Which aspect of the Amazon design doc culture that you loved the most?
417 karma · joined June 28, 2017
https://metamagic.substack.com/
Too many have learned (correct or not) that promo committees want to see that only the author wrote a doc and no one else. This further slows down everything and disincentivizes cross learning. I know software engineers who spend a full quarter or more in isolation writing design docs. The majority of the writing in a design doc is the actual design, but the other 99% is the definition of the problem. Too many times I have been in a review and spent a bunch of time improving the definition of the problem which results in the design needing to be scrapped and most of the doc needing to be re-written.
Worst case scenario is when by improving the problem definition a simple solution appears that doesn't require a complex design. The author having invested a lot of time in a complex design (that historically and many committees still look for to promote off of) will push back against anything that is simple. The difficult trick is helping the engineers to improve their problem definition early in the writing process.
I have seen design docs that have no alternatives presented. The design doc was simply a labor intensive way to write down what needed to get done or what someone wanted to do.
This also results in design docs turning into a bug tracking system if you squint. In a hand wavy way everyone is working on their design doc, not bugs, bugs can't get you promoted.
And OP like to wax poetically about how when you join a team you can just go and look at the design doc like that is a simple and obvious thing. They are often not tracked in any central place. For many teams design docs are not owned by the team or the project, but by the individual because you can make sure no one else contributed. This is again for the promo committee sake. Many design docs you can't get access to, not because they are super secret, but just because. And it isn't like teams have say two or three design docs, no there is a mountain of design docs to read. And with around a two year turn over at Google many design docs get lost to time. At any other company this could be like if you joined the team and I said everything you need can be found by reading all the closed bugs or read every commit message in the main branch.
Anywhere else I would have been grabbed after lunch and would have worked on defining the problem for a few hours with the team at the whiteboard. The senior members teaching the younger in real time how to think about these things and iterating quickly. Most of the time this would be written down in the bug tracking system or for bigger stuff in the project's wiki/folder to be owned by all.
All of the above can be improved and I have worked on improving all of them, but culture is a slow thing to change. Design docs are a good idea as a concept, but there are pitfalls and the way they are being used by many (not all!) at Google is not it.
Most companies reach a size and tenure where they are still trying to grow by a certain percentage every year. They had grown year after year, but as they saturate the market or the market starts to shift they can't grow at the same rate they once did. As they turn into a stable dividend type company ideally growth should more match general market growth, but still growing.
Google makes a lot of its money from showing ads to those using search. They are facing your classic innovator's dilemma. The upstart that can't do 1/100th of what you can, but that one thing it can do it does so much better and they start taking customers and they start climbing that classic S curve of growth. Many of these companies built themselves internally for growth, not for sustainability. Internal incentives cause them to bleed the smartest and brightest & outsource whole departments rather than simplifying. Layers of bureaucracy slow down everything further letting those scrappy startups go after opportunities that the old guard couldn't.
No one thinks Google will go from 23B to 0 by next quarter, no the thing they are talking about is when companies like this don't go from 23B to 25B, but instead to 22.9B.
Y Combinator teaches startups all about the beginning of the diffusion of innovation because that is what is most important. I could probably give a little class on the other side of it, call it the missing lesson or something fun. The value isn't in learning how to not get into the same trap, but to understand your competition better and how to learn what is most likely going on internally and how to exploit it.
This isn't the library I went to as kids that had a tiny rack of VHS tapes in the back. They seem to have fully embraced the digital era.
There absolutely could be blind spots and been iterating on it all year each time the tweaks are smaller, but the core idea has not changed, but simply accumulated more and more evidence.
And for anyone familiar with lisp, code is data, data is code. For modern coders you can think that it has a billion feature flags you can also flip on and off rather than rewriting the code on the fly
There are some scary implications such as in some cases we have had sexuality and gender changes once we knew how to “inject into the system”
I guess when you get down to it, it wasn’t actually that note worthy by itself as most cases are simply minor versions of already well documented conditions. It is only when you combine them that they add up.
And lastly given that I have not paid to get it peer reviewed and published formally it isn’t news yet. Again no school affiliation. Just now mostly helping treat a bunch of those common conditions I mentioned.
Sometimes this has involved using nebula and their whole genome sequencing dna test to get much more accurate data, but more often than not the cheap dna tests most people do were good enough.
As for actual programs, I did write some quick and dirty scripts to scan dna files for specific snps, but mostly I would just read them as the parts I needed were not that long.
There is a fair amount of phenotype data to start with. What ultimately started this was knowing 1) that there was a number of conditions that are seen in statistically weird numbers in the LGBT and 2) sex hormone levels in the LGBT are not exactly what you would expect.
My goto fun question when talking with someone in the LGBT is if they have hypermobility. A good percentage do. In one specific example those with classical like EDS will have 21-OHD and thus POTS and elevated 17-OHP, backdoor DHT production (aka PCOS for women) etc.
The real question I have been pondering is what exactly do I do with this as this is just a fun puzzle, not my job, I don't work for any school etc.
"This is no more difficult to understand than any event based system" [insert image of the Netflix micro services architecture]
This gets a laugh.
