Phil Booth's Blog

Before the advent of LLMs, my hobby was failing to finish software projects that I hoped might be generally useful to a wider audience.

I reckon I’ve drafted and then deleted a version of this post at least 10 times in the last 12 months.

Last summer I was about to start a new job where I’d be working with the Go programming language on a daily basis.

This post is an expansion of a comment I made on HN recently and continues my Extreme Learning series.

When engineers discuss program design and system architecture, a common source of misunderstanding is concurrency.

Every technology stack has idiosyncrasies that can trip people up when they first encounter them.

There’s a fascinating chapter in Keith Johnstone’s Impro, called Status.

This post is an extension to a talk I gave recently at work.

Recently I built a system that uses vector search to logically truncate long documents and retain the most significant parts according to some search term.

For the last ten months or so I’ve worked on integrating GPT (various flavours) with a large production codebase.

Production outages are great at teaching you how not to cause production outages.

Previously for Extreme Learning, I discussed all the ways I’ve broken production using healthchecks.

One reason I like working at startups is you get to wear many hats.

One of my stock interview questions goes: “When picking between dependencies to use in production, what factors contribute to your decision?”

As engineers we spend a lot of our time debugging problems, yet it’s rarely taught as a skill in its own right.

There’s nothing earth-shattering here, but I can recall that each of these principles were not obvious to me at some point in time.

I’ve always wanted a dog, but could never get one because I lived in rented accomodation.

Last week I received the result of my WSET level 3.

Automating your release process saves time, eliminates tedious busywork and reduces the likelihood of mistakes when cutting a new release.

Historically, the Firefox Accounts (FxA) codebase was organised as separate repositories because it’s deployed as separate microservices in production.

Along with all the fun, creative stuff it enables you to do, programming sometimes requires you to carry out boring and repetitive editing operations.

JavaScript’s Array and Promise types compose nicely with functional programming idioms to control concurrency without recourse to 3rd-party libraries.

Time passes and it’s easy to forget about all the cool stuff you did or lessons you learned.

For Christmas I bought myself a Garmin Forerunner 645, after becoming irritated to the point of distraction by my Polar Flow M430.

Recently I sat my WSET level 2 and did pretty well.

Recently I wrote about how Rust macros make it easy to refactor repetitive code that might otherwise become annoying in a strongly-typed language.

About a month ago, we had an outage caused by a slow-running query in MySQL.

Refactoring boilerplate code is always easy in dynamically-typed languages, but sometimes takes a bit more effort when constrained by strong typing.

Richard Charles Maxwell Booth 25th June 1948 - 17th June 2018

Here’s three little Rust tricks that I learned in the last week or so.

Let’s say you have a huge amount of JSON data and you want to parse values from it in Node.js.

“Bad performance hurts user engagement” is a sentiment that feels intuitively true but can be hard to sell in product conversations.