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GameForge AI

LiveTeam of 4

Describe a game in plain English; a multi-agent pipeline generates a playable one in the browser.

GameForge Studio showing a generated brick-breaker game running in the preview, with the agent chat on the left

Short silent clip of a generated game running. Loads only when you press play.

1The problem

People who are not programmers cannot turn a game idea into something playable. GameForge AI takes a plain-English description and produces a 2D browser game.

2My role

  • Backend and multi-agent AI orchestration; 25 of 61 commits in a teammate's repository.
  • Areas I worked on: the spec, asset-mapper, coder and debug agents, the multi-provider LLM fallback, the Kenney asset pipeline, the Supabase schema and generation stability.

My three teammates worked on the rest of the product. The code lives in a teammate's repository (devinfebrian/GameForge), so I link it as the team repo, not mine.

3Approach

A prompt goes to /api/generate, which streams progress over SSE while a pipeline runs: the spec agent writes a game requirements document, the asset mapper matches entities and sounds to curated CC0 Kenney assets or procedural sound presets, and the coder agent writes a short Phaser 4 scene.

Results are stored in Supabase, previewed in an isolated sandbox and published at a play URL. A debug agent can repair runtime errors. The highlighted boxes in the diagram are the orchestration I worked on.

Prompt (Studio UI)/api/generate (SSE stream)MY PART: ORCHESTRATION1 Spec agent: game PRD2 Asset mapper: Kenney + jsfxr3 Coder agent: Phaser 4 sceneSupabasegame_versionsSandboxed previewisolated iframe/play/[slug]Debug agentruntime error, repairProvider fallback across all agentsClaude, OpenAI, Gemini, Groq
Pipeline redrawn from the team repository README. Highlighted: the orchestration I worked on.

4Decisions and trade-offs

Provider fallback across all agents

The admin panel can route all four agents through Claude, OpenAI, Gemini or Groq, with automatic failover, so one failing model does not stop a generation.

Four agents with narrow jobs

Spec, asset mapping, coding and debugging are separate agents. The coder agent writes short Phaser 4 scene code (typically under 200 lines, per the repo README) on top of a pre-injected engine layer instead of writing physics from scratch.

What I would change, and what is still in progress

GameForge AI still needs improvement. It works end to end and I am happy with what a team of four delivered in two weeks, but I do not consider it finished. The agent orchestration is the part I would keep improving first. I have not listed specific fixes here because I have not scoped them yet and do not want to guess.

5Results

  • Live app: game-forge-rho.vercel.app (sign-up required to generate).
  • The team repository reports 430+ automated tests for the whole project.
  • Delivered in a 2-week remote sprint with a team of 4.
  • The screens below come from a local build of the team app; the short clip is silent and plays only when you press play.

6Screens

GameForge Studio showing a generated brick-breaker game running in the preview, with the agent chat on the left
A generated brick-breaker running in the Studio preview. Captured from a local build of the team app.
GameForge Studio start screen with four starter ideas and a prompt box
Studio start screen: describe a game or pick a starter idea.
Generation plan in progress: spec step done, asset mapping and coder steps running, with the synthesized game architecture shown
The agent pipeline at work: spec, assets, coder.
A generated endless-runner game in the preview with score, lives and distance, next to the agent chat
A second generated game: an endless runner.
GameForge landing page: 'Turn any idea into a playable game in seconds' with a three-step how-it-works section
Landing page of the product.

7What I learned and what is next

Working in a teammate's repository on a two-week clock meant agreeing on interfaces first and keeping my changes small and reviewable.

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