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Derp McDerpenheim's avatar

Many folks who give out what is labeled "bad advice" are unaware that their success is mostly due to randomness. Thats why that sort of advice lacks true insight - the giver did not become successful because of something they did, they just happened to be standing in the right spot when the bullets went flying. Its also why the advice seems super obvious - because the giver cant tell that their success is just a random selection and does not come directly from their own choices. There advice amounts to, "just stand there and hope you dont get taken out, thats what I did!"

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Matthew Ritter's avatar

A major, and hopefully relevant, gripe I have a long had about public advice is that it is too rarely conditional. I do think there are situations where “work harder“ it’s good advice, we could debate whether it is 1%/10%/80%, but the more productive framing would be “what kind of person would benefit from this, now?”

Maybe one heuristic is “If you have had an early success, but recently a failure, and this goal is not dominated by noise, you should *try* working harder for *one week* and evaluate the outcome”. As an example I finally got a personal trainer after believing my energy level was insensitive to exercise - turns out I just wasn’t doing enough of it.

Being human, I had a strong prior that exercise should be helpful. The cause and effect relationship is not nearly as noisy as entrepreneurship, and the reason I was not trying harder was pretty clear: it’s not fun and it is too easy to turn off a YouTube video.

But this is already way too complex to get across in a verbal public interview. Anything more complex than a single if/then statement would also get pretty dry for a written article. I don’t really have a solution to the problem that the algorithmic complexity requires to give good advice might simply overflow the capacity of most channels through which we receive it

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