It's really interesting to be on the other side of this.
Because I'm around programmers, I usually hear programmers explain how some other field is simple, but in this thread we have the opposite, someone from another field explaining how programming / engineering is simple
IMO, one of the most common mistaken beliefs I see is the belief that, outside of one's own field, the world is understood.
It's easy to see that, in one's own field, the world is not understood but, for some reason, people don't realize this is also true of other fields.
An example from the hardware world is Intel's Copy Exact methodology, where they tried to make every fab identical.
It's not obvious this is a good idea because it's very expensive to do this since conditions (land, etc.) are different in every location where you have a fab.
Also, people at other companies (AMD, etc.) argued that making every fab a copy of "fab 0" and having people train and fab 0 and copy the exact process elsewhere would stifle innovation and creativity since people at other fabs wouldn't be able to innovate.
With the benefit of hindsight, we can see that Copy Exact worked well and, despite recent stumbles, Intel wiped the floor with their competitors on the fab side of things for decades.
Copy Exact was a key enabler of this. Here's a story I was told that illustrates why:
When Intel opened their first fab in AZ, yields were low and efforts to fix it didn't work. Eventually, someone realized they failed @ Copy Exact because the AZ fab didn't run its dehumidifiers.
When they injected humidity into the air and ran the dehumidifiers, yields improved.
I believe it was later theorized that the reason yields improved was that the dehumidifier system was removing ammonia from the air, but with Copy Exact you don't need to know why something works, you just need to make sure you replicate the exact conditions.
I hadn't yet worked in software and I argued that hardware had a bunch of nearly impossible to convey implicit knowledge, but of course once I started working in software I saw it wasn't so different.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
Despite increased centralization over the past 20 years, the internet feels a lot more like the wild west to me in man ways, e.g., the Google index hasn't kept up with the size of the internet, so an increasingly large fraction of the web is undiscoverable via search.
Even 10 years ago, I could basically always find old blog posts I'd read with Google.
Now, an exact string match search with site:[URL] frequently doesn't turn up the result and I have to wget the page and grep for what I'm looking for.
If the site's too large to wget and it doesn't have a custom index, I frequently can't find the page. Large commercial sites, like Twitter, sometimes build complete indexes, but it's a non-trivial effort to index something that's even 1/100th the size of Twitter, so most don't.
One thing I really liked about it was that it suggests/summarizes actionable ways to check your own thinking, which I found useful even when it was discussing a way of thinking that I've had since I was a kid since I still mess up all the time and having concrete checks helps.
Another is that it does a really good job of laying out the case for various ways of thinking. There are 6 blog posts that were on my to-do list that I think I don't need to write anymore since the book describes what I wanted to describe, but better than I would've done it.
I feel like "regretted attrition" is a curiously bad stat to track considering how widely used it is.
On the one hand, it undercounts "attrition we shouldn't have had" by ignoring second order effects that cause people to become "unregretted".
When I've worked in orgs or companies that have low total attrition (~5%), non-regretted attrition has been something like 1% or sometimes as high as 2%.
When regretted is ~15%, non-regretted will be 5% to 10%. Most of that 5% to 10% wouldn't have non-regretted in a good org.
The same things that cause regretted attrition also cause people to burn out and do work that allows the company to call the attrition "non-regretted", but it's only non-regretted if you want to operate a company that sets people up to burn out and lose motivation.
One thing I've wondered about for a long time is why I fail interviews at such a high rate, e.g., see danluu.com/algorithms-int….
People who've mock interviewed me have a variety of theories, but I don't think any of them are really credible, so I'm going to wildly speculate.
The most suggested reason people have is that I get nervous and that's the problem, which people think because I do fine in their mock interviews.
That's a contributing factor, but I only get nervous because I've failed so many interviews and I didn't used to get nervous, so
there must be at least one other cause.
Another explanation that's consistent with the evidence is that when I say something "stupid sounding", people who mock interview me (who know me) assume it isn't stupid whereas interviews assume it is stupid, e.g.,
Is there anyone who's writing about different problem solving approaches / styles? An example of the kind of thing I mean (but, incomplete, because it would be nice to see more than two approaches to a problem and I'm only going to discuss two for this example):
Once, at a meetup Matt Singer was hosting, Brendan Gregg asked me what I was working on, and I mentioned that I'd recently written a little (5kLOC) parser to parse every line of every dmesg we had in our datacenters to audit machine health issues.
Of course, Brendan had done a vaguely analogous thing for Netflix and he showed me what he'd done, which was so much in his style that I think that if you saw the result without knowing who did it, you'd say "wow, this looks like something Brendan Gregg would make".
Is there anyone doing in-depth interviews on various aspects of why the world is the way it is?
Some examples of interviews I'd like to hear below
Looking for interviews because I don't think one person could have the breadth & depth to regularly answer these kinds of questions
How is it that Michelin has generally had either the best in class tire or close for every class of tire they make for decades?
Perhaps this isn't inherently more mysterious than the effectiveness of Apple's CPU design group, but I don't know who I could ask about Michelin.
Why has non-OC canoe tech stagnated relative to kayak tech?
There's the obv. answer that there's more $ in it, but I want to know why specific innovations that seem like they should be portable are super niche, e.g., the stuff Nick Adnitt is doing, or GRB's curved blade paddle.