent CLI Skills: Scaffold, build, test and evaluate the agent using ADK.3
Developer Knowledge MCP: Provided necessary context to connect to BigQuery MCP and integrate the census dataset for grounded investment advice.
Parallelized Workflow using sub-agents: While the system ran the evaluation suite, it simultaneously deployed the agent to Cloud Run.
The Outcome:
The "Napkin Challenge" proves that when you combine the right context with powerful models, the barrier between an idea and a deployed product has virtually disappeared.
I challenge you: What is your "napkin" project? Try it with Antigravity 2.0 and Gemini 3.5. 📝
🚀 How to join the challenge -