Read the full article at: jameshorsley.me/articles/where-is-meaning-part-one

TL;DR

After realizing how little I really understand what meaning is, where it comes from, or how it's shared, I've gone down a path of exploration to learn more. People have been philosophizing and contributing insights about meaning for thousands of years, and yet we still don't have any kind of final, conclusive "answer." While meaning is mysterious and fascinating, it is also practical and something we intuitively deal with all the time, without much thought. The rise of AI in our daily lives has made clarity about meaning more urgent, and so I'm writing a series of articles to share my own explorations. This first article creates initial scaffolding for thinking of meaning as sending and receiving signals. Signals can be any kind of sign that means something to someone, whether written words, speaking, singing, gesturing, or whatever. This signal processing falls under the heading of semiotics, which in turn relates to other fields like semantics (meaning in the signals themselves) and pragmatics (meaning created by the receiver). Future articles in the series will delve into distributional semantics (particularly relevant to AI), mental models (very relevant to humans), meaning from our environment (how can we function without it), and a much deeper look at pragmatics.

Read the full article at: jameshorsley.me/articles/think-like-an-alien

TL;DR

Like all living things, we adapt to our environment. A key way we do this is through a process called habituation, which helps us apply our limited attention to what matters most. Habituation is a superpower but also places blinders on us that can both trip us up and lead us to complacency. To help deal with the sharp edges of habituation, there are all kinds of practices we can adopt that add perspective, bring clarity, and make us feel more connected to our surroundings. Many practices have been around for millennia, such as those from stoicism and yoga, but more modern versions of those practices can make them feel more accessible to us today. As a sci-fi fan, a personal practice I use is to "think like an alien" from time to time and look at my surroundings as though these were my first moments on earth. We already live in someone else's sci-fi, we're just too habituated to notice.

Read the full article with interactive games and visualizations at: jameshorsley.me/articles/monty-hall-problem

TL;DR

This article is part of a series I'm writing about feature toggling, framed through my experiences working on the AWS Console. This first part in the series focuses on what our SDLC was like before feature toggles. Future articles will cover our path to adopting feature toggling, the feature toggling solution we built, and best practices and patterns I've personally landed on.

TL;DR

Back around 2013, when I was tech lead for the AWS Database Services User Experience team, our Software Development Lifecycle (SDLC) was more complex, stressful, and manual than I wanted it to be. This led to increased risk of launch delays and finding bugs at the last minute, which had knock-on effects for our future launches. This article uses a simplified, example set of feature launches to describe the challenges, and then provide lessons I learned along the way. These learnings fed into us building and adopting an internal feature toggling solution that I'll outline in future articles.

Lessons learned include: 1) automation is a mindset not a deliverable, 2) your production release pipeline should always be in a deployable state, 3) keep non-deterministic procedures as simple, repeatable, and constrained as possible, and 4) proactively evolve your SDLC to reduce cascading instability across launches