Comment by DrScientist
19 hours ago
I think one of the issues I find with text based interfaces, which is not often discussed, is they are not good at expressing what they can and can't do.
Their very strength, of not being limited, is also a weakness - you only find the boundaries of what's possible by trial and error.
This isn't inherent, just a side effect of poorly designed text UI. Suggestions on the input, manual commands, or honest answers in response to the question "what can you do" all do as good a job as a GUI does, and sometimes a better job.
So many of the complaints I hear about TUIs just come down to bad design. Even one input and textual responses require thoughtful design.
That's design as in function, not color palette. Although... that too.
OK - so in the case of text interface to a constrained tool, you are effectively mapping free text down to some underlying set of function calls and parameters, and you could ask the tools to describe those.
For more general AI tools, I guess it becomes harder to give a succinct description - and so that's still a bit trial and error ( even if you have good feedback ).
The term you're looking for is discoverability, and in my experience it's the most discussed concept when it comes to critiques of text based user interfaces.
Thinking about it - for traditional text based interfaces like a unix shell, perhaps I'd argue that with stackoverflow and google search they became more discoverable than GUI's.
And perhaps even more with LLMs.
ie it's easier to find out how to do X in bash and cut and paste the solution than watch a video on which series of things to click.
Not sure how that extends to specific chat interfaces - can you ask the general models how best to use specific chat from ends over specific tools?