Retro Snake Game in Python A retro Snake game built in Python using Google Antigravity and Gemini 3 Pro as an AI “junior dev team”. This repo turns a classic beginner-friendly game into a hands-on demo of agentic development and AI-assisted coding workflows.​​

Features Classic Snake gameplay with growing body, food pickups, and game-over on collision.​

Clean, beginner-friendly Python code that you can read, tweak, and extend.

Built end-to-end inside the Antigravity IDE using natural-language prompts to generate and iterate on the game logic.​​

Great starting point if you want to experiment with AI-assisted development or add your own mechanics (scoreboard, levels, power-ups, etc.).​

Tech stack Language: Python

Environment: Google Antigravity (agentic IDE) with Gemini 3 Pro as the main model.​​

Focus: Simple game loop, input handling, collision detection, and basic rendering logic.

Getting started Clone this repository:

git clone https://github.com/mafazr/snakegame.git

Open the project in your preferred editor or in Antigravity.

Install any required Python dependencies (see requirements.txt if present).

Run the main script, for example:

python snake.py

Once the window opens, use the arrow keys (or your configured controls) to move the snake and try to survive as long as possible.

To Play the game : Simply go to the dist folder and get the exe file and you are good to go!

How this project was built This project was created as part of an experiment: using Antigravity’s agent mode plus Gemini 3 Pro to generate most of the boilerplate and iterate on the game via prompts instead of manual coding. The full step-by-step walkthrough, including prompts, screenshots, and lessons learned, is documented in the accompanying Substack tutorial linked from this repo description.​​

Ideas for extension Add a visible score and high-score tracking.

Increase difficulty as the snake grows (speed, obstacles, or shrinking play area).​

Refactor the code into smaller modules to explore cleaner architecture patterns.

Hook this into your own AI workflows (e.g., prompt the model to add new features or refactor functions).

License This project is shared for learning and experimentation. Please respect all applicable licenses and intellectual property when reusing code, assets, or tutorial content.