What indie puzzle game development actually looks like, solo
Solo development doesn't mean doing a studio's job alone — it means every scope decision has to earn its place, because there's no one else to absorb the cost of a wrong one.
Studio Practice
The best use of AI for a solo developer is discarding bad ideas faster, not polishing good ones.
Last reviewed 2026-07-17 · Signal Notes
Key takeaway: The true value of rapid prototyping isn't getting to a finished product faster; it's getting to the 'fail state' of a bad idea before you've invested weeks of work into it.
In solo development, curiosity is expensive. Wondering if a new grid mechanic would be fun often requires days of building the underlying logic, creating placeholder art, and designing a few test levels. If the idea turns out to be a dud, that time is lost. AI tools drastically reduce the cost of this curiosity.
Using AI coding assistants to quickly scaffold the core logic of a mechanic, and AI art generators to mock up a quick visual representation, allows a developer to go from concept to a playable prototype in hours instead of days. The code might be messy, and the art might be inconsistent, but it serves its purpose: answering the question, 'Is this actually fun?'
Because the prototype cost so little to make, it is emotionally much easier to throw it away if it doesn't work. This is the hidden superpower of AI in the prototyping phase: it encourages ruthlessness. You can test ten ideas, discard nine without regret, and focus your real, meticulous human effort entirely on the one idea that proved its worth.
Related notes
Solo development doesn't mean doing a studio's job alone — it means every scope decision has to earn its place, because there's no one else to absorb the cost of a wrong one.
Why large language models and procedural algorithms solve different problems, and where they belong in a small studio's toolchain.