Earlier quoted context omitted.
I've been writing software for 30 years, a part of it had success in the sense of being widely known and adopted for a long time. Writing software is difficult, consumes time and is difficult as you get older to focus the needed time away from other matters like a professional life and family. With LLM, my productivity suddenly went up x25 and was able to produce at a speed that I had never known. I'm not a developer…
What tool do you use, which languages? Could you give us an example of something you’ve built and how you did it 25 times faster?
The code is written in Dart and never wrote a line of DART in my life, I'm a veteran expert around Java, C++. The reason for choosing DART is simply because it is way readier for multi-platform contexts than Java/C++. The same code base now runs on Linux, Android, iOS, OSX, Windows and Web (as static HTML). Plus the companion code in C++ for ESP32 microcontrollers. It also includes a CLI for running as linux server.
Don't ask me for a hard analysis and data proving x25 performance increase, what I know is that an off-grid product was previously taking me two years of research/effort to build in Android/Web and get a prototype running. Now in about a month went far above all previous expectations (cached maps with satellite imagery, bluetooth mesh, webRTC, whatever apps) and was able to release a product several times per day that works as envisioned. Iterating quickly and getting direct feedback from users.
The repository: https://github.com/geograms/geogram
Overview of the apps being written: https://github.com/geograms/geogram/tree/main/docs/apps
IMHO, Codex is far superior at the moment for complex tasks, Claude is cheaper and still good enough quality for most tasks. In addition to keep several terminals with tasks in parallel, this gives me time throughout the day for other tasks with family/friends and a lot of motivation like a coding-buddy to try different routes and quickly implement a prototype instead of always being alone doing this kind of work. For example, it added an offline GPT bot but wasn't what was needed so could quickly discard it too.
These tools get lost on API implementations and the documentation folder is mostly there to provide the right context when needed. I've learned to use simple markdown documents with things to keep in mind like "reusable.md" or "API.md" to make sure it won't reinvent them. Given my experience, there are parts that I'd implement with higher quality on my own, the trade-off is that I can't touch the code by myself now. One of the reasons is that it would make more difficult for these AI to work since my naming and file structure would make it difficult for the AI to work with, the other reason is because I don't want to waste a full day on a single problem like before. As the product grows more stable is when more attention is given to the finer details. On early stages, that type of quality is still more than good enough for me.
You can try the Android or Linux versions if you are so inclined. Never in my life would I ever be able to build so much in 5 weeks.