All the talk about AI generated javascript games got lions wondering if more of a starship racing game could be automated.  The trend has been abandoning natural language & using novel prompt languages to describe programs. The compiler is the large language model & the prompt language is more optimized for describing a program than natural language while being higher level than a programming language.  The mane problem is standardizing on a prompt language.  There's an example game written in a prompt programming language:

https://x.com/nobody_qwert/status/1893584330095509843

Develop a web-based 3D game demo that features a procedurally generated maze and a soldier character with smooth movement and proper orientation. Follow these specifications:

- **Libraries & Dependencies:**
  - **Three.js (r128):** Use Three.js (version r128) via a CDN, for example, [cdnjs](https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js).
  - **GLTFLoader:** Load the 3D soldier model using GLTFLoader from [jsDelivr](https://cdn.jsdelivr.net/npm/three@0.128.0/examples/js/loaders/GLTFLoader.js).
  - **OrbitControls:** Implement camera control with OrbitControls from [jsDelivr](https://cdn.jsdelivr.net/npm/three@0.128.0/examples/js/controls/OrbitControls.js).

- **Scene Setup:**
  - Create a Three.js scene with a perspective camera.
  - Set up a WebGL renderer to cover the entire browser window.
  - Include lighting (e.g., HemisphereLight and DirectionalLight) to properly illuminate the scene.
  - Add a debug overlay (an HTML element) that shows real-time data like the soldier’s position and rotation.

- **Maze Generation:**
  - Build a 16×16 grid maze with each cell sized 4 units.
  - Always mark the outer boundary cells as walls.
  - Reserve a central open area (for example, cells 6–9 on both axes) without walls.
  - Randomly place walls in the remaining cells with a 15% chance.
  - Create procedural textures using canvas:
    - **Floor Texture:** A texture with a brown tone and grid lines.
    - **Wall Texture:** A texture with a base color and randomized patterns.

- **Wall & Collision Setup:**
  - For each wall cell, create a box geometry mesh sized to match the cell dimensions and add it to the scene.
  - Compute bounding boxes for each wall to facilitate collision detection.
  - Implement collision detection by checking if the soldier’s position (using a collision radius) intersects any wall’s bounding box.

- **Soldier Character & Animations:**
  - Load the soldier model from [https://threejs.org/examples/models/gltf/Soldier.glb](https://threejs.org/examples/models/gltf/Soldier.glb) using GLTFLoader.
  - Scale and position the soldier within the open area of the maze.
  - Set up an AnimationMixer for the soldier with at least two actions:
    - **Idle Animation:** Plays when no movement keys are pressed.
    - **Run Animation:** Activates when the soldier is moving.
  - Smoothly transition between animations using fade-in and fade-out techniques.

- **Movement & Controls:**
  - Implement WASD keyboard controls for moving the soldier.
  - Calculate movement direction using the camera’s forward (XZ-plane) and left vectors.
  - **Rotation Fix:** To ensure the soldier faces the direction of movement, compute the angle with:
    ```js
    const angle = Math.atan2(moveDirection.x, moveDirection.z);
    soldier.rotation.y = angle + Math.PI;
    ```
    This adjustment (adding π) is crucial for the correct orientation of the character.
  - Update the OrbitControls target to follow the soldier, keeping the character centered on screen.

- **Responsive Design:**
  - Handle window resize events to update the camera’s aspect ratio and the renderer’s size.

- **Animation Loop:**
  - Create a main animation loop that:
    - Updates the AnimationMixer.
    - Processes soldier movement and collision detection.
    - Updates the debug overlay.
    - Renders the scene continuously.

The result is trash but some of the physics modeling shows promise.

With a simple grok prompt

Develop a web-based 3D game demo that features a rocket that drives like a car down a 2D track in space.  It drifts when turning.

 The result is a turd that doesn't do anything.

What we're seeing on AI twitter is manely the result of preprogrammed libraries that were developed by animals with a very focused investment in prompt development.