[humbleferret]

Good work!

The sample searches were particularly strong for uncovering discussions on specific subjects, i.e. 'Dedicated Vector Databases'.

With less focused searches, such as 'Deep Work', I notice some results feel only loosely related. Is this an aim – to broaden the scope of discovery that may not seem directly related?

[isoprophlex]

Thanks for testing it out! So, because I've found (in purely vibe-based testing, of course) that with queries of 1, 2 or 3 words, a vector embedding doesn't always make a lot of sense. What's "Apple"? The fruit, the company? So, here it defaults to priming the fuzzy search with a full text search on 'apple', or 'flow state'. If you want to know something about deep work, try "tricks for performing deep work", or "help me get into a flow state".

It's all very serendipity-driven, and this is mostly a tool for wasting time, but you might discover some interesting (and hopefully on point) conversations this way.

Anyway, valuable feedback. Maybe in a next interation, I'll always do both searches and merge the resulting ranking.

[humbleferret]

Thank you for the detailed reply – I appreciate the insight into how the shorter queries are handled.