Ray Dalio describes the way he makes decisions as: 1. making mistakes and 2. storing the lessons learned from those mistakes in a computer to better help with his decion-making criteria.<p>I'm wondering if anyone's done this and what that program would look like?
I've only done what I see described here in big-picture studies and simulations. It did help though. An example would be in financial planning & simulation, where there's a lot of objective leverage information available. Dates, growth rates, technical indicators, and so on. This can all be manipulated algorithmically. I even did some of it in hobby languages like SmallBASIC (the non-MS version, really interesting project).<p>In fact what he describes sounds like & overlaps a lot with a technical trader's mindset. In that world you are always tinkering with new criteria and storing the updates (mistake-derived as they often are) as scanners, models, etc. (You may find this "software" in ThinkOrSwim or TradingView scripts, etc.)<p>In other areas that aren't so tractable to pure algorithm, I keep it more subjective in the best way I can (subjectivity also has big strengths to leverage) and update my various systems & frameworks more qualitatively, like by updating & rearranging lists of effective steps, designing new thought models, and so on.<p>BTW, did he not go into further depth than that?<p>I remember reading one of Dalio's books some time ago and he was big on principles (200+) but didn't share many details and didn't seem to have created a unifying system. To me that'd be frustrating or maybe even a non-starter under the circumstances for a lot of reasons, i.e. the principles will necessarily start to contradict one another, access to principles by newcomers is necessarily less efficient, and so on.