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Since this documentation heavily refers to Technical Due Diligence processes, I thought I'd offer an "AmA" since this is what I do for a living (personally have conducted 400+ Tech DD projects).

Disclaimer - I'm not a GitLab employee and they are not a client of mine, but their documented processes are very synonymous with what I do.


It's a pity that docker swarm did not make it. It wasn't perfect but it was a lot simpler to setup and manage than kubernetes.

If you can get away with it, vanilla docker hosts running docker compose provide most of the same benefits with a fraction of the cost. For most startups, that's a great way to avoid getting sucked into a black hole of non value adding devops activity. You lose some flexibility but vanilla ubuntu hosts with vanilla docker installs are easy to setup and manage. We used packer and ansible to build amis for this a few years ago with some very minimal scripts for container deploys.


There are organisations varying from grassroots to global where you can participate in such purchases with nominal sums, and end up with small parts of land in your name, collectively owned with other participants, or probably something in between.

Here is one (that I know about because my employer currently offers an option to use some of our open source contribution rewards for that): https://www.helsinkifoundation.org/


I only started at Ecosia in 2016, but I feel you.

Not sure if this is appreciated on HN (I only saw a guideline about posts, not comments), but if this piqued someone's interest, we have a bunch of open positions at the moment: https://ecosia.workable.com/


$450k is approximately the package (salary, bonus, 1 year of RSU vesting) for the “career level”, the point in the ladder that all devs are expected to make if they’re not fired. AppAmaGooBookSoft people can tell you the exact name of it at their firm.

It’s not insane, it’s the market.


I think I am in quite a similar position to you: after secondary school here in Ireland, I didn't consider any universities outside of my home town (pretty much because I didn't know a single person who was considering bigger and better options, so it genuinely didn't cross my mind to apply to Stanford, CMU, MIT etc.) so I ended up going to a fairly average and not very well known university to study electronic engineering for my undergrad.

I went on an exchange for a year to UCLA and this was when I started to feel something similar to the sentiment you're expressing here.

I'm now in my 3rd year of undergrad EE and for the last year I've been trying to fast track myself into the AI / ML field as I've been increasingly regretting my EE major and becoming more and more interested and passionate about ML (particularly the intersection of ML, altruism and design): I got Norvig & Russell's textbook and read it in outside of my engineering classes, read less technical books like Nick Bostrom's Superintelligence for motivation / food for thought, made a simple collaborative filtering recommender system using the movielens open source dataset, moved away from the web dev stuff I'd been doing in 1st and 2nd year and tried to hone in on improving my algorithm and pure CS skills, watched a load of AI / ML videos to try and get a better sense of who's who, where's where and what's going on etc. in the field. The "dream" (I use that word loosely) is to do the google brain residency program instead of a PhD, or the U Chicago data science for social good fellowship, so I've been trying to figure out how to get myself into good shape for either of them.

It's been overwhelming at times, largely because I feel like 1) I'm not in the "right" major, 2) I've had a taste of but no longer "go to" UCLA (or an equivalent high ranking university) and won't be graduating from there so will need to work hard to stand out against the competition for placements / fellowships / internships 3) I don't have mentors or peers who can help me navigate the field (I have a great relationship with a lot of my engineering professors but again, it's not ML). So I'm sort of trying to make sense of it all myself. It's reassuring to hear there are others feeling similarly and it's great to hear all that you're doing!

On a positive note, I suspect you may be overestimating the educational superiority of the top tier schools (I know I certainly did before I went to UCLA) but at the same time I don't think it's fair to completely disregard the big unis and just say "circuit theory is circuit theory" and forget about it. While I was there, I really didn't notice all that much of a difference in terms of course content or even teaching quality - the biggest difference was there were an awful lot more high achiever students in my EE classes compared to in my home uni in Ireland, and there was a much more impressive "career fair" and internship opportunity scene than at home (think Irish Cement vs Hyperloop One).

You seem to be doing everything right. I think I was edging down a "burnout" path a couple of months ago with fretting over what you're saying and over my own EE vs CS major "challenge". I've tried to take a step back and remember that there's no one enforcing a particular pace or path for me, hopefully you won't let the fretting get in the way of your passion which almost happened to me.

Just wanted to comment this to warn you about the burnout thing, reassure you somewhat about top schools and throw in a few links you might find interesting for good measure!

You mightn't find any of these links below helpful, you very well may be much more well read than myself but I thought I'd link these here anyway. The first is a reassuring AMA on reddit from the google brain team (particularly the comments where the team talk about all the different backgrounds everyone has at google brain). The second is a list of programmes, fellowships, resources and random AI / ML related pages I've encountered in the last year (amongst a lot of other stuff ). The third is a playlist I made for a friend on interesting AI / ML videos which you most likely will have seen before but you might just enjoy anyway. The quick interviews are cool if you haven't seen them already.

Anyway - best of luck!

https://www.reddit.com/r/MachineLearning/comments/4w6tsv/ama...

http://sharedli.st/cvigoe40g9

https://www.youtube.com/playlist?list=PLxB_QX9z7BFSc7VRmy5zt...


I have shipped React and React Native apps. I've built nontrivial open source infrastructure/devops tools that are used at Companies You Have Heard Of. I've done backend stuff for NASDAQ-listed companies.

I'm not a web or mobile developer. I'm not a "devops engineer", and I'm not a "backend engineer." I'm a problem-solver. But to many (most?) companies, this means that I need to be classfied into a track. I need to be an X or a Y or a Z. I can't adopt those roles when necessary--I need to be slotted in and just go.

That doesn't really work for me. Which is a major reason why I'm a software consultant now. I'd go do a full-time job that respected my complete disinterest in being pegged to a particular role and was able to give me the latitude to solve cross-cutting problems at scale. But that's a hard role to define, a hard role to hire for, and a hard role to evaluate--which is why they, and other generalist-focused roles, don't often exist.

It's easy to get a job. I can walk into almost anywhere in Boston if they're hiring and get an offer; I interview extremely well. I can't get a job that actually leverages my skills.


I'm in the range of 3-5 years out of undergrad, working at a quant firm. My total gross comp for this year will be about 400-450k, majority of that is bonus.

By quant firm I mean either a proprietary trading firm (no outside investors) or a hedge fund (takes outside money), but not a bank.

I have a CS background but have self-studied in stats, and received mentorship from people with strong math backgrounds.

Main advantages of quant shops (doesn't apply to banks) over working at Google/FB/Netflix etc:

- small company size, startup style working environment, but big corp pay (or more)

- more varied/interesting work, e.g. mix of distributed data processing, high performance numerics, or performance optimization in latency sensitive code

- compensation paid purely in cash, no stock options/RSUs


That would be a sound assumption.

Why else should a Silicon Valley billionaire give 300k to someone running for attorney general in a Missouri? Is he just interested in justice being pursued in a small Midwestern state he doesn't live in, that he is neither from, nor studied in, nor has his major business interests in?

$300,000 is a sizable donation for someone running for attorney general in a low key state.


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