Some time ago I came across an article talking about the XY Problem. I don’t remember the article or its specific context, but the XY problem concept is well-documented. I’ve seen it very often in requirements specifications and IT professionals asking for support on chat rooms and forums. But it’s also relevant to working with AI as well.
Wednesday 12th August bring a solar eclipse. In UK it’s not a total eclipse, but will be about 90% totality. My adoption of AI and expertise has increased massively over the last year, to an extent where I am finding plenty of innovative uses of AI. Viewing a solar eclipse safely is crucial, no one should ever look directly at the sun. But AI gives a lot of potential for maximising your viewing experience. With ChatGPT and Google AI Mode, amongst others, there is a lot you can do for free. With children now on summer holidays, it’s a great opportunity to get experience of AI (together?), build a safe viewing option, and hopefully have a great time.
I didn't study Computer Science at university. Instead I studied Classics - Latin and Greek. This meant translating texts from a variety of authors and genres, one of which was Plato.
Without a doubt AI has revolutionised software development and is here to stay. But we're constantly adapting to the change, and I'm reminded of the Tuckman model. However, it's worth also remembering where the pain points of the past have been beyond just writing code.
I’ve been using AI for over two years, progressing from clever auto-completion through vibe coding to agentic engineering. Recently I iterated for a couple of weeks over a prototype application. The biggest problems came down to a single word, a term I’m found myself using more than any other over the last few weeks. And it’s not exclusive to a single project. It’s a term that’s been used across coding work, research work, everything.
When I was at school in the late 1980s, our school got a computer. Just one, in the library. I remember using it for some document I wrote, I can’t remember what, on a floppy (yes, actually “floppy”) disk. At university we had computer labs, but I still wrote my undergraduate dissertation on an electronic typewriter. My MA was written on the computer and during my PhD I published two articles on an “electronic journal”. But computers had not had a significant impact on education.
Fast forward to now, and most schools have Google accounts for their students, even at primary school. During lockdown lessons were delivered on Microsoft Teams. Online applications are not only used for teaching Computer Studies, learning Python, HTML and CSS. They’re also used for maths homework and times tables, as well as pointing to videos on BBC website and others.
But computers and mobile devices have just replaced text books and written homework. They have changed where learning happens, not how learning happens. But I think AI should create a monumental change in the steps through education. The question is how long it takes academics to realise it.
Last week I spoke at Engage conference in KAA Arena Ghent. I’ve been attending Engage since 2010 and only missed one of the annual conferences since then. It was my first conference, so it’s always held a dear place in my heart. Although it’s many years since I developed for Domino REST API, my work over recent months gave me experience to build innovative proof of concepts using Domino REST API and experience of various models and AI agents to integrate the API with various interfaces.
AI usage has evolved over the years as the power and limitations of LLMs and agents have progressed. The community has learned that they needed ways to provide additional abilities. Coding clients have adapted to provide those capabilities. Thankfully the IT ecosystem has changed dramatically since the birth of enterprise IT, so open source and standards have become the default mechanism instead of a last resort after community pushback. But we’re starting to see yet another approach, one I’ll call Token Engineering.
AGENTS.md has become the de facto standard for directing your agent. Claude Code had CLAUDE.md but with AGENTS.md becoming part of the Agentic AI Foundation last year, even Claude Code now recognises and uses AGENTS.md. But the benefits of AGENTS.md are now being discussed and challenged in academic circles. However, maybe what’s being discussed is just the first iteration. And just as the AI world went through Prompt Engineering and then Context Engineering, maybe the next phase (or a next phase) is “AGENTS.md Engineering”.
The ability of AI to generate software applications has taken gigantic leaps forward in just the last few months. A team of agents using Claude Opus 4.6 wrote a C compiler with minimal human interaction. In the press release for Opus 4.6 Anthropic build Claude with Claude. I personally use coding agents more and more, and I’ve seen significant rapid application development with AI.