AI agents and game development

By Eduardo Orellana · Updated

Flockbay is free on your own Claude or ChatGPT plan. Claude Pro or Max, or ChatGPT Plus or higher, builds a real Godot project in the Godot editor. Claude Free and ChatGPT Free do not run here. More models are optional, a credit reload at API prices. Windows today. The engine is the official Godot release. Agents are good at codebases that describe themselves. Game projects do not describe themselves, and that — rather than model quality — is why agentic game development mostly disappoints.

The disappointment has a cause

Agents got good at software fast. They are noticeably worse at games, and the usual explanation — games are harder — is not quite it. Plenty of game code is simpler than the web services agents handle daily.

The real difference is that a game project carries most of its meaning outside the code. What a scene is for, which node is the player, how the terrain relates to the water, what "the village" refers to: none of that is written anywhere an agent can read. It is in a person's head and in a set of conventions that were never stated. So the agent infers, and inference on missing context is where the confident, expensive mistakes come from.

Watch a long agent session on a bare game project and this is what you see. Not incompetence. A model reconstructing the world model from scratch every few turns and getting a slightly different answer each time.

Making the game legible instead of upgrading the model

There are two responses. One is to reach for a bigger model and hope it infers better. That works a little, costs a lot, and gets you a system whose reliability is somebody else's roadmap.

The other is to make the game legible — to give the agent operations at the level a game is actually described in, so there is less to invent. That is what Flockbay is: Godot underneath, and a capability layer on top that turns the parts a game is made of into things an agent can operate rather than files it must interpret. In a 3D world those parts are terrain, water, weather, sky and characters. In a flat one they are the tile ground, the band of scenery beyond it, the person, and the objects you place.

Every capability that exists is a chunk of code no model writes from nothing and a class of failure that stops happening. When the layer is good, a cheap model composes against it reliably, and the expensive one is only needed for taste and for getting out of trouble. That is a better cost structure and a steadier one.

Two paths, and no secret third one

Flockbay ships inside the app. You describe the behaviour you want, it writes GDScript into your project, and you play the result. Nothing to connect, nothing to maintain, and it is aimed at the capability layer already.

Or you bring your own agent. Flockbay ships one MCP server inside the desktop app, and an MCP-capable agent on your machine can drive it: the capability layer, the assets, and the game itself, which it can edit in the open Godot editor, run, look at and play. We have no bespoke integration with any agent product — no plugin, no extension, no listing. Both sides speak MCP. We have not tested every client and behaviour varies.

What does not exist is a third path where an agent quietly does everything. An agent writes the code and can call the world tools, you can shape the world by hand with the builder in the Godot editor, and you judge the result by playing it.

More on this: Making games with Ollama, and what that does not buy you

The person is not being removed from this

The builder is where a person places the world directly. Terrain, water, weather, buildings and characters in a 3D project; ground painted cell by cell, and sprites dropped, turned and sized, in a 2D one. That is the part where taste is the whole job and where describing a thing in a sentence is slower than doing it. Handing it to a model would be a worse product, not a more advanced one.

And the judgement stays with you. You play the game and say whether it is right. Not writing the code does not mean not having an opinion about the result — the opinion is the part you supply, and the agent revising after you say what is wrong is the normal loop rather than a sign something failed.

This is also why the pages promising an agent that produces a finished game from a paragraph tend not to survive contact with a real project. Somebody has to decide the game is good, and that somebody is playing it.

What it runs on, and what it costs

A desktop application for Windows, with Godot bundled inside it. Your project is a real Godot project in a folder on your disk. When you press play the game runs locally, at your machine's framerate — no streaming, no cloud rendering, no browser preview.

Building needs an internet connection, because the AI, asset generation and world data all come over the network. Playing what you built does not. There is no offline mode and we are not building one.

The platform is free: the whole world builder, using your own assets, plus play, playtesting and publishing. Flockbay is free on your own AI: your Claude or ChatGPT plan, your own agent, or an API key. Flockbay builds from a library of ready-made objects, or with Godot's own shapes. Connecting your own agent over MCP is free. There is no team or enterprise tier; it is a desktop app.

More on this: Roadmap: the direction, and the things we have ruled out

Questions

Why do AI agents struggle with game projects?
Because a game project carries most of its meaning outside the code, so the agent has to infer it, and inference on missing context is where confident mistakes come from.
Can an agent make an entire game for me?
Not on its own. An agent writes the code and can shape the world through the world tools. A person judges the game by playing it, fixes by hand what reads wrong, and says what to change.
Do I have to use Flockbay?
No. Flockbay ships in the app and is the shorter path, but an agent of your own can drive the same capability layer over MCP.
Do you integrate with specific agent tools?
No. Flockbay ships one MCP server and any MCP-capable client should be able to reach it. We have not tested every one.
Does using a better model fix quality problems?
Not economically. The design bet is that reliability comes from the capability layer rather than model size, which is what keeps a bigger model from being the answer to every complaint.
What does it cost to use my own agent?
Connecting your own agent is free. You pay your agent's provider for the model; Flockbay charges nothing for the connection.