Rethinking Systems for AI
Most software systems were designed for a world without AI.
Not in the sense of lacking ML features — in the deeper sense of having an architecture shaped by assumptions that AI changes. Assumptions about where intelligence lives, what questions systems should answer, what "the right data model" looks like.
Those assumptions are worth examining.