The AI Agent Indie Game Workflow Revolution: My Journey to Efficiency
I’ve been using AI to help me write code for two years now. From the early days of Copilot completing my code snippets, to ChatGPT helping me write function documentation—now I’ve started treating AI as a “virtual colleague” rather than a tool.
Where does this road lead? I’m not sure. But what’s happened over the past three months has completely redefined the boundaries of what “making a game solo” can look like.
Three Stages of Evolution
Stage 1: The Tool Phase (2022-2023) AI was an advanced autocomplete. You’d write a segment, it’d complete a segment. Efficiency improved by maybe 20-30%, but the core workflow stayed the same.
Stage 2: The Assistant Phase (2024) You described what you needed, it helped you implement it. You’d say “write me an inventory system” and it actually would. Efficiency jumped to 2-3x improvement, but there was a lot of “translation” work on your end—converting game design requirements into technical requirements, then translating technical implementation into actual code.
Stage 3: The Colleague Phase (2025-Present) I started feeding complete game design documents to AI Agents, letting them understand, delegate, and execute on their own.
This isn’t “AI helping me write code.” It’s “AI helping me make games.”
What Happened After Devin
The most jaw-dropping thing this year wasn’t any single new tool—it was the workflow pattern Devin demonstrated: AI Agents can complete an end-to-end task from start to finish without hand-holding.
I tried feeding a complete endless runner game design document to a similar AI Agent system. The brief was something like: “A vertical endless runner with three playable characters, five terrain types, ten achievements, roughly five minutes per session.”
Twenty-four hours later, it came back with a runnable game prototype.
Not code snippets. Not a design document. Not mockups. A fully playable game.
What My Workflow Looks Like Now
Morning: Write a brief design note for today’s features Mid-morning: AI Agent reads the design note, breaks down tasks, writes code, runs tests Afternoon: I handle what AI can’t—feel tuning, visual effects, external system integrations Evening: Review what the AI accomplished, decide on tomorrow’s direction
The key shift: I no longer need to implement things myself. I just need to decide and validate.
Where This Road Ends
I don’t know that either.
Some say AI will replace indie developers. Others say AI will just make indie developers more efficient.
My take: AI isn’t replacing me—it’s improving my conversion rate from “idea” to “implementation.”
A person without AI, making a game needs: idea → design doc → technical spec → code implementation → testing → tuning → release. A person with AI, making the same game: idea → design doc → AI implementation → tuning → release.
Three steps in the middle, AI is handling those. And the human value is increasingly concentrated in two things: the idea itself, and judgment on the results.