Vibe Coding in Practice: Building a Powerpuff Girls Rhythm Runner

A Sspai article detailed retrospective of a Vibe Coding practice — developing a Powerpuff Girls rhythm runner game entirely through AI conversation with zero hand-written code.

Documents the complete process: requirement description, AI generation, debug feedback, iterative optimization. Shows Vibe Coding's real capabilities and limitations.

Excellent case study for understanding Vibe Coding workflow and outcomes.

This is one of the most complete Vibe Coding case studies available. With zero hand-written code, through about 15 dialogue iterations, a fully functional Web game was developed in 4 hours. The article documents the Vibe Coding workflow in detail: requirement description → AI generation → phenomenon feedback → iterative fixes. Extremely valuable for understanding AI Coding's actual capability boundaries and optimal usage patterns.

This Sspai article is a complete Vibe Coding case study — developing a Powerpuff Girls rhythm runner game from scratch using only AI conversation.

What Is Vibe Coding

Vibe Coding is programming entirely through natural language conversation with AI. Developers write no code, only describing requirements, reporting bugs, and suggesting modifications. AI handles all code generation and modification.

Development Process

Requirements: Author described game concept — Powerpuff Girls running through a city, jumping to music rhythm to avoid obstacles. Including character selection, scoring, visual style.

Initial Generation: AI generated the basic framework including HTML Canvas rendering, keyboard events, collision detection, and simple rhythm system. ~500 lines.

Iterative Debug: First version had issues — inaccurate collision, animation stuttering, rhythm sync drift. Author described symptoms (not code fixes), AI fixed them.

Polish: After ~15 conversation rounds, the game reached playable state. Added particle effects, combo system, and leaderboard.

Results

Final product is a fully functional web game running in browsers. Visual quality and gameplay are 'presentable.' Total development ~4 hours.

Limitations

  • Complex physics simulations still inaccurate
  • AI sometimes 'forgets' previous fixes
  • Art assets (sprites etc.) need separate preparation
  • Performance optimization needs human guidance

Conclusion

Vibe Coding is very effective for prototyping and small projects, but complex logic and performance-sensitive scenarios still need traditional programming.

Industry Trend Connection

Vibe Coding is evolving from a developer community buzzword to a genuine productivity tool. This case proves AI Coding already has practical value for prototyping and small projects. As Agentic AI frameworks (like Claude Code Agent Teams) and Code Sandbox technology mature, Vibe Coding's capability boundaries will expand further, potentially transforming fundamental software development workflows.

In-Depth Analysis and Industry Outlook

From a broader perspective, this development reflects the accelerating trend of AI technology transitioning from laboratories to industrial applications. Industry analysts widely agree that 2026 will be a pivotal year for AI commercialization. On the technical front, large model inference efficiency continues to improve while deployment costs decline, enabling more SMEs to access advanced AI capabilities. On the market front, enterprise expectations for AI investment returns are shifting from long-term strategic value to short-term quantifiable gains.