Developer Ships Steam Game with Claude Code: Lessons on Vibe Coding vs. Vibe Engineering

From Prototype to Production with AI-Assisted Development

A developer has released Codex Mortis, a necromancy-themed survivor/bullet hell game on Steam, built almost entirely through AI-assisted development using Claude Code. The game runs on a custom ECS engine in TypeScript + PixiJS + bitECS. The demo is available now, with Early Access launching March 19.

The One-Prompt Trap and Vibe Coding

The project started with a single prompt: "Make me a Vampire Survivors-style game." This generated a working prototype in minutes, with sprites, abilities, synergies, and companions added within hours through rapid iteration. The developer calls this vibe coding—describing what you want and letting AI build it for fast iteration.

However, vibe coding creates technical debt quickly. After weeks of adding features with prompts like "add X," performance tanked, files grew to thousands of lines, and new features required hacks on top of hacks. The developer refactored with a proper game loop and separated rendering from physics, but testing with 16x more enemies broke everything again.

Two Complete Rewrites and Vibe Engineering

The solution was two complete rewrites. The first rebuild focused on proper architecture, and the second introduced a new stack with proper ECS and batched rendering. The developer notes that AI makes rewrites cheap—when rewriting takes hours instead of weeks, code becomes a tool you swap out rather than "your baby."

This led to the concept of vibe engineering: instead of just saying "make me X," you provide architectural context like "build system X using module Y, following pattern Z, respecting constraint W." You tell AI not just what you want, but how it fits into existing systems. The developer emphasizes: "Your prompts are your architecture."

The Role Shift: From Developer to Lead

With 10 years of gamedev experience, the developer found that deep technical skills were less important than experience as a lead and coordinator. Working with AI in production means defining specs, reviewing output, catching architectural drift, running parallel workstreams, and making priority calls.

On productive days, the developer would catch three bugs, spin up three Claude Code terminals in parallel, feed each one a problem with proper context, and ship three fixes simultaneously. The bottleneck shifted from writing code to managing the process: "My role shifted from someone who writes code line by line to someone who defines what gets built and checks whether it actually makes sense."

Domain Expertise Becomes Portable

Before this project, the developer had zero TypeScript experience (coming from Unity/Unreal), yet built a production game with a custom engine in an unfamiliar language. AI allowed transferring universal knowledge about engine architecture, ECS, production pipelines, and scaling issues into a new environment. The developer notes: "I never actually learned TypeScript. I knew what to build, and AI handled the how. The patterns and instincts came from me. The syntax came from AI."