TDD, BDD, DDD, Agile, SAFe, Scrum, Kanban, XP… there’s a lot of ways to skin a cat write code in a professional environment.

I take pride in being a person who is a non-ideologue when it comes to my code. There are many good ways of working, and they are all context-dependent.

You can’t apply the same things that worked when you were a two-person startup operating out of the proverbial garage and expect them to work once your hypothetical unicorn has reached a thousand-plus developers. Even within the same organisation, processes that work for one team can be catastrophic when applied to their neighbouring team.

This series is a place to collect interesting things I’ve seen, read, or heard, along with some brief thoughts (often incomplete and/or inconclusive) that they provoked.

The rise of Whatever - eevee

This is probably the best post about LLMs I’ve read, which is probably why I’m the millionth person to share it. It really sums up my emotional reaction to their meteoric rise: “ew”, basically.

The power of the argument is that it identifies a theme that runs through recent tech changes, of which LLMs are just the latest and greatest example: the lack of care for quality, and the realisation from Big Tech that consumers mostly are fine with mediocre output.

Have you ever argued with someone who is seriously good at debating? I have. It sucks.

You’re constantly thrown off-balance, responding to a point you didn’t expect to. You find yourself defending the weak edges of your argument, while the main thrust gets left behind in the back-and-forth, and you end up losing momentum, confidence, and ultimately, the argument.

One of my close friends won international debate competitions for fun while we were at university (he’s now a successful criminal barrister), and he told me that the only trick in the book, once you boil it all down, is to make sure the conversation is framed in your terms. Once that happens, it’s all over bar the shouting.

“Saying the quiet part out loud” is a phrase I’ve just made up, to describe a method of building alignment on practices within a team. It’s the habit of stating why you are doing things a certain way, even when you would assume it’s obvious.

Anyone writing code professionally in December 2021 will remember the “fun” of the Log4J vulnerability. For those that weren’t - this was a critical security error that allowed attackers to run any code they wanted on your servers. The root cause was a logging library, Log4J, that is used by most projects that are writting in Java.

It’s usually used to write code something like:

log.info("Process completed successfully");

which will then appear in your logs, allowing you to track your application’s behaviour. Pretty innocuous stuff.

“Institutional knowledge” - the information that a company collectively knows - is a familiar concept to anyone involved in hiring processes. When an individual leaves who has knowledge the organisation needs, companies will organise offboarding sessions to keep that knowledge within the institution. Maybe they’ll even try to hire someone with similar experience.

Lots of companies similarly try to optimise for “Institutional learning”, especially smaller firms. This makes a lot of sense - smaller companies don’t have the resources to buy in extra experience, so they focus on rapidly expanding the experience of their existing employees. It also fits really well with the agile philosophy of fast development cycles to maximise your knowledge about customers’ needs.

Kit Wilson writes in The Spectator about Facebook’s new venture into the Metaverse, a concept that most of us probably hadn’t heard of until last week. To layout the roadmap for what our journey into this new digital reality might look like, Kit joins the podcast along with Tom Renner, a software engineer for NavVis. (12:55)

Coming to grips with DevOps metrics

In my team we have been considering ways to monitor our own performance, and finding some ways to contextualise our ongoing process and quality improvements. Like many other teams, we’ve landed on the DORA metrics as a good way of doing this.  These four key metrics are an easy way to understand what adjectives like “maintainable”, “reliable”, and “efficient” mean in practice when applied to software and teams, and the provide a way of comparing team performance across teams and over time.

Talk given at Codebar Festival.

If you wish to see my slides in their full glory, they are available on Slideshare.

Your work inbox is probably not a place that sparks joy. It’s full of people asking you to do things, complaints that something hasn’t been done, and 571 messages marked urgent.

In fact email is usually considered to be a hindrance, with many productivity guides recommending simply ignoring your email for large periods of the day, blocking out that time for focussed work. The consensus is that your work inbox is just a place that generates distractions, and contains never-ending to-do lists that nag away at you throughout the day.

Unfortunately since Elon shut down the Twitter APIs, the below method no longer works. Still, it was fun while it lasted, eh?

Gephi is a piece of software for visualising graph networks. It’s a powerful tool, and to use it fully requires significant domain knowledge that I don’t possess, but fortunately it’s still fascinating to play around with as an amateur!

As a techie, to me the obvious networks to graph are those created by the big Social Networks - YouTube, Facebook, etc. It’s not hugely surprising to find that mostly these graphs mostly aren’t available for querying, but excitingly there is a plugin that allows you to stream in live data from Twitter.

Last week I facilitated a session at XTC, where we discussed the new product development framework from Basecamp, Shape Up, led by Thomas Ankorn.

It was a really interesting discussion with people exploring the ideas openly, guided by questions posed by Thomas to get the conversation started.

I’ve summarised the points that came up in the discussion, reconstructed from memory and the collected post-its of scribbles at the end of the evening.

1. What problems does this solve?

We started by looking at the positives of the framework, trying to identify strengths that would help mitigate problems we have encountered in our own teams.