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Nice ! For the "when to give up" problem, optimal stopping theory (wikipedia) provides a framework that may help (essentially 37% of total time you are willing to work on the problem - e.g. 2 years for a PhD).

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Thanks Shamik.

I've known about optimal stopping theory and the 37% heuristic for a long time but I've never once managed to (or felt like) using it in real life. It is possible that I don't understand how to use it. But also possible that in real life you never really have enough data to ever be able to apply optimal stopping theory effectively.

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Agree that the theory is too rigid for real-life application. But i find that the rule-of-thumb of 1/3 : 2/3 for calibrate : persist generally applies well to most settings.

Examples : 2yr to find a PhD problem (6yrs for a successful phd), atleast 3 interviews before accepting (assuming a 9 interview journey), 2-3 years in a startup before giving up (8years for a succesful startup). At the 1/3rd point, if you dont see a good path forward, give up and try something else.

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Good examples. Thanks.

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Indeed a great article , I loved reading it.

We live in the era where only a final reward is celebrated. To reach a goal, there are various dips a person goes through, but the person is recognized for goal achieving and that specific moment, I feel even the process of ups and down should count. Celebrating dips, as dips are signals of us reaching closer to our goal should be introduced.

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Good article

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