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> How does it work? We don't know! We built this to learn a little bit more. We've seen that LLMs tend to prefer user-generated content (sites such as wikipedia, reddit, etc.) and …

We absolutely do lose information here; that's a great point. The goal for us wasn't necessarily to surface the best ranking; it was to learn how LLMs produce a given ranking and w…

Interesting call out - we're working on adding Gemini soon!

That nuance is really important/hard to piece apart. Have you found any good techniques to solve for it?

OP here - looking at what the models pick up as sources for "Trustworthy News Sources" is especially interesting. I wonder why the providers reach for such esoteric material when b…

That's a great point - we built this moreso to learn a bit about how the AI models interpret ranking products, and less so to actually be a trusted source of recommendations. Seein…

Hi HN! AI Product Rank lets you to search for topics and products, and see how OpenAI, Anthropic, and Perplexity rank them. You can also see the citations for each ranking. We’re i…

"kay-len" - confusing I know

Thanks! You can think of Grimp as a lower-level tool for interacting with the import graph in Python, while Tach is a high-level tool responsible for 'modularity' as a whole (e.g. …

Thanks for this feedback! Here's a more structured walkthrough: https://www.loom.com/share/7c03d72ea2b54212a3509d4333f61b99?... We'll add this to the README.

Hey everyone! We're Evan and Caelean, the authors of Tach. Tach lets you visualize the architecture of your Python codebase, and gives you the tools to incrementally improve it. It…

Yes, good call out - I actually wrote a bit more about this and how we arrived at our solution with `tach`. [0] https://www.gauge.sh/blog/the-trouble-with-all