A stronger model launches, developers start using it, and increasingly difficult programming tasks become possible.
Fable raises a different question.
What happens when the most capable model is also too expensive to use for everything?
A complex architecture problem may deserve a frontier model.
But developers also use coding agents for repetitive implementation, updating tests, reviewing files, creating documentation and following patterns that are already well defined.
Should all of those tasks receive the same expensive model?
That is where model routing becomes interesting.
Instead of selecting one AI for an entire development workflow, coding systems could eventually choose different models depending on the task.
But cost isn't the only consideration.
Context quality, privacy, speed, testing and the tools surrounding the model could all influence the result.
This suggests that AI coding may be moving away from:
Best Model = Best Coding System
toward something much more complicated.
So what role do coding harnesses play? Can better context make smaller models competitive? And could AI coding platforms eventually route models automatically?
👉 We explored the full shift and why Fable matters on WikiGlitz.
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