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A maker is using Google’s Gemini image-generation and coding tools to help design 3D-printable parts for a Fallout-inspired Halloween prop with his son. The AI-produced OpenSCAD code helped him explore shapes and produce usable models, but it also missed design instructions, and the project is still in progress.
A maker writing for ToolGuyd is using Google’s Gemini to help design and 3D-print parts for a Fallout-inspired Halloween prop he is building with his son. The account describes a practical use of AI in a hands-on project: generating adjustable OpenSCAD code and helping visualize unfamiliar shapes, while leaving design decisions and construction to the maker.
The project began after the maker’s son asked for a costume tied to Fallout 4. A full DIY power-armor costume was not feasible within their time frame, so they settled on a simpler character concept, including a decorated chest piece and scavenged-looking accessories. A motorcycle chest protector ordered online was delayed and appeared to be lost, leading the maker to consider foam and craft materials instead.
He has focused on a prop intended to stand out. One part he wanted to model was a truncated cone with a mounting ring. After several iterations, he used Gemini to produce OpenSCAD code for two connected truncated cones. He says the parametric code let him adjust dimensions and geometry, and that an initial print was good enough to inform the next version. He plans to enlarge that part and add holes so it can be attached to a wooden box.
The maker also asked Gemini to help with a handle and a breakdown of a fictional tool into printable subassemblies. He reports that the AI-generated results had errors, including ignored instructions about flush side arms and the placement of pill-shaped holes, as well as unwanted chamfers. He later edited code himself, changing mounting holes and slot dimensions, and was printing a low-density version of the handle while considering whether to remodel parts manually in Fusion or similar software.
AI Supports Early Prop Prototyping
The account offers a specific example of how generative AI can fit into a maker workflow: not by completing a finished object, but by helping turn an incomplete idea into testable geometry. For someone who finds it difficult to model a design that is not yet fully visualized, a generated starting point can make it easier to compare shapes and decide what to change.
The limits are as relevant as the assistance. The maker says the generated models did not consistently follow constraints, and he had to revise code and plan additional modeling work. The story shows AI as an iterative aid rather than a substitute for fabrication knowledge, accurate measurements or human design judgment. For readers trying similar tools, the practical value may be in speeding up early experiments while retaining time to check and correct the output.
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From Costume Idea to Printed Parts
The maker says the original plan was to create a more elaborate Fallout-themed costume, but the available time ruled out building power armor. He and his son instead moved toward an original prop, with a hard hat and a flashlight among the proposed costume elements. The prop’s specific fictional purpose remains undecided; the writer has suggested ideas such as a detector, while his son may choose its name.
The project combines AI-generated code with ordinary workshop methods. The maker is considering attaching individually designed parts to a small wooden box with screws or glue, and says some hot glue may be needed because of the deadline. He also used 3D files for air fittings to test how parts might fit with quarter-inch inner-diameter hoses, while weighing whether to use inexpensive metal fittings. These are prototype decisions, not a report of a completed assembly.
“The code also let me change parameters until I was happy with the geometry and dimensions.”
— ToolGuyd writer
Design and Deadline Remain Open
The writer has not yet reported a finished prop or a final design. The current plan is to make a rough first version, then refine it if time permits before Halloween. It is unclear whether the current printed parts will fit together as intended, whether the low-density handle print will work, or whether the maker will redesign components in CAD software.
The final materials, assembly method and function of the prop are also undecided. The source does not give a precise project completion date, the final cost, or a detailed account of how well the printed parts perform. The writer’s observations about Gemini reflect this project and his experience; they do not establish how the tool performs across other designs or users.
A Rough Version Comes First
The maker’s stated next step is to complete a rough V1 prop from printed parts and a wooden box, then assess whether the components work together. He may print the handle in its final color or remodel it manually to make dimensional changes easier. The assembly is intended to be built with his son, who will decide what the prop is called.
Any later account could clarify which parts made it into the final build and whether the design was refined in CAD software. For now, the project remains a work in progress, with the maker using AI-generated code as one input among printing, manual edits and hands-on assembly.
Key Questions
What is the maker building?
He is developing a Fallout-inspired Halloween prop with his son, as part of a costume plan that does not require full power armor.
How is Gemini being used?
The maker used Gemini to generate OpenSCAD code for printable shapes and to explore possible subassemblies. He then adjusted parameters and edited the code.
Did the AI produce a finished, accurate design?
No finished design is reported. The writer says Gemini ignored some instructions and created unwanted details, so the generated output required review and modification.
Is the prop complete?
No. The maker was printing and revising parts, with a rough first version planned before any further refinement.
Source: rss
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