The grand version of the semantic web didn’t happen. A narrower version of it turned out to be a good fit in regulated finance. A while back, in a piece about agents, I dropped a comment while listing the technologies that have each had a turn (e.g., expert systems, neural nets, rule engines): “Ontologies (remember those? Well… it’s coming back. That’ll be a separate blog).” This is that blog. 2 different things travel under the word “ontology,” and only one of them has a future. There’s the ambitious one: formal logic, automated reasoning, machines inferring facts nobody stated. And, there’s the…
J O H N R A . M E Posts
The industry is building agents even for deterministic workflows and that’s a mistake. It feels a lot like the dot-com era, when everyone rushed to establish an online presence without questioning why, and we all know how that turned out. There is a meeting happening right now, in some conference room or some Zoom grid, where a perfectly reasonable process (the one with simple decision point, a lookup table, and a decade of stable behavior) is about to be rebuilt as an “agentic” system. Someone said the word agentic out loud, and the room nodded, because nodding at agentic is what rooms do in…
I’ve lived through 25+ years of technology hype cycles, and what they (and don’t) tell us about the one we’re living through now. There is a particular kind of meeting that happens in technology organizations at the peak of every hype cycle. The room is full of smart people. There is a slide deck. Someone presents a technology that is going to change everything; not incrementally, not in some narrow domain, but fundamentally, at the root, in ways that will render existing patterns of working obsolete within a measurable timeframe. The questions from the room range from credulous to breathless.…
When a measure becomes a target, it ceases to be a good measure. – Charles Goodhart There is a moment, in the life of every flawed metric, when it stops measuring the thing you care about and starts measuring how badly people want to look good on it. That moment is invisible while it’s happening. You only see it in the rear-view mirror, usually after the budget meeting where someone asks why costs tripled and outcomes didn’t move. This week, 4 of the largest technology companies on earth hit that moment more or less simultaneously (read the article on thestreet.com),…
AI is shifting the advantage toward people who know what to do, why it matters, and how it all fits together – not just those who go deepest in a single domain. For most of the last century, the career playbook was simple: find a field, go deep, become indispensable. Depth was the moat. Specialists commanded premium salaries, held the door on complex decisions, and were the first call when something went wrong. AI hasn’t made expertise irrelevant. But it has quietly restructured where the leverage lives. “It is tempting, if the only tool you have is a hammer, to…