Some concepts from my recent readings collide together when it comes to the framework of how to make a decision, identify a good idea, or make a good investment. They are somehow similar but congruent. I think it’s a good idea to list here.
1. Sam Altman suggests to “look for small bets you can make where you lose 1x if you’re wrong but make 100x if it works. Then make a bigger bet in that direction.” One common example is people can get too comfortable to leave behind their jobs at Google or Facebook, instead of bootstrapping a business even they have some good ideas. The truth is that if the business fails, it’s not difficult to be back to the corporate life; but letting go of a potentially great idea that could grow exponentially would be regrettable.
2. Chamath Palihapitiya shed light on how he comes up with ideas by always asking two questions “Is it relatively non-courageous to start but will it get deeply courageous to keep going? And, if it were to happen, is this an unbelievably hard thing that would just shock people?” He raised an example of Airbnb – it’s super easy to scrape a bunch of listings on Craigslist and I stuck them on my website, but it gets incrementally harder and the courage has to go way up to make every room in every building that’s not a hotel bookable and behavable like a hotel.
3. Ray Dalio in his famous Principles: Life and Work puts that you should find the most believable (or the smartest) people possible who disagree with you and try to understand their reasonings led to the conclusion but not the conclusion itself. It’s a great way of staying out of your confirmation bias bubble. You’d consider not doing it if the reasonings resonate; if you still insist, then go for it.
4. Try many options at the very beginning when cost is still low to avoid path dependent. Like the nature of Greedy Algorithm, people tend to look for the optimal choice at each step (when breadth isn’t wide enough) as they attempt to find the optimal overall solutions. It’s a short term game versus long term’s. As mentioned here, the solution is to introduce Simulated Annealing where in general one should explore more opportunities early on and can explore less as one proceeds for efficiency.