The hardest part of shipping a retrieval-augmented generation system is not getting the first version live. It is knowing when the next change quietly made it worse.
When people talk about prompt caching, they usually frame it as infrastructure optimization. Lower costs. Lower latency. Fewer repeated tokens. All true.
A lot of agent dashboards are visually impressive and operationally shallow.
If you are building serious AI products, the answer is almost never “use the biggest model for everything.”
A lot of the excitement around agents focuses on reasoning. I think a lot of the real progress is happening somewhere less glamorous: interface design.
RAG became the default answer to a lot of AI product questions because it solves a real problem: models do not know your data by default.
Synthetic data is one of the most useful accelerants in AI engineering, and one of the easiest ways to fool yourself.