AI Opinion & Analysis
There was no dramatic moment, no single announcement, no headline that said it plainly. But somewhere in 2026, without a parade, open-weight models stopped being the scrappy underdog and became the default sensible choice for a huge slice of real work. It was a quiet war, and the open side won more of it than anyone expected.
Every executive survey says AI budgets are going up. A quieter set of numbers says most of that money is not paying off. Only about a quarter of enterprise AI initiatives deliver the ROI they promised. That gap is the most interesting, and least discussed, story in corporate AI, because the reason for it is almost never the thing everyone blames.
Read more: The uncomfortable truth about AI ROI in the enterprise
I want to make a small, cranky request on behalf of clear thinking everywhere: stop calling everything an agent. The word has been stretched so far that it now means anything from a genuinely autonomous system to a chatbot that calls one API. When a word means everything, it means nothing, and the fuzziness is not an accident. It is marketing.
For a long time the comforting story about AI went like this: sure, it can crunch numbers and play chess, but it will never do the human things, the creative things, the intuitive things. That was the line, repeated confidently, for years. I want to gently point out that the line keeps moving, and it is moving in a direction that deserves more honesty than it usually gets.
Read more: AI is getting good at the things we were told it never would
Every model launches with a splashy chart and a breathless thread. Almost nobody reads the boring document that ships alongside it, the model card, with its dull sections on training data, limitations, and known failure modes. I read them, every time, and I think it is one of the highest-value habits you can build in this field. Here is why.
Read more: Why I still read the model cards nobody else reads