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Battle Drones game
First published on
on games, gamedev

I came across this post on Simon Willison’s blog, where he writes about a game he developed with the help of Claude Code. The game is entirely vibe-coded. It’s incredible how capable AI models have become at creating these kinds of games.

The game is really impressive, though not perfect. It makes me wonder whether it’s really worth investing time in learning game development when AI can already do it on its own.

simonwillison.net

simonwillison.net

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Mulberry32 algorithm
First published on
on programming, tech, gamedev

I’ve wanted to explore game development for a while, and these days it’s much easier with AI. However, my goal has never been to create a game as such (even if that might seem like the ultimate objective), but to learn all the concepts and techniques involved in game development. So a few weeks ago, I started building a proof of concept: a video game based on the legendary FreeCiv, which I’ve named MicroCiv.

FreeCiv is a turn-based strategy game that lets you develop and manage a civilization from its beginnings until it becomes a world power, competing against other players or artificial intelligence on a procedurally generated map.

One important aspect of games like this is randomness, which lets us generate different parts of the game at random (maps, biomes, structures, and so on). However, we need some determinism within that randomness: we need to be able to reproduce the exact same sequence of random numbers from the same seed. That’s where Mulberry32 really shines.

Mulberry32 is a deterministic 32-bit pseudo-random number generator (PRNG). Deterministic means that the entire sequence of numbers it produces is fully determined by its initial state, commonly called the seed.

class Mulberry32 {
  constructor(seed) {
    this.seed = seed >>> 0;
  }

  next() {
    let t = (this.seed += 0x6d2b79f5);
    t = Math.imul(t ^ (t >>> 15), t | 1);
    t ^= t + Math.imul(t ^ (t >>> 7), t | 61);
    return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
  }
}

Basic implementation of Mulberry32

In my current implementation, I’m using it for the procedural generation of a basic 2D map.

In the previous map, the different colors correspond to terrain types according to the following relationship:

const TERRAIN_COLORS: Record<TerrainId, string> = {
  OCEAN: "#2f79a8", // Blue
  GRASSLAND: "#7fad4b", // Green
  FOREST: "#28674a", // Dark Green
  MOUNTAINS: "#85817a", // Gray
};

If you’d like to learn more about how this algorithm works internally, here are some excellent links that explain it in detail, step by step.

My Game development intro
First published on
on gamedev, games, javascript

Since a long time ago I’ve wanted to start developing a game, and now that my 7 years old kid asked for a game as his next birthday I think is a good time to start. I have no problem learning a new language like Python, C# or Rust, but as a web developer I wanted to start by using my main programming language, Javascript.

So, to start learning (and to get my hands dirty), I want to replicate the game made by Drew Conley Build a Multiplayer Game with JavaScript & Firebase.

More coming soon…