this is what "fake it 'til you make it" is supposed to mean. Act like you can do the job while you work crazy hard to learn something fast enough to actually be able to do it well.

coder / founder / investor Founding partner @FirstStarVC 

Loves: AI/ML, data, Bitcoin, climate, techbio, coffee, and pie.

I'm here to build global community. Artist, collector, father and husband, leftist, LGBTQ. Twitter @ OurCoOpFuture. pfp by Nilus Dantes. Creator of /solidarity

That's how you do it. When you've built teams you realize someone who learns quickly and genuinely wants to be good is the most valuable person you can hire. Trajectory >> starting point.

That was me 7 years ago, was doing min wage BS jobs and applied for a Senior Appraiser position. I had zero experience in appraisal or basically anything related, or the "required" college degree, but I did my research and got the job somehow. Dug in to learn as much as possible, now I'm promoted to defending appraisals in appeal hearings. 🤷‍♂️

Founder https://tuum.tech | @intori | /intori | Exploring Farcaster and Base → https://paragraph.xyz/@bullers

great point. reminders me of a decade ago I was working on speech recognition and remember researchers talking about when neural networks took over.

originally you needed deep knowledge of linguistics and human speech (English has 44 phonemes, etc) and then ~2012, researchers who didn't know anything about that stuff but were good with NNs made end-to-end NN models that were better than state of the art. suddenly someone w/ a PhD in Linguistics and a decade of speech work had all of his knowledge made basically obsolete.

Raises an interesting question: would you rather hire someone with knowledge of using AI and research tools who is unqualified at first, or someone with the work history but not tapping into AI tooling?

Depending on the role if it gets the job done + explores areas the other applicants may not have it could be a benefit to the company.