I know this is kind of out in left field, but some people also mentioned query result history. I've been using phind since it was in beta as sayhello and encountered similar a faux pas where submitting feedback sent me to an plaintext error page. Going back and resubmitting the query produced a result that didn't include the important information in the original result. It would be helpful to have search history, but furthermore (and the reason for writing this) is an idea that's been floating around in my head about git-tree esque search histories in bash. Though it's currently outside the range of my expertise. While reading the comments of this thread I had an idea for a similiar feature, something i would probably pay for an recommend.
The feature relates to a problem I've encountered as an active intermediate developer with managing the multidunious and varied queries that i might do both getting up to speed and solving problems in-the-wild. I find that what i learn and use doesn't stick right away, so rather than making the same query (and in this case sometimes getting different results) resorted to keeping 3 notebooks for each subject: a technical reference, a working notebook, and a learning log. That's a lot of notebooks!
I mention this because knowledge management and effective learning go hand in hand. And learning something you didn't know seems to be the problem domain of ai search for developers.
Organizing query results thematically by learning trees would be a gargantuan undertaking, and probably far outside the scope of what is already an excellent service. Just putting that out there.
The feature relates to a problem I've encountered as an active intermediate developer with managing the multidunious and varied queries that i might do both getting up to speed and solving problems in-the-wild. I find that what i learn and use doesn't stick right away, so rather than making the same query (and in this case sometimes getting different results) resorted to keeping 3 notebooks for each subject: a technical reference, a working notebook, and a learning log. That's a lot of notebooks!
I mention this because knowledge management and effective learning go hand in hand. And learning something you didn't know seems to be the problem domain of ai search for developers.
Organizing query results thematically by learning trees would be a gargantuan undertaking, and probably far outside the scope of what is already an excellent service. Just putting that out there.
Thanks!