A real game changer
- Tomer Shulner
- 7 בינו׳
- זמן קריאה 2 דקות
A One-Hour Game: Inside the Generative AI Revolution at “Game Changers”
I came into Reichman’s “Game Changers” special program expecting to learn about gaming and innovation, but nothing could have prepared me for what I witnessed in Mr. David Kalmanson’s course “Tech, data and AI in Gaming”. The challenge was simple yet bold: clone the core mechanics of classic 2D games, but instead of weeks or months, we had just one hour.
The tool? Google AI Studio, powered by large language models like Gemini.
The result was nothing short of a paradigm shift.
From Concept to Code in 60 Minutes
The speed achieved during the lesson wasn’t a product of rushed, sloppy work. It was a testament to how conversational AI has become a collaborator in the development pipeline. Traditionally, creating a 2D game, even a simple one like Snake or a short platformer, requires a lot of manual effort: hand-drawing or importing sprites, defining physics, coding game loops, and debugging collision detection. (Anyone who did the Nand2Tetris course by Prof. Shimon Schocken would know)
Using the AI tools, this entire process was compressed into a series of refined prompts. The model didn't just write code; it served as a content generator.
We were able to:
Generate Assets: Request background art, player animations and components textures based on a simple style description.
Define Logic: Describe the game's rules ("The player jumps when the space bar is pressed, and collision with a red block ends the game").
Synthesize Code: Receive runnable, commented code structures (HTML, CSS, JavaScript) that instantly brought the concept to life.
This hands-on experiment was far more than a fun exercise, it was a front-row seat to the future of game development.
The True Power of Generative AI
The technological emphasis of the lesson was clear: AI today possesses genuinely revolutionary abilities. We weren't just using a smart text editor; we were leveraging a foundation model that understands creative context, translates natural language into logical programming structure, and generates artistic assets on demand.
The days of needing vast resources and months of grinding labor for prototyping are over. Generative AI allows small teams and independent creators to iterate at speed, turning "what if" ideas into demonstrable experiences in a single afternoon.
This shift moves the developer's role from being a laborer writing every line, to being a prompt engineer and creative director—guiding the AI, refining its output, and focusing on the core experience rather than the repetitive technical requirements.
After witnessing David Kalmanson’s lesson, it's clear that the ability to effectively collaborate with AI is not just a desirable skill—it is the new baseline for innovation. The future of creative technology is conversational, and the speed at which we can now build is, quite frankly, crazy.
To wrap things up, we held a short competition for the best game created. Below are the top three entries — and for context, the top two weren’t made by CS students!
1st place — Daniel Sagiv
Third-year Business and Entrepreneurship student
2nd place - Nicole Karlin
Third-year Communication student
3rd place - Orine Bason
Third-year CS and Entrepreneurship student
Learn more about the “Game Changers” program at the link below
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