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Pick two books at random and start building as you read them.

Do you want to build a profitable business or do you want to theorize how to build one?


> Do you want to build a profitable business or do you want to theorize how to build one?

I was part of a startup with an inexperienced angel who insisted on bringing in a CEO. The CEO made a good pitch to me that we would adopt the lean startup model, so I went along with it.

Anyway the moment he started, the book went out the door. We didn’t have time to discuss things like strategy and market positioning and hypotheses (though he used the word at every opportunity) but we had plenty of time to have risk assessment meetings and road maps and CRM system integrations (zero customers mind you), monthly 3 hour board meetings and weekly 2 hour “senior executive meetings”. The board and executive was larger than our headcount. I had brought an experienced team into the business with me and they were just flown into the ground with this inanity. (It turns out that despite what I’d been told, CEO had only ever been in corporate settings and had basically no experience with starting a business).

Anyway the outcome was as expected. I’ve been in startups my whole professional life and this was easily the worst experience of career.

The moral of this story is that building a business is hard and none of the books are going to tell you how to do it. So I agree with the parent comment. Pick a couple of books, read them, and get going. If things don’t work out, read a couple more.

But for God’s sake, keep your eye on the prize - have a clear vision, execute an early version of it, find some customers, iterate.


What's the plan, full (parallel) rewrite or refactor?


First order of business:

1) Fix the issues with email notification logic

2) Get them off of the very expensive & complicated AWS stack We've migrated staging and testing to a DO Droplet with DO MySQl/Redis stack. Moving to DO with plenty of headroom is a 10th of the cost of AWS!

3) After that, not sure at this stage. Most likely we will refactor low hanging fruit.

A ground up rewrite would require knowing all of the business logic. We'll just begin cleaning it up and getting it into a manageable state. We don't know what we don't know yet! :-)


I'm in a similar situation to yours, and I've kind of settled on a similar approach: put out the most pressing fires and reassess 3-6 months down the line. At first I had thoughts to refactor but now I just don't want to deal with the complexity, not to mention I have end-users pressing me. I'll have to tolerate the spaghetti, but at least make it produce correct output.

Best of luck with the migration to DO :)


I've found that Statistics is one of those topics that changes your world view about everything. You can consider pretty much any issue statistically, and that will enrich your perspective significantly. In that sense, Statistical Rethinking will help. However, it's a book on Bayesian stats, it's quite dense, and examples are coded in R. It may be overkill for web app metrics interpretation. For that you may be better served with basic stats & inference, frequencies, descriptive statistics, percentiles, basic distributions, data visualization (e.g., trend lines, scatter plots, boxplots, histograms), etc.

To be clear though, Statistical Rethinking is a beautiful piece of work. You can check out the author's lectures[0] and see how much they suit your needs.

[0] https://www.youtube.com/playlist?list=PLDcUM9US4XdPz-KxHM4XH...


> I speak four languages out of necessity, not by choice.

I also speak four languages and mostly agree with your take. I'm native in Spanish; English I learned gaming, and reading Tolkien as a kid. The other two, German and French due to a combination of self interest, education and travel. While I often fantasize about picking up a couple more (namely Norwegian and Japanese), I quickly become disappointed as I go through the motions all over again. It's a huge mental effort for a seemingly low _tangible_ ROI.

Sure, listening to music or reading in the target language and understanding most of it is quite the magical experience, probably similar to what cracking a secret code feels like; but there is no practical gain to it afterwards. It's a bit like reading/writing poetry: an intense but ephemeral enjoyment. More of an art form than anything else really. Unless, of course, you find yourself immersed in the language by way of relocation, then it truly does make sense to learn it. I do get your point with Dutch though: now you've got to figure out a fifth system for conveying an idea you're perfectly capable of saying in four other systems; it gets tiring.

I've been comparing it with programming languages lately. The question often pops up in HN: "what's the best programming language to build a backend in?" -- imagine you already can build a great backend in Python/Go/TS but you start picking up Rust only for the purposes of building said backend, what's the point? Just use whichever language you know best and build the damn thing already. Simple enough right? As is often the case though, this type of analysis is superficial; you may build a fantastic backend in say, Clojure, but then miss out on the opportunities a more popular language with a larger community may have to offer (e.g. Python). Writing Python may not necessarily provide general cognitive advantages over writing Clojure, but it will give you easier _access_ to the entire ML ecosystem, for instance. Does being capable of using more powerful tools help develop cognitive advantages?

I only read the abstract, but even if _Bilingualism Affords No General Cognitive Advantages_, learning a second language, English specifically, has unquestionably changed my life.


> We are already looking to move to other places and created a university-wide google sheet where we compare different countries and cities around the world for those kinds of categories.

Could you share a few places at the top of your list? As you yourself pointed out, it looks like the same story is playing out everywhere one looks, especially in the West.

Given the current situation, the more I think about it, the more I conclude that going fully remote from a low-COL location may be the better answer. Unfortunately I think this complicates things for founders to raise.

Also, this makes me think how utterly unprepared Germany is to receive all those immigrants needed to keep the economy working.

Best of luck with your plans.


> These days I do 20 minutes a day of mind control which involves nothing more than counting down from 9 to 1 repeatedly.

If it works for you that's great. However, I would say approaching meditation from a "mind control" exercise such as "counting down from 9 to 1 repeatedly" goes counter to its purpose and will hinder its full potential. If you're willing to experiment with other methods, try letting your mind wander and don't let it stick; just experience the ebb and flow. Twenty-minute sessions sound about right for me as well.


User name checks out.


Would you mind sharing your thought process to get from `daily_users` to `reqs_per_sec`? I'm playing with some estimations of `concurrent_users` for a basic website, and I'd be quite interested in the breakdown.


let's think step by step:

24hrs * 60mins * 60secs = 86400

86400 < 50000

QED


And also the monster investor happens to be a university. Why does a university need to manage such a huge endowment ($150bn of assets)? Further, why does a university end up investing in the rental market? Seems to me these are both standalone loop holes of our current economic system that will eventually need to be dealt with if we want to fix both education and housing. Until then we'll keep witnessing all sorts of distorsions and crashes.


A public university at that.


I'm a Python dev, learning Rust out of interest, but also considering its viability for Data Engineering. It would be helpful to know the equivalents of the following libraries: Pandas (Polars), Prefect/Airflow/Orchestration, Flask, SqlAlchemy, psycopg2, requests, BeautifulSoup.

Thanks!


Flask -> Axum (see also https://www.arewewebyet.org/topics/frameworks/#server)

SqlAlchemy -> Sqlx or SeaORM

psycopg2 -> postgres and tokio-postgres

requests -> reqwest

BeautifulSoup -> scraper

Searching for packages on lib.rs, crates.io or github usually works.

There will be differences of course. The ecosystem is not as complete. On the other hand, writing the code and having it work the first time is easier once you know the language.


Brilliant, I'll be playing with these once I reach the more advanced material in The Book. Ty.


1. Could you share a bit about your stack? I'd be specially interested about the data engineering side of things if possible.

2. As a SWE, how deep into biology/genetics concepts have you had to go during your tenure?


1. I'm on the product engineering side rather than data, but from what I know, Scala is still heavily entrenched. New projects are all in Java; other languages are effectively disallowed.

2. I learned a fair amount in the 2017-2019 time frame but with the pandemic and increased specialization my pace has decreased. Lunchtime talks are just not as fun to attend on Zoom. Another possible explanation is that my curiosity has been satisfied, and someone with more curiosity could get more out of it.


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