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💫 I forced 4 AIs to recreate Mario from scratch using Symfony AI and Godot

on May 8, 2026

Creating a video game with artificial intelligence has become almost commonplace.

Today, all you need to do is open Cursor, Claude Code or ChatGPT and type:

“Create me a Mario.”

And a few minutes later, something appears on the screen.

But behind this apparent simplicity lies a much more interesting problem:

How ​​to properly orchestrate multiple AI agents to produce a coherent, playable, and maintainable result?

That's precisely what I wanted to experiment with in this video:

  • ChatGPT
  • Claude
  • Gemini
  • Grok

Even prompt. Same objective. Completely different results.

But above all: a completely different architecture from what is called “vibe coding” today.

An inspiration from Playdate

Before even talking about AI, we need to talk about video games.

In the video, I quickly show the Playdate, a small independent console developed by Panic with a black and white screen and a mechanical crank.

What's interesting about the Playdate isn't the power.

That's the philosophy.

The equipment imposes constraints:

  • limited screen
  • minimalist controls
  • simple gameplay
  • maximum creativity

And paradoxically, these constraints make the games more interesting.

It's exactly the same phenomenon with AI agents.

A vague prompt often results in a fragile system.

Well-defined constraints produce much more consistent results.

The Single Prompt Problem

Most AI demonstrations work like this:

Create a Mario game

The model then attempts to:

  • generate the gameplay
  • handle collisions
  • create the graphics
  • balance the levels
  • produce the mechanics
  • organize the project

The result is often impressive for a few seconds.

Then appear:

  • broken collisions
  • impossible levels
  • inconsistent rules
  • contradictory mechanisms
  • an immediate technical debt

The problem is not necessarily AI.

The problem is that he is being asked to do everything simultaneously without specialization.

Symfony AI + Godot

For this experiment, I used two main technologies:

Symfony AI

Symfony AI

Symfony AI provides:

  • the agents
  • the tools
  • multimodal
  • the RAG
  • memory
  • multi-agent orchestration

The framework is divided into several specialized bundles:

  • Agent
  • Store
  • AI Bundle
  • Platform
  • App

The goal is to build a clean architecture around AI models rather than simply sending prompts.

Godot

Godot Engine

Godot is an open-source game engine extremely well-suited for rapid prototyping:

  • 2D
  • 3D
  • scene system
  • GDScript scripting
  • nodal architecture
  • multi-platform export

The idea was simple:

Orchestrate AI agents with Symfony AI to automatically generate a Godot game.

Multi-agent orchestration

The core of the project is based on a multi-agent architecture.

Instead of having a single AI that does everything, I separated the responsibilities.

The Orchestrator

The orchestrator receives the main prompt:

Generate a Mario-like platformer

Then it automatically delegates to the appropriate specialized agents.

Specialized agents

Layout Agent

The “level designer”.

It generates:

  • the platforms
  • the holes
  • the pipes
  • the stairs
  • the progression of the level

Gameplay Agent

The mechanics specialist.

He manages:

  • collisions
  • the enemies
  • the bonuses
  • the jumps
  • the checkpoints
  • the interactions

Godot Export Agent

The role of this agent is to transform the generated data into structures compatible with Godot:

  • scenes
  • TileMaps
  • objects
  • JSON exports

QA Agent

The most important thing.

The QA Agent verifies:

  • the gameplay
  • collisions
  • impossible jumps
  • the consistency of the mechanics
  • the rules of the level

This is probably the element most lacking in “vibe coding” demos.

The orchestration with Darkwood Flow and Navi

To orchestrate all of this, I use:

  • Darkwood Flow
  • Darkwood Navi

Flow allows you to manage the execution of multi-agent workflows.

Navi allows:

  • traceability
  • observability
  • routing
  • monitoring of executions

The pipeline looks like this:

User Prompt
    ↓
Orchestrator
    ↓
Layout Agent
Gameplay Agent
Godot Export Agent
QA Agent
    ↓
Generated Game

The orchestrator automatically chooses which agent should intervene depending on the progress of the system.

A single Symfony command

The entire generation process is launched with a simple Symfony command:

php bin/console app:mario:orchestrate

This order:

  1. calls the orchestrator
  2. Route to the specialist agents
  3. generates the result
  4. Automatically exports the game

The most interesting thing: The pipeline becomes reproducible.

The results

ChatGPT

ChatGPT produces a very good database quickly.

