It's obvious that the generation of work artifacts is largely going to be done via AI but I am finding it very hard to give up that generative control to AI.
For example I am still manually reviewing every line of code AI produces because half the time I need it to be reworked/regenerated because of gaps (context, pattern clarity, usage details etc..).
So my question to you all is; what systems and processes are you using to optimize your AI generative output and quality?
I don't even have time to test the all programs I'm creating, let alone review the LOCs. I build stuff on a whim and it's in my "did it work" pile. I've also got a "looks ok, I'll deploy it sometime" list.
Embrace it. Enjoy it. Ship solutions to problems not lines of code.
I made a video game to wish a friend happy birthday. I made a couple websites for job applications. I can make a landing page for an idea for a friend and the longest part is buying the domain name. I had a convo with a friend about finding more ideas to work on as I have abundant spare time due to LLMs and there are LLMs sourcing stuff to help execute on that.
Every time a friend has a "it would be cool" idea, I can trivially throw something together to do it.
Really my biggest optimization has been giving the AI as many tools as possible to do the testing part itself, as testing the work is the real bottleneck. Dockerize everything, so all the error logs are in one place and it can reset at will. Have it set up fixtures, so that if it deletes the database (has happened), it can just re-create it.