I've been a professional C# and TypeScript developer for years. I know how to ship software. But game development? Unreal Engine? C++? None of that was in my vocabulary.
Twenty years since I last wrote C++. Never opened Unreal Engine. Didn't know what a GameMode was or how physics simulation worked in a game engine. I had an idea for a game and two weeks of evening time.
Just over two weeks and roughly 20,000 Kiro credits later, I have a playable 4v4 arena combat-sport game with probabilistic AI, full combat, disc physics, animation layering, in-game music, sound effects, an announcer, menus, and a match flow that runs start to finish.
This isn't a tutorial. It's what happened when I pointed an AI coding agent at a domain I knew nothing about and iterated relentlessly.
The Game
The project is a clone of DeathRow, a 2002 Xbox game by Southend Interactive. Two teams of four in a futuristic arena, throwing a disc through a goal ring to score. You can also beat your opponents unconscious. Knock someone out and their team plays shorthanded. Win by outscoring, or just KO everyone.
Here's what the original looked like:
The Setup
Kiro with Claude Opus 4.6 on macOS. Unreal Engine 5.8. The experimental Unreal MCP server connected so Kiro could interact directly with the editor: creating assets, configuring properties, placing actors in levels.
Two steering files gave Kiro permanent context: one describing the game and my background, one covering architecture decisions and project structure. No game development experience. No Unreal tutorials. No C++ refresher. Just a description of what I wanted and a willingness to iterate.
How the Iteration Works
I'd describe what I wanted at a high level. "I need a disc that bounces off walls with configurable physics and triggers a score when it enters a goal." Kiro figured out the Unreal-specific implementation. I'd play the result, describe what felt wrong. Kiro would diagnose and fix it.
The work was phased: movement, then disc physics, then teams, combat, AI, game flow, polish. Each phase had a deliverable I could test by playing. Some phases spawned sub-phases when something wasn't right. I'd describe a gap and Kiro would go as deep as needed.
I ran autopilot mode exclusively. Kiro wrote C++ classes, created Unreal assets via the MCP, configured inputs, wired up particle systems. My job was playing the result and saying "this doesn't feel right" or "what's next."
Week One: From Nothing to Playable
The first week produced the core game. Arena, movement, disc physics with auto-targeting, four-player teams with switching, a full combat system with KOs, seven AI characters running behavior trees, match flow with scoring and halftime, a menu system, controller support, and basic audio feedback.
It worked. But it felt mechanical. The AI was deterministic. Predictable patterns, robotic movement, no personality.
Week Two: Making It Feel Like a Game
I designed a probabilistic weight engine to replace the deterministic AI. I sketched out how decisions should be calculated: base weights modified by stacking multipliers for personality, team tendencies, game state, spatial awareness, and difficulty. I gave Kiro pseudo code showing the pipeline stages and how modifiers should compound. Kiro recognized the pattern, implemented it in C++, and wired it into the behavior trees.
This broke everything. The new AI exercised code paths the old deterministic system never touched, and latent bugs surfaced everywhere. Disc physics bouncing off characters instead of passing through them. Animation states leaking into the wrong context. Catch volumes too small at higher speeds. These bugs had been there from day one, just never triggered. I spent hours describing symptoms and Kiro traced each one to its root cause.
Beyond the AI, I added an energized disc mechanic. Hold the throw button to charge a power shot that instantly KOs opponents on impact (the namesake "deathrow" move). I overhauled the animation system to support priorities, interruptibility, and weighted variations. Catch animations now start before the disc arrives. The disc doesn't release until the throw animation hits its release point. Characters celebrate after scoring.
For audio I used ElevenLabs for sound effects and announcer voice lines, Suno for in-game music. Still entirely AI-created, no human artists involved yet.
Here's where it stands after just over two weeks and 20,000+ Kiro credits:
Prototype status: Combat is difficult because players move fast and there's no target lock for melee. Stamina tuning needs work. There are animation quirks and AI quirks I'm still chasing. Zero art, texturing, or modeling has been done. Everything you see is placeholder geometry and free Mixamo animations.
Where Kiro Carried Me
I didn't know Unreal's class hierarchy, macro system, or memory model. Kiro wrote thousands of lines of C++ across dozens of files spanning every layer of the engine's framework. I never wrote a line of C++ myself.
The things that would have taken me months to learn from documentation, Kiro just did. When the Unreal MCP couldn't handle something (and the experimental tool has plenty of gaps), Kiro explained exactly what I needed to do manually in the editor, step by step.
The steering files grew with the project. Every time I hit a recurring failure pattern, I'd document it so Kiro would recognize the symptoms immediately in future sessions instead of rediscovering the fix from scratch.
What I Actually Did
My contribution was design and direction, not code. I wrote the game design. I played and described what felt wrong. I designed the probability system and gave Kiro pseudo code to implement. I made architecture decisions when options were presented. I generated audio with ElevenLabs and Suno. I followed Kiro's instructions for the manual editor steps. I said "good enough, move on" when polish wasn't worth more time.
The Numbers
About 20,000 credits over two weeks of evening work, Claude Opus 4.6 exclusively. Over 80 C++ files. 150+ property-based tests (written by Kiro). Zero lines of C++ written by me.
At current pricing that's the Kiro Power tier ($200/month for 10,000 credits, overages at $0.04/credit). For two weeks of what would otherwise be many months of learning, I'd make that trade every time.
The Takeaway
The hard part isn't getting something working. It's getting it working well. The first week was fast because everything was new and "it does the thing" was the bar. The second week was slower because the bar became "it does the thing and feels right," and that meant chasing bugs that had been invisible until the AI started exercising edge cases.
The skill that mattered most wasn't programming. It was describing what I was seeing clearly enough that Kiro could diagnose it. "The disc bounces backward off a teammate" leads to a fix. "Passing doesn't work" leads to a conversation.
