This article rests on the premise that LLMs require their inputs to be well written. The article points to the existence of prompt engineers to emphasize the d

This article rests on the premise that LLMs require their inputs to be well written. The article points to the existence of prompt engineers to emphasize the difficulty of creating the "right" input. The truth is, these LLMs have already seen the average (and worse) of human writing, and have generalized to a more precise (and typically the intended) input. When they're wrong, they recover pretty well when corrected. The existence of prompt engineers is more for the adaptation and additional context for the mass of thin apps on top of an LLM. I posit that what's needed isn't an abandoning of LLMs as interface, but an acknowledgement that chat-based AI as an input only helps at a certain, rather high, level of abstraction. There are many possible applications that can be built with an LLM but very few that actually enhance the UI of the rest of the app. Application designers need deeper understanding of the LLM's capabilities and the core value of the software product it's intending to enhance in order to build something that is an improvement on what the app would be without an LLM.