OpenAI: the best advice this founder received working at the company

Brian Sozzi · Executive Editor

Tue, February 17, 2026 at 5:00 AM GMT+9

Opening Bid Unfiltered is available on Apple Podcasts, Spotify, YouTube, or wherever you get your podcasts.

Chai Discovery co-founder Joshua Meier shares the best piece of advice he received while working at OpenAI (OPAI.PVT).

Listen on your favorite podcast platform or watch on our website for full episodes of Opening Bid Unfiltered.

This post was written by Langston Sessoms, producer for Opening Bid Unfiltered.

Video Transcript

00:00 Speaker A

OpenAI is back to your company.

00:01 Speaker B

Yes.

00:01 Speaker A

Has Sam given you, Sam Altman given you like amazing advice that you still adhere to every single day?

00:05 Speaker B

Yeah, actually maybe I can take a story there. So so back at at OpenAI, you know, when I was leaving to join Facebook, we actually had some of these conversations with Sam about, should we go and do something around like proteomics, like and and actually use AI to do protein design, you know, back back then.

00:20 Speaker B

And kind of decided that the technology wasn’t ready yet. So I think there’s this uh maybe the lesson there and it’s the same with AGI. It’s like you have to think really big, but you also need to hit the iron when it’s hot.

00:29 Speaker B

So it wouldn’t have made sense again to go and put these AI models into people’s hands like three years ago because it just didn’t work yet.

00:33 Speaker B

And I think one of the reasons why we think this will be the year of deployment in AI drug discovery of AI models actually being being deployed is that the technology is finally working.

00:41 Speaker B

One thing that uh Ilya had actually said to me, this is on I think my first week of the job at OpenAI. Um he said that uh any experiment you start, you should try to make sure it finishes that day.

00:50 Speaker B

And I and that’s something I’ve taken with my throughout my career. It’s not even just like training AI models, but you need fast feedback loops. You need to be able to try things and get feedback from people.

00:58 Speaker B

And this is why drug development is so so hard, right? If it takes two years to discover your drug, how are you getting those like feedback loops?

01:03 Speaker B

And if we can just, you know, kind of compress those timelines and go after harder problems, we can just iterate through a lot more and then hopefully come up with much better solutions.

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