We find:

  • a faithful structure
  • consistent gameplay
  • a rapid iteration

The result is strongly reminiscent of the old Mario Game Boy games.

The main advantage: the speed of prototyping.

Claude

Claude produces something more graphically detailed.

The activities:

  • are more fluid
  • more modern
  • sometimes more ambitious

The reasoning seems more structured.

But we also feel more creative freedom compared to remaining faithful to the original.

Gemini

Gemini is probably the most visually interesting.

We find:

  • more modern graphics
  • better art direction
  • greater inventiveness

The gameplay also seems more refined in certain aspects.

There's a more "Nintendo-like" approach.

Grok

Grok is the most unpredictable.

He takes more initiative:

  • level selection
  • scoring system
  • graphic variations
  • new gameplay approaches

But it also deviates further from the original Mario.

The real subject is not Mario

This project was ultimately just a pretext.

The real issue lies elsewhere:

The future of AI development lies in orchestration.

A single agent can produce a prototype.

But several specialized agents can produce:

  • systems
  • pipelines
  • workflows
  • coherent architectures

And most importantly: reproducible results.

The future of vibe coding

Current “vibe coding” often relies on:

  • a huge prompt
  • a single AI
  • many hallucinations
  • little validation

The next step is probably:

  • specialized agents
  • explicit constraints
  • tests
  • QA loops
  • observability
  • of the orchestration

In other words:

The future of vibe coding is orchestration.

Source code

  • Matyo91: matyo91/mario-orquestration: https://github.com/matyo91/mario-orquestration
  • ChatGPT: yoloyee1/SMB-clone-made-by-Godot: https://github.com/yoloyee1/SMB-clone-made-by-Godot
  • Claude: Axelrpg/Super-Mario-Bros-Godot: https://github.com/Axelrpg/Super-Mario-Bros-Godot
  • Gemini: charpurrr/SuperMarioSolarEngine: https://github.com/charpurrr/SuperMarioSolarEngine
  • Grok: wchen02/platformer: https://github.com/wchen02/platformer

Resources

  • Presentation slides: https://github.com/matyo91/slidewire
  • Symfony Multiagent: https://github.com/symfony/ai/blob/main/examples/multi-agent/orchestrator.php
  • Symfony AI
  • Godot Engine
  • Playdate

Related Links

  • AgentCraft: The Orc at the Heart of the Orchestration — Ido Salomon: https://www.youtube.com/watch?v=kR64LOqBBCU
  • Learn JavaScript by building Mario! (Super simple!): https://www.youtube.com/watch?v=VNs96uQoetw
  • I created an AI that plays Mario all by itself: https://m.youtube.com/watch?v=F63GNXGHVwM&feature=youtu.be
  • understand the code that the AI ​​produces for: https://www.linkedin.com/posts/thierry-templier-7ba726_%C3%A0-l%C3%A8re-de-claude-code-g%C3%A9n%C3%A9rer-200-000-lignes-share-7457029437134512129-CSJb?utm_source=share&utm_medium=member_ios&rcm=ACoAAA2M-8wBB-yYv6qd4pdeoz3fTBIAhu6HQH8
  • Nakiros 0.9.0 — audit your entire .claude/ directory with specialized AI agents: https://www.linkedin.com/posts/thomasailleaume_claudecode-ai-devtools-share-7457340449356144640-bWe6?utm_source=share&utm_medium=member_ios&rcm=ACoAAA2M-8wBB-yYv6qd4pdeoz3fTBIAhu6HQH8
  • I Built a GAME OF KAREN with Genspark AI + GitHub (And Made Expensive Mistakes 😅): https://www.youtube.com/watch?v=fI9Z1-SPfaI
  • Text-to-Level Diffusion Models With Various Text Encoders for Super Mario Bros: https://arxiv.org/pdf/2507.00184
  • NVIDIA's New AI Turns One Photo Into A World That Never Breaks: https://youtu.be/eCw33snvoNI?is=7KOOQzRpbPXPBtFl

