My current large project is gas-fakes, which is an emulation that allows local execution, continuous integration, and containerization of native Apps Script code. In other words, we are not just ’emulating Apps Script’ – we are liberating it.
Initially, AI generated code and testing was not something I was comfortable publishing, so to this point real people have coded and tested the majority of the repo. However, now the architecture and techniques are fully mature the remaining work is largely just busy work implementing and testing the remaining, less used, Apps Script platform methods.
As of gas-fakes v2.5.3 we are at 4399/6708 methods and 10,500 parity tests on the emulation against the live Apps Script platform. Now feel a little more confident about allowing AI to do some of coding work.
As an open source developer, my work is voluntary and unpaid, and therefore have to balance the potential token cost at my own personal expense, versus the value of any time saving I might make.
This article is about combining the planning capability of antigravity, with the a free local model (Gemma running under oMLX on a Mac) doing the grunt work. Like this my Gemini costs are minimal, and the local heavy work is free.
