No-Code 3D Procedural World Generation
miran248 · reddit · 2026-07-16
In about a week and with almost no manual coding, the author created a 3D procedural world experiment. Initially a 2D zombie game, the project pivoted to procedural generation, trying out various CLI/model combos including opencode + deepseek v4 pro, claude + fable 5, opus 4.8, codex + gpt-5.6-sol, and gemini + auto model.
Key takeaways from the experiment:
- When letting models modify code directly, they tend to add new functions rather than alter existing logic, leading to duplicate implementations in the codebase.
- codex spent most of its time refactoring. Though painful, it eventually produced better-structured code and highly useful unit tests.
- Regarding CLI experiences: opencode had the best UX, codex excelled at compaction and starting new sessions, claude was frequently rate-limited right before finishing, and gemini-cli was relatively basic.
Model performance: deepseek was fast but prone to hallucinations; sol loved writing wrapper code; opus was average but had mediocre code style; gemini was slow and often failed to find answers. The author concludes these models are great for plan mode and brainstorming, but shouldn't be left unsupervised (yolo-style) in real projects. For safe implementation, isolate features in separate branches and conduct manual reviews.
Related event: AI Workflows for 3D Worlds, Games, and Video(12 posts)→
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