AI’s “Magic Box” Is Anything But Simple—The Hidden Engineering Burden
Tom Tunguz shows that today’s LLM‑powered apps still require massive pipelines, tool‑orchestration, observability, and guardrails—essentially the same hidden infrastructure that plagued 2015 ML systems. The hidden technical debt now lives in data stores, retrieval‑augmented generation, and cost‑control layers, turning promised simplicity into an iceberg of engineering work.