Links of the week

  • LIVE 1/5 LIBERTY WEBI OPEN HOUSE - THE AI SHORTCUT: https://www.youtube.com/live/L0H-rgqf7zI?is=1mc0YgZAxwjABKay
  • Eve of the week of May 4, 2026 Guillaume Loulier: https://guikingone.substack.com/p/veille-de-la-semaine-du-4-mai-2026
  • How MrBeast Works 18 Hours Per Day https://youtu.be/wPeUb2SVmEc?is=psItbJ2YNJFjVHiq
  • Richest People in the World (1900-2026) - From Rockefeller to Musk: https://m.youtube.com/watch?v=5h_vKrHzRvg&is=M9gch9O_AuqDTiKe
  • Day 287 growing my SaaS startup to $1M: https://m.youtube.com/watch?v=7aQ01ZKysl8&is=tdQGj8GddnmVH5sQ
  • ANDREJ KARPATHY JUST DECLARED THE END OF PROGRAMMING AS YOU KNOW IT. https://x.com/neil_xbt/status/2049687182336541013?s=46
  • How France's biggest pirate site was taken down: https://youtu.be/ULTV6T6jRTw?is=F9k6GcMNll0IfjZo Japan has just made a major decision: https://youtu.be/n_Kfco-kuFY?is=TBrMM-XdMTeE0qGR
  • check: Remove use of subtyping for monads: https://github.com/Gabriella439/grace/pull/261
  • Agentic Search for Context Engineering — Leonie Monigatti, Elastic: https://www.youtube.com/watch?v=ynJyIKwjonM
  • FLUX, open research and the future of visual AI — Stephen Batifol, Black Forest Labs: https://www.youtube.com/watch?v=x8Yb4RidLgM
  • How the Transformers finally devoured vision – Isaac Robinson, Roboflow: https://www.youtube.com/watch?v=VhfAVA3BG2I
  • This 50-minute lecture by Jeff Bezos will teach you more about business than a 2-year MBA program: https://x.com/Alokkumarzz/status/2049882855170588755?s=20
  • This lecture from Massachusetts Institute of Technology breaks down wealth, compounding, and long-term thinking in a way most financial advice never does: https://x.com/allen_explains/status/2049857599919825252?s=46
  • Stanford just taught the entire thing in a 1-hour lecture. For Free. https://x.com/codewithimanshu/status/2051240758125252872?s=46
  • this 2-hour Stanford lecture on AI careers. It will teach you more about winning in the AI ​​race than all the AI ​​content you've scrolled past this year. https://x.com/radha_ai/status/2051617864617263397?s=46
  • Peter Thiel gave a 1-hour class on how to create a monopoly starting from 0. https://x.com/indutripat82427/status/2051709170618098065?s=12
  • In this 24-minute session, Cherny outlines a future that is already his daily reality: https://x.com/datachaz/status/2051770066912379309?s=12
  • Radha Tripathi on X: "Claude FULL COURSE 1 HOUR (Build & Automate Anything) https://t.co/gg81I06To0" /
  • A Stanford University lecture taught the way engineers are actually trained to think about AI systems. You understand the why, every prompt you write, every system you design, and every agent you build operates from a completely different mental model. https://x.com/cyrilxbt/status/2049690838972723503?s=46 -Sam Altman. Dustin Moskovitz. The first lecture of the most influential startup course ever recorded. https://x.com/neil_xbt/status/2050411454830907898?s=46
  • OpenAI's own engineers just showed how to actually use OpenAI Codex properly. https://x.com/heyzarakhan/status/2051357610222239745?s=46
  • How much of your project code was written by #AI? Whether to track coding agent adoption in engineering teams or security risks introduced by vibe coding, it's time to track what Claude/Cursor/Copilot/Codex do. https://usegitai.com/: https://www.linkedin.com/posts/fzaninotto_git-ai-track-ai-code-all-the-way-to-production-share-7450124640389263360-jhxu?utm_source=share&utm_medium=member_ios&rcm=ACoAAA2M-8wBB-yYv6qd4pdeoz3fTBIAhu6HQH8
  • practitioners' perspective: Takeaways based on a qualitative survey of 419 practitioners involved in workflow maintenance: https://dl.acm.org/doi/10.1145/3806833
  • In 14 minutes, this Anthropic engineer who created MCPs will teach you more about building them right than most developers figure out on their own in months https://x.com/Av1dlive/status/2051967150894772609?s=20
  • Star Wars: Episode 1 - Racer (Podracing) 100% Speedrun in 1:17:33 [World Record]: https://youtu.be/OWv69snqBFs?is=kNL8iJzzGVRL3hRl
  • In 2007, Elon Musk Predicted Everything: https://youtu.be/xyCOvT1Y5YQ?is=igUlB5wqAuX1qbRs

🎶 Music credit

  • Questo trend è mio! ⭐️ : https://www.tiktok.com/@maya_cianflone/video/7607524440364289302
@maya_cianflone

Questo trend è mio! ⭐️

♬ original sound - smb.0685

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