AI Isn’t Magic — It’s a Stack

Artificial Intelligence. Two words that trigger everything from excited coffee chats with my mates to boardroom FOMO to outright apocalyptic fear. AI has dominated every conversation I’ve had for the last six months. Everyone wants a slice of it. It shows up in product roadmaps, vendor decks, job specs, and shareholder updates. But when I scratched beneath the surface, I found a messy pile of buzzwords and vague ambition.

I don’t know about you, but I like simple. So here is my attempt to make AI simple.

If you’re leading digital delivery, managing platforms, or just trying to figure out what AI means for your portfolio, this is your practical intro. There are buzzwords, but I explain them. There is no hype because I don’t have to impress anybody. It is just a clear look at how AI is structured, what matters now, and what’s coming.

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Bold Predictions or Hype? Tech CEOs on AI’s Impact on Software Development

I’ve never seen a hype cycle like this one. Huge sound bites about AI — specifically, generative AI. Depending on who you ask, AI is either a helpful copilot or it’s gunning for your entire dev team’s jobs. As usual the truth is probably somewhere in between. But with so many CEOs talking up how much code AI is generating, it’s worth stepping back to ask: are they predicting the future, or selling it?
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Another Silver Bullet? What AI Tools Can Learn from the Last 50 Years of Developer Hype

The emergence of AI coding assistants such as GitHub Copilot, Amazon CodeWhisperer, and Claude 3.5 Sonnet has stirred debate about their long-term impact on software development. I’ve been in this game a while, which means I approach software innovation with a healthy dose of scepticism. I have seen lots of fashion trends — waves of developer productivity tools — some impactful, most not. From 4GLs to IDEs to low-code — each one promising to change the game, then fading into the background. Sound familiar? Every year there is somebody claiming they have a tool that can write your code for you. Is AI just the latest wave? I wondered if looking back at those old patterns — the hype, the crashes, the survivors — might tell us where this one’s going. Do those patterns from history tell me anything about the current trajectory of AI coding tools? The answer? Yes and no. Which, if you’ve ever worked in software, is probably the only honest answer you’ll get.
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