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ted (not lasso) pfp
ted (not lasso)
@ted
i haven't yet dug deeply into DeSci (i will), but here are some high-level thoughts from my experience launching a drug development fund* that was very hands-on with academic labs: 1. proving a hypothesis in the lab (research) =/= finding product-market fit (startup). they shouldn't be funded as if they are the same. this is not exclusive to DeSci; VCs who funded AI researchers will learn this quickly in the coming years. note PMF for biopharma startups looks different than for traditional tech startups. 2. most scientists (like most people) aren't good entrepreneurs. good science =/= good business (market demand, scalable operations, strong marketing). DAOs can introduce more management and inefficiencies, not more expertise, and tokenized IP introduces more legal/reg complexity i don't yet see how DeSci, esp DeSci tokens, solves either of these problems *the fund raised $250M+, funded 200+ lab discoveries, launched 35+ companies, 20+ medicines in clinical trials, and 15 licensed to pharma companies
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Noun 839
@noun839.eth
One thing different for ai and has been one of the playbooks for the last decade is that AI teams get hired wholesale at multiples that aren’t just an aquihire. So if you can put together a team of incredible ai researchers there is some downside protection. My team was acquired by Clouders in 2017 and everyone involved made money. But I agree with everything you said, that’s just one nuance. It’s not true for every ai entrepreneur but if you have the kind of researchers that Facebook wants, you have downside protection. My team got into a bidding war between Airbnb and Cloudera. In the end Airbnb offered more but Clouders was a better fit (and we held all the meaningful voting equity)
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