DNA is like an executable file written in assembly. Most of the time it makes a bunch of pure functions (but not always) and it is self modifying, lol. For most of the work I do I can presume that gene X produces a "pure function"
At the next level up you have a bunch of functions that can take some arguments and spits out some stuff. The question is does that function work etc?
At the next level up you have systems thinking. If I have 100 lambda servers that are all executing from a queue and then I have 20 lambda servers that are all reading from those 100 you can guess where the data is going to pile up.
I am radically over simplifying, but hopefully you see the parallels to binary, code, application logic
In our "designed" software you can almost never go and change one line to modify the behavior of a program. Instead you have dozens if not millions of functions that all interact depending on the lens by which you want to look. Usually it is contained in on "area" with code that matters the most, but that isn't always the case. Is it any surprise that biology is even messier?
The article mentions the 300 genes related to schizophrenia. This is like me mentioning that my random Go service also uses a bunch of Go standard library code when it is executing.
Debugging stuff like this is what our careers are made of.
For a long time scientist were looking for a single gay gene. Poking around once I knew what to look for it only took around 6 months to figure out the whole LGBT, but in nearly all cases it involves more than just one gene. You simply have to apply debugging logic at each layer to figure it out. It is handy to understand all the layers, but depending on the problem not always required.
My current best guess on how it work starts with the fact that when taken in low doses that only last a few hours it results in upregulation of the opioid receptors. A high level pathway you have for pain and turning off the pain would be:
Pain stimulates nociceptors => increased substance P => increased cytokines, chemokines, etc => increased T-lymphocyte => increased β-endorphins => inhibit substance P
So with LDN less β-endorphins is needed to "turn off the pain" and you now get a shorter pain on / pain off cycle or really a shorter substance P cycle.
It's obvious first use is when the opioid receptors have been down regulated, but it has lots of extra benefits for instance, the immune response is time limited to the necessary duration of pain, reducing the likelihood of autoimmune complications. Additionally, diminished cytokine levels result in less hypothalamic activation, mitigating excessive appetite (not to mention better TRH response). This helps many with fibromyalgia may struggle with weight management. Numerous other secondary effects have been documented over time (last 40ish years), underscoring the multifaceted impact of low-dose naltrexone.
However, I agree that it is crucial to acknowledge that while this can effectively alleviate symptoms, it may also mask underlying issue(s). That could be something as simple as Zinc deficiency (due to diet or genetic predisposition) or more complicated such as classic like EDS.
Here is a presentation that I gave last summer. Slightly out of date with some details given what has been learned since, but the main aspects are all there. The presentation focus's primarily on explaining the gender dysphoria aspect the second half touches on the rest of the LGBT. https://docs.google.com/presentation/d/1PdGQlNfY39JX9iPowsBh... Overall it is complex with many possible variants.
Given the sensitive nature I am not rushing to publish, but working on getting it right. Once the key aspects were figured out there is a ton to investigate in this area.
This was actually one key point in helping me understand and figuring out the biology and genetics behind gender dysphoria and the rest of the LGBT.
Adult me is both horrified and impressed at this creation.
Option 4) The business core is turned into a library. Everything from the command line tools to UI all wrap this in other languages. Everything that is not the core is deleted.
With the C++ committee after the last two decades I am firmly in the I'll believe [shiny feature] when I see it camp.
many men who program have an avoidant attachment style?
That would be nice if it was true, but that is not how it plays out at most tech companies.
I have specifically targeted this in my career, thinking about engineering productivity and even spent a number of years working at a company that provided software for manufacturing and explicitly learning about lessons learned in that field.
What usually happens is maintenance costs are not taken into account when building a product and a team is not disbanded after building something. They continue to run the larger teams/orgs until one day some VP looks at the expenses and decides to simply kill the entire product.
So in a world of having hiring freezes, having someone come in to help reduce total costs, from AWS to headcount is a way to free up people and get "new hires" without additional cost.
Some companies and individuals seem to get this instinctively, but many are happy to not make waves and try to improve the system. For some in management, adding value without headcount doesn't mean anything for them individually so they wont.
Increasing the total value over total costs of teams and orgs is my jam. I can take over products that have high maintenance burden, but are valuable, dramatically reduce the maintenance burden, then turn around with my free headcount and go and do it again and again growing the total value produced. This is the 10X-100X game.
“Is C17orf69 related to cholesterol”
Vs
“How is C17orf69 related to cholesterol”
How questions by their nature can be lies. Been using chatgpt daily for medical questions but then I verify _everything_ it says via sources. It feels like 1998 Google in a way.
A dozen questions can save me tons of time. “My drunk college friend” who knows a lot but likes to boast that they know everything. Great for brainstorming, not great for fact checking.
I would absolutely love to try this model.
ooooo now there is a signal. Putting in the time and effort to find/get a jeweller to make me a custom ring with a lab-created diamond when no one will. Unique, expensive. Not something he can just order from the internet.
Because lets just cut to the chase. The diamond is all about the story, the signal and what it represents, not what it is.
I guess later in the game one doesn't mind randomly walking right by the castle just because it is the shortest path, just going to eat some time dealing with each guardian of course.
Same for swimming across a the river twice around a bend rather than just following the coastline.
Also there are 226 waypoints, the linked map is missing a lot...
I am not sure what it is trying to show. Was this the waypoints you had not done at the end of the game?