AI engineering skills beyond prompting

One engineer argues that focusing only on prompting and calling language-model APIs is a mistake. Their recommended topics range from retrieval-augmented generation (RAG) and AI agents to model routing, fallbacks, memory management and input/output validation. They also emphasize logs, metrics and traces, inference engines, load balancing, and backend fundamentals—framing AI engineering as the work of building reliable, scalable systems around models.