5 ms·
In this last week, I've performed experiments in an almost fully automated way - parallel to my main work, and easy to orchestrate. This has led to 3 parallel
by switchbak 2mo ago
In this last week, I've performed experiments in an almost fully automated way - parallel to my main work, and easy to orchestrate.
This has led to 3 parallel pieces of adjacent work that each speed up our build by quite a drastic margin. When combined, this is a massive improvement. None of this would have happened in the old days, as the research itself takes a long time to babysit and a lot of options to check.
So I very much agree - the activation energy can be a lot lower on some kinds of tasks, and some of those get big returns for small inputs. It's not all like that, but part of the game is identifying when you can spot those high return efforts.
- rsoto2 2mo agoor the AI could lead you to a completely unusable experiment and lead you to believe it was successful wasting weeks of work. Not saying it will happen to you, but there is a huge "survivorship" bias already in software for what tools are useful or not. Maybe it's the person and not the tools.
- rsoto2 2mo agoFigured out a better way of explaining it: dev A knows exactly what the program should do and how to verify the AI output dev B thinks they know what they are doing but are actually misguided by bad psycophantic AI output they have incorrectly verified. both work on product C