A World Labs engineer has released an open-source toolkit called image-blaster that converts a single still image into a complete 3D environment, including meshes, physics, lighting, and audio, with Claude Code orchestrating the pipeline.
The project comes from Nicholas Neilson, a member of the World Labs team. Image-blaster is a personal experiment, not an official World Labs release.
Quick read:
Single-image input: Feed the toolkit one image and it generates an explorable 3D scene
Composable stack: Marble handles 3D generation, Claude Code drives the workflow, and fal supplies compute
Side project, not product: A solo experiment from a World Labs employee, with no formal support or roadmap
The Stack: Image-blaster wires three AI services into one workflow.
Marble, World Labs' image-to-3D model, builds the geometry and environment from the source image. Claude Code, Anthropic's terminal-based coding agent, runs as the orchestration layer, coordinating calls between the other services and assembling the output. Fal handles the compute and model inference. The result is a scene with rendered meshes, physics-ready geometry, baked lighting, and generated audio.
Why Claude Code is the Glue: Neilson built image-blaster as a Claude Code toolkit, not a standalone app, putting the agent itself at the center of the creative loop.
A developer or technical artist runs Claude Code in their terminal, points it at an image, and the agent chains the API calls, handles errors, and writes the assembly script that produces the final scene. The toolkit form factor means anyone with Claude Code installed can fork the project and modify the pipeline.
This pattern reflects a wider trend in which AI coding agents are treated as a runtime for creative tools, not just IDE assistants.
The World Labs Connection: Marble is World Labs' generative 3D system, and Neilson's day job places him close to what the model can do.
The startup, founded by Fei-Fei Li, has focused on what it calls "world models," AI systems that produce navigable 3D scenes rather than flat images or video. We covered the company's web-streamable 3D Gaussian Splatting capability as another milestone in that direction. Image-blaster is not endorsed by World Labs. It is a side project from a team member exploring what the underlying model can do when paired with an agentic coding layer. Production teams evaluating Marble for pipelines should weigh the official product, not this experiment, against their needs.
Status check: The GitHub repository at github.com/nicholasneilson/image-blaster returns a 404 and may have been renamed, moved private, or taken down. Anyone tracking the project should watch Neilson's X account for updates.
One Image, Many Scenes: Image-blaster sits at the intersection of two trends: image-to-3D generation maturing into usable pipelines, and AI coding agents taking on roles beyond software development.
For VFX artists, previs supervisors, and indie creators experimenting with rapid scene building, the toolkit signals what composable AI workflows can look like outside the major DCC apps. Whether image-blaster itself sticks around or not, the pattern of agent-orchestrated, model-agnostic creative tools is worth tracking.
