Full Title: Tribe of Mentors: Short Life Advice from the Best in the World
A Summary: Writer Tim Ferriss asked 11 questions to >100 highly successful professionals across a variety of fields. The book consists almost entirely of each titan's responses. You may recognize some of the following titans:
Brené Brown
Terry Crews
Whitney Cummings
Jimmy Fallon
Neil Gaiman
Temple Grandin
Jesse Williams
Steven Pinker
Pros
Organizing the book as a series of interviews creates a fast-paced reading experience
Some of the guidance from one titan to another is contradictory.
Why is this a pro? Because it means that the author probably didn't cherry-pick responses (i.e. to create a more cohesive narrative).
The methodology behind the selection and sequencing of questions was thoughtful
Area for Future Growth:
There is a crucial 12th question that Tim Ferriss should include if he ever decides to expand his tribe of mentors:
How much of your success has come from luck and/or privilege?
Without the answer to this question, I’m not sure how effective each titan's guidance would be to anyone else.
Before starting this book, I recommend getting comfortable with the following cognitive biases:
The Survivorship Bias
If we try to understand cause-and-effects relationship by only focusing on the subjects that had a positive outcome, then we might wrongly conclude the subjects were successful because of some wisdom or talent— even when it's simply luck.
Example: Sometimes news reporters will interview a lottery winner asking them to reveal their method of picking the winning ticket. This implies that the winner may have some secret knowledge or skill that caused the victory. In reality, they should also survey the winner about their 1,000 previous failed attempts, as well as the 1,000,000,000 failed attempts by other unsuccessful lottery players (many of whom probably performed near-identical actions with no success). Having all the data (vs. focusing on one data point) will clarify that the winner was almost certainly just lucky
Confusing Correlation with Causation (or Spurious Correlations)
Our brains seek out patterns and actively try to identify cause-and-effect relationships. The more cause-and-effect relationships we see, the more control we feel in the world. The problem is that, when we falsely decide that a cause-and-effect relationship exists, we may then make decisions to repeat the "causal action" but fail to produce the desired effect. When 2 data sets seem to show a relationship, there are a few possibilities:
they have a cause-and-effect relationship
they are two effects of the same cause
the data is flawed
the data sets are unrelated (i.e. coincidence)
Below is an example of a spurious correlation (a.k.a. a coincidence).
Obviously, there is no relationship between naming an American child Tyler and Italian drivers pumping more gasoline; this is just a coincidence. (To view more silly coincidences, I recommend checking out this website.)
Is Tribe of Mentors worth reading?
Perhaps not all >450 pages, but I do recommend the following:
Read the prologue where Tim Ferriss explains the methodology behind his questions and their sequence
I may not agree with all his decisions, but I do feel inspired by how he thinks through the complete experience for the respondents in order to optimize for interesting answers
Read the chapters for the titans whose biographies you’re already familiar with, and whose writing you already trust to be candid
