SocialCops’ 10 (base 10) Engineering Commandments — the values that drive everything for the #Engineering Team #InsideSocialCops 🙌

(Thread👇) Tell us if you can relate to any of these? Do you have your own values that guide your decisions? Share them with us! ⛳

0. Coder != engineer

Coders focus just on writing code to make something work. Engineers take a much wider view, focusing on both the problem and every aspect of the solution. 🤓
1. “Import lib”

It's not wise to waste time building tools or libraries if there’s already something that does the same job! Wherever possible, extend existing libraries and contribute back to the community. 💁‍♀️
2. With great power comes greater responsibility

Every choice we make on our platform and every feature we build stands up to a responsibility — helping people make more data-driven decisions and bring about real change for millions of people. 💪
3. Fail fast and keep learning

Failing fast is about doing lots of fast iterations and learning from each, rather than getting stuck on one solution or decision. 👊
4. Know thy build

Knowing your build inside and out is a crucial part of engineering. It’s not enough to know what will work and when it’ll work. It’s just as important to know what won’t work and when it won’t work. 🚧
5. #ItIsNotMagic

There is never a magical problem or a random occurrence. We expect our engineers to figure out what caused a break, not throw their hands in the air and proclaim that it’s just broken — find what is happening under the hood. 🕵️‍♀️
6. Measure whatever is measurable

While our products help organizations make better data-driven decisions, it is important for us to measure everything that we can to figure out the next course of actions. 📊
7. Automate whatever is repetitive

Our base tendency should be to automate wherever possible, rather than doing tasks manually — automation gives us more time to work on building the actual product. ✔️
8. Premature optimization is the root of all evil

Pick the right battles to fight at the right time. If you optimize too early, you’ll spend and re-spend lots of time and still come out with not the most optimized solution. 🙅
9. When in doubt, ask!

Stuck or confused? 🤔 Just ask your fellow engineers! Someone will have a solution, or at least an idea to help you get started on the right path. ➡️
We hope these were helpful — whether you’re an engineer interested in working with us or you’re forming your own team’s engineering commandments! :) Interested to learn more about #engineering culture #InsideSocialCops? Check here: https://t.co/QTVs9tf1tj

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global health policy in 2020 has centered around NPI's (non-pharmaceutical interventions) like distancing, masks, school closures

these have been sold as a way to stop infection as though this were science.

this was never true and that fact was known and knowable.

let's look.


above is the plot of social restriction and NPI vs total death per million. there is 0 R2. this means that the variables play no role in explaining one another.

we can see this same relationship between NPI and all cause deaths.

this is devastating to the case for NPI.


clearly, correlation is not proof of causality, but a total lack of correlation IS proof that there was no material causality.

barring massive and implausible coincidence, it's essentially impossible to cause something and not correlate to it, especially 51 times.

this would seem to pose some very serious questions for those claiming that lockdowns work, those basing policy upon them, and those claiming this is the side of science.

there is no science here nor any data. this is the febrile imaginings of discredited modelers.

this has been clear and obvious from all over the world since the beginning and had been proven so clearly by may that it's hard to imagine anyone who is actually conversant with the data still believing in these responses.

everyone got the same R

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