Hidden Technical Debt in AI: The Infrastructure Complexity Beneath the LLM Promise

Building production AI applications reveals that large language models are just a small portion of the required infrastructure, similar to hidden technical debt in traditional ML systems. Beyond the core AI model, engineers must build deterministic software, tool selection systems, observability, guardrails, RAG systems, and memory management—creating enterprise-grade complexity that mirrors pre-LLM machine learning architectures.