self improvement for agents rely on three loops the first one is the more common, the bug-fixes loop basically you connect your loop to posthog / sentry, you see a bug, you let your agent fix it. fairly easy, thats where most of the 'software factory' thesis in bay area is focused so far. closed loop, but you need to do lots of testing to make sure the agent is not adding noise, that you are measuring the right target etc the second loop is the feedback loop. it's quite early & the most prominent tweet i've seen about that is from @brian_armstrong, with his /feedback endpoint tweet. basic idea is to build an endpoint for agent to give feedback & suggest improvement. once you have that, you have your own users that can improve your software, which is quite awesome. i've started to implement that everywhere, on my skills, on aeon, on my websites & more. honestly this is quite an exciting space. the third loop is the human loop. humans are so unique, so interesting, our memory is so complex. we will never be able to approximate what a human can ship in a day using AI. ask an AI for a project idea, most of the time it will be a pomodoro app or a very simple idea like that. the human loop means putting yourself as the master of the loop & trying to let the AI automate everything for you. which means giving the AI a high level overview of your taste, of what you did today, what you did yesterday, so all information gets mapped in real time in the factory. for this, you need a very good simulator system, a way to ingest fine-grained human data at scale AND PRIVACY.