Once you see that an answer is not serving its question properly anymore, it should be tossed away. It's just their natural life cycle.
They usually kick and scream, raising one hell of a ruckus when we ask them to leave. Especially when they have been with us for a long time.
You see, too many actions have been based on those answers. Too much work and energy invested on them. They feel so important, so full of themselves. They will answer to no one. Not even to their initial question!
The hardest thing about customer interviews is knowing where to dig. An effective interview is more like a friendly interrogation. We don’t want to learn what customers think about the product, or what they like or dislike — we want to know what happened and how they chose... To get those answers we can’t just ask surface questions, we have to keep digging back behind the answers to find out what really happened.
Like a programming language interpreter, GPT-3 translates the designer’s intent from a language they’re already familiar with (English) to one they need to learn (Figma’s information architecture, as manifested in its UI.) This can be easier for a new/busy designer, much like Python is easier and faster to work with than assembly language.
But that’s not “designing” — at least not any more than compiling Python code is “programming.” In both cases, all the system does is translate human intent into a lower level of abstraction. Sure, the process saves time — but the key is getting the intent part right. I’ll be convinced the system is “designing” when it can produce a meaningful output to a directive like “change the product page’s layout to increase conversions.”