Optimizing CEO Name Extraction via LinkedIn URLs: Tips and Tricks

This is another trick: If you prompt claygent to find the CEO of a company and return the linkedn url of said CEO, you can extract the CEOs name through the linkedin URL. You don't need any further GPT to extract the name from the reasoning of the first GPT. Caveat: A few names will need to be split, but for this i would use a conditional GPT One less GPT can mean $$$$ 🙂 Do you have a faster and cheaper method?

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7 comments

Bo (.
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Great idea, Dominique. You can also simply prompt the Claygent to return the full name and the LinkedIn URL. You can add up to 5 outputs with Claygent without having the quality degrade :) https://downloads.intercomcdn.com/i/o/w28k1kwz/1237466627/828cc6a8ed694640e091d617cce8/CleanShot+2024-11-02+at+_56x8NiTVc0%402x.png?expires=1730556000&signature=3cfadee625e292b98cea84a6b539d08f2aae7b4f0a597322da3467ad01c832fc&req=dSIkEc14m4ddXvMW1HO4zfHDM0Pczln88Mi7KXWXmSnf3i0AX%2FFQAIScC7il%0A0A7g%0A
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Dom M.
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great! Do you define all the parameters in the prompt? Like extract the name and save it as "Full Name" or is the left side automatically making the connection, that a name will match this output?
Bo (.
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Exactly. You can also specify it in the [...] beside the output. That'll make this even more exact :)
Dom M.
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worked like a charm. Didnt realize that the points next to it are mini prompts for the fields! Amazing.
Channeled
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Channeled
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Thank you so much for sharing your feedback Dom M.!
JP M.
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Thanks for sharing!!!