Per-token costs are collapsing. Total AI coding spend is climbing anyway. That isn’t a contradiction. It’s a 160-year-old paradox doing exactly what it has always doing. Somewhere in second quarter there will be a budget review where two slides will appear to be in disagreement. One shows the price of a thousand tokens, and the line slopes down and to the right, the way the cost of a maturing technology is supposed to. The next slide shows the monthly spend on AI coding tools, and that line climbs up and to the right, steeply, and nobody in the room can…
J O H N R A . M E Posts
In Part 1: “Ontologies, Back in Fashion”, there are 2 things traveling under the word “ontology”. The first is the ambitious version (automated reasoning, machines inferring facts nobody stated) which is “roughly where it was 20 years ago: academic, brittle, confined to narrow domains”. The second is the humble version; an agreed vocabulary, stable identifiers, a declared column meaning that two systems can check without holding a meeting. Part 1’s claim is that the humble version is quietly working well in the regulated finance, kept alive by regulatory mandate rather than hype. The LLM angle was flagged as a “plausible…
In a span of couple of years, 3 new job titles in AI space have appears. Not all survived. At first, the hot new role in AI was the prompt engineer. For a few months, LinkedIn was filled with people who had appended it to their headline. Then prompt engineering was declared dead (read this think-piece). The indispensable skill become context engineering. While prompt engineering was about “one-off tasks, content generation, format-specific outputs”, context engineering was about “conversational AI, document analysis tools, coding assistants”. Now, the new job title is the product engineer: the person who, armed with an AI…
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…
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…