Feel the pain.
I’ve been waiting eagerly for this episode to air — it’s my favorite of the season. As I looked through my notes, I was surprised to find that Kor and I first started working on scenes for “eps3.4_runtime-err0r.r00” as far back as January. The attacks against E Corp’s Hardware Security Modules (HSMs) are among the most complex hacks we’ve depicted on the show
Rich Hickey explained the design choices behind Clojure and made many statements about static typing along the way. I share an interesting perspective and some stories from my time as a Haskell programmer. I conclude with a design challenge for the statically typed world.
People often talk about a Person class representing a person. But it doesn’t. It represents information about a person. A Person type, with certain fields of given types, is a concrete choice about what information you want to keep out of all of the possible choices of what information to track about a person. An abstraction would ignore the particulars and let you store any information about a person. And while you’re at it, it might as well let you store information about anything. There’s something deeper there, which is about having a higher-order notion of data.
It was emotional.
Having a formal system means we can better support the growth of our engineers. We’re able to have more honest, open conversations about progress, promotions, and opportunity. While the framework is still relatively new, it is showing early promise at incentivising the kinds of behaviours we want to see in the team, and recognising the different kinds of value that people add.
We already have ideas on how to improve the framework further, and plan to continue iterating on it over time. We are releasing it publicly now, in the hope that it can help other companies that are thinking about how to grow and support their employees.
Medium’s growth framework looks well thought out and nicely structured.
A series of posts on options for creating a unified UI over disparate services.
The L16 replaces one big lens with 16 small ones and combines the images via software.
The old clustering of commodity hardware with software approach keeps on popping up in different contexts.
Some handy tips in here.
The real story in this mess is not the threat that algorithms pose to Amazon shoppers, but the threat that algorithms pose to journalism. By forcing reporters to optimize every story for clicks, not giving them time to check or contextualize their reporting, and requiring them to race to publish follow-on articles on every topic, the clickbait economics of online media encourage carelessness and drama. This is particularly true for technical topics outside the reporter’s area of expertise.
However there are general five general areas of interest that are always worth examining because they reveal mistakes with such surprising regularity. Specifically it’s worthwhile to find out how any system handles inputs, math, text, time and system resources.
Plenty of good testing advice.
I have long felt there is a shadow org chart, much like a shadow economy, where employees trade ideas, give direction, offer help, and spread culture. This shadow org chart is built bottom up by employees and is very different from the top down hierarchical org chart set by me.
I wanted to map this shadow org chart and find employees who have disproportionate levels of influence relative to their hierarchical position. I also wanted to see the influence centers and decision makers, and the directional current between them and the rest of the company.
Some fascinating analysis and data visualisation of a graph of influence.
An algorithm for splitting and sharing secrets.
The researchers found quite simply that the more people use Facebook, the more unhappy they are.
His idea was that if the price is falling that means the market is working, and no questions of monopoly need be addressed. This philosophy still shapes regulatory attitudes in the US and it’s the reason Amazon, for instance, has been left alone by regulators despite the manifestly monopolistic position it holds in the world of online retail, books especially.
I’ve spent time thinking about Facebook, and the thing I keep coming back to is that its users don’t realise what it is the company does. What Facebook does is watch you, and then use what it knows about you and your behaviour to sell ads.
Facebook is in the surveillance business. Facebook, in fact, is the biggest surveillance-based enterprise in the history of mankind.
A look at the internal data structure Emacs uses to represents buffers.
Management and leadership lessons.
They kill me.
Our goal should be to reduce these issues—we’ll never be truly rid of them. The first step is self-awareness. Ask yourself:
- “Do I know what I’m doing?”
- “Do I have a plan?”
- “Is this the simplest thing I could do?” (note: Simple ain’t easy)
- “What is the problem I’m trying to solve?”
Versioning is always a compromise between improving developer experience and the additional burden of maintaining old versions. We strive to achieve the former while minimizing the cost of the latter, and have implemented a versioning system to help us with it. Let’s take a quick look at how it works.
Explicitly modeling changes between versions via a DSL.
PumpkinDB is essentially a database programming environment, largely inspired by core ideas behind MUMPS. Instead of M, it has a Forth-inspired stack-based language, PumpkinScript. Instead of hierarchical keys, it has a flat key namespace and doesn’t allow overriding values once they are set.
The core ideas behind PumpkinDB stem from the so called lazy event sourcing approach which is based on storing and indexing events while delaying domain binding for as long as possible. That said, the intention of this database is to be a building block for different kinds of event sourcing systems, ranging from the classic one (using it as an event store) all the way to the lazy one (using indices) and anywhere in between.
In my experience, when an architecture review brings attention to a problem and proposed solutions from multiple perspectives, decisions become less controversial. When a decision appears to be obvious to a broad group (“Question: should we (or should we not) take backups of critical databases? Decision: Yes.”) how a decision gets made almost disappears.
Extending Haskell to support dependent types.
Putting the science into computer science.
Cogent and clear advice.
Lamar Odom’s story.
Monads are a solution to a specific problem: the problem of repetitive code. If you write enough code in a functional programming language, you start to notice that you’re writing a lot of suspiciously similar code to solve a bunch of superficially different problems. Wouldn’t it be nice if you could just write this code once and then reuse it, instead of rewriting it slightly differently every time? I’m omitting a lot of detail here, but this is effectively what monads allow you to do.
I used this to get edeliver to apply migrations in an Elixir umbrella app.