Rarely seen him make a bad call

The 2018 State of JavaScript survey is out. They got 20,000 responses and have some delicious, delicious data. I'mma thread in some highlights:

First up: JavaScript flavors. There's TypeScript at 47% adoption, a tad higher than npm's own survey results (which said 46%). npm's survey is coming up again soon and will ask about TypeScript in a lot more detail.

I really, *really* like SoJ's "would not use again" question, which lets people who've abandoned a tech self-identify. This is noticeable in the graph above with Flow users -- 41% of people who've used Flow say they wouldn't use it again.

Now JavaScript frameworks. It's been a full year since npm's survey, so these numbers differ from ours in the directions I expected:
React 65% (vs. 60%)
Vue 29% (vs. 24%)
Ember 5% (vs 4%, I was expecting a bigger rise)

But there's a shocker in here: Angular.

npm's survey had Angular at 40% last year and SoJ has it at either:
- 58% (if you include those who don't want to use it again)
- 24% (if you count only those who like it)
Since npm's question didn't ask if they intend to *continue* using it I think that might explain this.

1/ I am seeing more and more founder secondary in venture rounds (Secondary = founders selling some of their shares before some other shareholders are able). Series B-D. I see both as an investor and through entrepreneur circles.

2/ I like secondary for entrepreneurs. Moderation is key but in a lot of situations I think it helps accelerate the co. Lots of very smart investors disagree. Here are my thoughts.

3/ Magnitude: My basic rule of thumb from what I see is market is 4+ yrs and up to 10% of founder’s equity stake with some $ cap that makes sense given stage etc. (typically <$10m)

4/ The entrepreneurial journey is brutally hard. Giving some financial relief helps remove one piece of pressure. I don’t think that secondary in the magnitude mentioned impacts the drive/persistence of great entrepreneurs.

5/ That secondary means they will be able to just sleep knowing they can pay their kids’ tuition. Secondary will make most founders better at their jobs, thus accelerating the co.

❤✈️🌎 2 years ago today @JamesIvings and I sold all our belongings and left the UK to travel for a year. We've never been happier and we have no plans to ever return there 🙂

Thread 👇

Since then we've started a remote web dev company @SquarecatWebDev and been lucky enough to have completed several freelance projects 💻 that have kept us on the road.

In the last few months we've become a huge part of this amazing new Maker community and have found so many new friends from @makerskitchen, @women_make_ and several others! 🥰

We love travelling together (even if I'm only a glorified laptop watcher 😒) but we're both much happier being able to share our ideas outside of our own little bubble and our products have benefitted too!

Here's to another year of nomading with my favourite person and to the Maker community continuing to grow with our help! Maybe one day we'll all get to meet each other ✌️ 💛

This post is pretty bizarre, but it manages to hit on so many false beliefs that I've seen hurt junior data scientists that it deserves some explicit

(1) The notion that R is well-suited to "building web applications" seems totally out of left field. I don't feel like most R loyalists think this is a good idea, but it's worth calling out that no normal company will be glad you wrote your entire web app in R.

(2) It is true that Python had some issues historically with the 2-to-3 transition, but it's not such a big deal these days. On the flip side, I have found interesting R code that doesn't run in modern R interpreters because of changes in core operations (e.g. assignment syntax).

(3) "Most of the time we only need a latest, working interpreter with the latest packages to run the code" -- this is where things get real and reveal some things that hurt data scientists. If this sentence is true, it's likely because you don't share code with coworkers.

(3) Really is a broader issue in data science: people only think of what they need to do their work if no one else existed and code was never maintained. Junior data scientists almost always operate on projects they start from scratch and don't have to maintain for long.

Rio de Janeiro, 1920. 🇧🇷

São Paulo, 1910. 🇧🇷

“Arpoador”, Rio de Janeiro, 1900. 🇧🇷

“Avenida Paulista”, São Paulo, 1902. 🇧🇷

Recife, 1885. 🇧🇷