I spent three months working full time to get a job. Here’s how it all went down.
This is a long article. If you don’t like reading, here are the highlights:

• Yup, hiring is messy.
  
• Build empathy for your candidates.
  
• I got a job.

I tapped my network, asking for intros to recruiters, VCs, and specific companies, and I was off to the races. I accepted pretty much any intro so that I could get a feel for the different opportunities out there, and because as I talked to more people about what they needed, I could get a better sense of what I wanted. It worked. After a couple weeks of talking about CTO and VPE roles (because those are merged often enough at small companies), I realized I wanted less proper management responsibility and more focus on solving technical problems.

Hollywood portrayals of computing superstars are more rooted in comic-book super-heroics than the realities of software development. Except that in programming, superpowers do exist. Fabrice Bellard has them.

Computing in the movies is hard to recognize: Typographical errors are non-existent, crackers break through tested defenses in seconds, and practitioners create twenty-function-point programs in fewer keystrokes than the count of bullets whizzing by their heads. Hollywood portrayals are more rooted in comic-book superheroics than the realities of software development. 

Except that in programming, superpowers do exist. Fabrice Bellard has them.

A 10x programmer is, in the mythology of programming, a programmer that can do ten times the work of another normal programmer, where for normal programmer we can imagine one good at doing its work, but without the magical abilities of the 10x programmer. Actually to better characterize the “normal programmer” it is better to say that it represents the one having the average programming output, among the programmers that are professionals in this discipline.

The following is a list of qualities that I believe make the most difference in programmers productivity:

• Bare programming abilities: getting sub-tasks done
  
• Experience: pattern matching
  
• Focus: actual time VS hypothetical time
  
• Design sacrifice: killing 5% to get 90%
  
• Simplicity
  
• Perfectionism, or how to kill your productivity and bias your designs
  
• Knowledge: some theory is going to help
  
• Low level: understanding the machine
  
• Debugging skills
  

sort: File sort utility, often used as a filter in a pipe. This
command sorts a text stream
or file forwards or backwards, or according to various
keys or character positions. Using the -m
option, it merges presorted input files. The info
page lists its many capabilities and options.

• To reduce latency — Because the request is satisfied from the cache (which is closer to the client) instead of the origin server, it takes less time for it to get the representation and display it. This makes the Web seem more responsive.
  
• To reduce network traffic — Because representations are reused, it reduces the amount of bandwidth used by a client. This saves money if the client is paying for traffic, and keeps their bandwidth requirements lower and more manageable.
  

Let’s dive together into the world of web content caching with Nginx. Starting with basics we will quickly move to more advanced topics and see some real world examples. If you can make it to the end of this blog post… You will bear the title of a “Caching King”.

Today I will show you how to make the internet faster and more stable. How you can easily adapt Nginx’s caching, to boost your applications.

We will start with caching concepts and then jump into available Nginx caching configuration - directives. I will explain why they are useful and how you can profit from them. Armored with the right knowledge we will fight our way through a real world example.

Do you want to code a chat app? Here you’ll see how to do it the hard way. I show how Redis Pub/Sub works in detail, all the way down to the bits and bytes! This is the first part of a series of deep dives into Redis.

At Pusher, instead of treating our system as a stack of black boxes, we like to get our hands dirty and poke around. Today we’ll roll up our sleeves and dismantle the drivetrain of Pusher’s pub/sub system: Redis

In short, skip lists are a linked-list-like structure which allows for fast search. It consists of a base list holding the elements, together with a tower of lists maintaining a linked hierarchy of subsequences, each skipping over fewer elements.

Skip list is a wonderful data structure, one of my personal favorites, but a trend in the past ten years has made them more and more uncommon as a single-threaded in-memory structure.

My take is that this is because of how hard they are to get right. The simplicity can easily fool you into being too relaxed with respect to performance, and while they are simple, it is important to pay attention to the details.