Recently I had an experience that changed my understanding of believability. Since about 2010 I’d been reading a management blog by an engineering leader that I’ll call Q. Q is fairly famous — they’d been working in Silicon Valley for the good part of two decades, in fairly senior leadership roles at a series of famous companies. They also wrote a blog on management and leadership that’s been around since forever. From an external perspective at least, Q presents as an extremely authoritative, highly believable source.
I’d say your conclusion about management is justified. As someone who managed for decades, success is highly subjective. Only survival is really objective.
You have to be careful for folks whose primary accomplishments come from burnishing their brands.
When I was reading the article, I felt some sort of enlightenment.
I’d go even further than you - writing programming blogs is the best way of becoming a famous programmer.
First reason - blog are usually named after their authors, so unless your blog has a weird name, every regular reader immediately knows who you are.
On the other hand most people who read books and use software don’t have any idea who wrote them.
Blogs are a lot easier to write, and a lot easier to popularize than books. They also seem to generate greater feeling of “connection” between the reader and the autho .
So if you have a popular blog on programming, named after you, then you’re guaranteed to be a famous and respected programmer.
Becoming famous by writing software is much more difficult. Let’s say that you somehow managed to some write very popular software. Let’s say that you somehow managed to make people associate the program with you. That’s even more difficult and has more to do with marketing than programming. How many people can name author of libc on their system ? But somehow everyone can name author of 2% of just another reimplementation of Unix kernel.
Even then, when people use your software and know who wrote it, you’re as likely to be hated as respected. If someone considers you author of some program, they will intuitively blame you for all faults of the program (for their completely subjective definition of “fault”). If the program is very faulty (few big systems aren’t), the most you can achieve is infamy.
I am fascinated by how scientist seems to turn the decision making on the believability of other scientists into a core community responsibility. Not great for the general public and amateur scholars, or for inclusion (as whisper networks tend to favor the stereotypical white cis dudes). But I understand why, and the Twitter thread and linked original tweet go into some detail for how this came to be. I guess that is the positive side of what might be derided as “gossip” and “rumor mill” in a community.
In my own women in tech community, we have a constantly running whisper network as well. For example, which companies are worth working for in terms of equitable employment practices, i.e. which company’s DEI statements are worth believing and to which extent.
Just like with Q, how do we test Ray Dalio’s believability?
If we check his Pure Alpha returns from the last 10 and 15 years, it’s pretty bad.
From Jan 2012-Jan 2022 his fund only returned 1.6% a year, while an S and P index fund gave 16.4% a year.
From 2005 to the end of 2021 his fund only returned 4.5% a year while an S and P index fund gave 10.5% a year.
I’m not even sure he has beaten an S and P 500 Index Fund since he started the Pure Alpha fund in 1991.
One could argue 15 years is too short a time period to evaluate performance, but Dalio got famous from his first 15 years of performance.
Maybe his ideas were good 20 years ago but are no longer valid?
Or maybe his competition has already been using his ideas so he can’t keep up?
Or maybe he was just lucky the first 15 years, and the last 15 years of bad performance is due to Regression to the Mean?
Or maybe we shouldn’t pay attention to any stock pickers at all since predicting the future is impossible?
Personally I really like Ray Dalio’s “Principles,” but I thought I bring these thoughts up. It seems verifying believability seems to be really hard in the business world due to luck and narratives.
The gist of it is that I’ve found Dalio’s Principles (or at least Chapters 1 through 5) repeatedly useful, which means it passes a higher bar than ‘believability’ in my hierarchy of practical evidence. But I’ve found that I’m actively discounting more and more of his recent stuff — the Principles for Navigating Big Debt Crises is probably ok — he’s navigated a few of them successfully — but I am very sceptical of Principles for Dealing with the Changing World Order.
Matt Levine, of course, writes the funniest takes on Dalio.
I do feel like this is a criticism that people make of almost every celebrity hedge fund manager: They start out totally focused on making good investments, they make some good investments, they have good returns, they attract more assets, they get really rich, they go on television, they become convinced that they’re omnicompetent geniuses, they get more interested in going on TV and telling people how to solve the world’s problems than they are in picking investments that will go up. And, sure, why wouldn’t you follow that path? You’re already rich.
You know, one thing I’ve been thinking of on the topic of believability is this observation I learnt from Visakan (on Twitter): real experts can articulate the tradeoffs that you might need to make. Whereas non-believable people will just spout advice from a place of “blah blah this thing is good”. (And they may be very articulate about it, which makes them dangerous.)
So one way to push back if you’re talking to a lower/unknown believability person is to ask them to articulate the tradeoffs you’ll encounter when you have to put their advice into practice. And to ask them for real world examples, preferably from their experience.
Unfortunately, you can’t do this when you’re reading advice on the internet (say if the authors are pseudonymous, as in https://staysaasy.com/). So there’s a limit to the usefulness of this approach.
