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.
Yesterday marked the launch of the latest release of MCP, the protocol championed by Anthropic and a founding member of the Agentic AI Foundation back in December 2025. MCP had been on my radar since the middle of 2025, when I integrated into a proof-of-concept project. When the last version of the spec launched in November 2025 (2025-11-25 spec) I did in-depth research on the new features. And I've been tracking the latest release for many months, particularly because of the potential of Skills over MCP. So it's great to see the launch.
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.
Later this month I will be speaking at Engage 2026, delivering the session Super-Charging Your AI with Domino REST API on Wednesday 24th April at 14:05 in Room E. The session will showcase a variety of AI techniques for integrating Domino applications with agentic interfaces or agentic engineering. The session demonstrates the art of the possible, but is primarily designed to provide the information needed to make the right choices when integrating Domino data with agentic solutions.