Fable 5, a Claude model, became available to me for a limited window. I could have spent that window shipping features. Instead I had it build something that would outlast the model itself: a context framework for running AI coding across several models.
The reason is a thing I keep circling back to when I work with coding agents. The less a human does by hand, the better the quality and the speed. Not because people are bad at the work, but because every manual step is a place to forget a constraint or approve something on autopilot.
So this is a design write-up, not a benchmark post. I have not run this on a long project for long enough to put numbers on it. What I can tell you is that using it felt more efficient, and I can show you the exact failure modes it was built to kill. If you want a graph, this isn't that article. If you keep watching your agent walk off in the wrong direction and you keep rewriting the same prompt, keep reading.
The pain I kept hitting
Before any of this, my problem was simple and expensive. The agent would drift. It would go off on something that wasn't the point, burn tokens on it, and I would spend real time pulling it back on course.
