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Show HN: Find AI – Perplexity Meets LinkedIn

usefind.ai

51–60 of 78 posts

Re: Show HN: Find AI – Perplexity Meets LinkedIn

#52
Confused by these numbers:

Software engineers Search completed: less than a minute ago • 1792 candidates analyzed • stopped after 53 matches found

We have analyzed 84 candidates and found 31 records matching the search criteria. The search was initiated 1 minute ago and took 30 seconds to complete.

Re: Show HN: Find AI – Perplexity Meets LinkedIn

#55

Cool but after waiting 2 mins for a one sentence prompt I got; We have analyzed 1681 candidates and found 0 records matching the search criteria. The search was initiated 2 minutes ago and took 1 minute and 42 seconds to complete.

And then a second more simple Query ‘find me people who have posted on Mamba architecture and might be looking for jobs’ and got;

We have analyzed 695 candidates and found 0 records matching the search criteria. The search was initiated 1 minute ago and took 50 seconds to complete.

Re: Show HN: Find AI – Perplexity Meets LinkedIn

#56
Why use this over LinkedIn Sales Navigator? Zoominfo/DiscoverOrg? How much time have you actually spent prospecting? If you have to ask vague questions to find your prospects, you probably don't know your ICP and need to refine your GTM strategy

After a little research I'd be frankly surprised if this product ever made back the ~6M in funding you guys have. The whole bet is predicated on the incumbents not adding the most basic of AI features

Re: Show HN: Find AI – Perplexity Meets LinkedIn

#58
The examples start out looking like recruiting, and heavy on the usual school obsession (MIT, Stanford, Harvard), with no improvement over existing simple queries that every bottom-end sourcer is doing.

Ideally, smarter tech will let us get closer to what we're really trying to do like "Find me a person, who I can hire, who will do great work at responsibilities X, Y, and Z."

Re: Show HN: Find AI – Perplexity Meets LinkedIn

#59
Multiple examples are querying for "female" (which could be fine), and this prompted a thought...

What happens when a customer is searching for hiring purposes, and searches specifically for "male"? Or "young", or "unmarried", or "childless", or "straight", or "white", or "non-disabled", or "non-veteran"?

The data is out there, and is bought and sold heavily. (You mention that dog ownership is something you query over.)

What queries are you going to permit, and what not?

Even with current tools, it seems a lot of people people do this casually. Besides the many biases that people will openly admit on HN, I'm reminded of when someone told me to use one of the popular hiring sites to filter out candidates who weren't in early/mid-20s. (They spoke of it as if it was clever to use graduation year, since the site didn't let you filter by age directly.) Aaaannnndddd... the hiring sites surely have that search history information that recruiters and hiring managers for numerous employers are doing, unless they're intentionally discarding it against all data-appetite industry convention, so should be easy fodder for some energetic regulators/lawyers.

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