More Than We Can Tell

If AI’s design output keeps failing the fundamentals, the obvious fix is to teach it the fundamentals. Write them down. Package them as instructions the model has to follow every time it generates — hierarchy, contrast, balance, proximity, rhythm — with examples, templates and rules for when each applies. People have done this. I’ve built a few such systems myself, with nested files and reference templates and careful checklists. They help. They also break, and the more elaborate they get, the more reliably they break. The surface reason The first explanation is mechanical. A model working through long, layered instructions doesn’t reliably attend to all of them. It weighs, compresses and skips what it judges unnecessary. You can read that charitably, as a system trying not to spend your time and money on what doesn’t matter, or less charitably, as a system doing the minimum. Either way, the parts it skips are rarely the parts you’d have chosen. But I don’t want to rest anything on…