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Letting AI Find a CoFounder

Find a collaborator rather than being a collaborator

I have seen (which is not the same as read) countless articles about ChatGPT or a similar system acting as an assistant, editor, collaborator, researcher, or muse. Sometimes with better results than others. Sometimes with outstanding bad results (See LegalEagle’s video on Mata v. Avianca, Inc. (1:22-cv-01461)).

What if, instead, we used a large language model to find us a collaborator?

Recently a founder in search of a cofounder did exactly that using a ChatGPT competitor Claude made by Athropic called Claude.

He scraped six hundred profiles from Y-combinator’s matching system, and in groups of ten, he asked Claude which would be best.

Unfortunately, Claude, like many other Large Long Models (LLM), shows a large bias to select choices near the beginning of large lists even when later choices are better.

So he replaced it with Claude selecting from pairs making a tournament system where a candidate gets removed after having too many losses.

While Claude is in Beta, there are no fees or real limits on its use, so a many-round tournament with hundreds of pairs to judge each round was not problematic. (I am estimating that OpenAI GPT-4 would have been about $200 / tournament with several tournaments of experimentation needed.)

Claude was tasked with determining the cofounders’ ability to invest their own money into the project, interest in the areas of the project, and skills match.

Ultimately Claude gave the thumbs up to a dozen impressive potential cofounders who were contacted on linked in. Claude provided an explanation as to why each of them was a good fit which made creating the individualized initial outreach message simple.

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Written by Russell Brand

Russell has started three successful companies, one of which helped agencies of the federal government become very early adopters of open source software, long before that term was coined. His first project saved The American taxpayer 250 million dollars. In his work within federal agency, he was often called, “the arbiter of truth,” facilitating historically hostile groups and factions to effectively work together towards common goals

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