Key Points
- AI coding agents like Claude Code, Claude Opus 4.5, and OpenAI Codex enable rapid software prototyping.
- The author’s experience dates back to using an Apple II Plus and programming since 1990.
- A multiplayer Katamari Damacy clone, “Christmas Roll‑Up,” was created using Claude Code.
- AI agents produce flashy prototypes but rely on patterns from their training data.
- Creating durable, production‑ready code still requires human experience and skill.
AI Coding Agents as Rapid Prototyping Tools
If you’ve ever used a 3D printer, you know the thrill of loading a model file, pressing a button, and watching a physical object appear. The author compares this sensation to using AI coding agents such as Claude Code, Claude Opus 4.5, and OpenAI’s Codex. Since November, the developer has run extensive experiments through a personal Claude Max account, generating dozens of projects and enjoying a level of fun not felt since learning BASIC on an Apple II Plus at age nine.
Personal Background and Toolset
The author’s programming history spans languages like BASIC, C, Visual Basic, PHP, ASP, Perl, Python, Ruby, MUSHcode, and others, with experience dating back to 1990. Though never an expert in any single language, the developer has built small tools, scripts, and hobby games, giving insight into modular program architecture. This background informs the evaluation of AI‑assisted development.
Notable Experiments
Among the projects created with Claude Code is a multiplayer online clone of the game Katamari Damacy, dubbed “Christmas Roll‑Up.” The experience demonstrates the agent’s ability to generate functional game prototypes quickly.
Limitations of Current AI Agents
While Claude Code, Claude Opus, Codex, and Google’s Gemini CLI can produce flashy prototypes of applications, user interfaces, and games, they rely heavily on patterns found in their training data. The author likens this to a 3D printer that can produce a model but cannot replace the craftsmanship needed for mass‑production quality. Durable production code, complex project management, and truly novel software still demand human experience, patience, and skill beyond the current capabilities of AI agents.
Conclusion
The developer’s hands‑on experience underscores that AI coding agents are valuable for rapid prototyping and exploration, yet they are not a substitute for seasoned programmers when it comes to building robust, production‑grade software.
Source: arstechnica.com