What are you doing now with the eye stuff?
Well, I mean, I'm more curious to hear your thoughts and predictions, frankly, because I think you're better at it. But I mean, I'm using Claude Code with Ferris APIs to do tons of like inbox analysis and stuff.
Right? I'm doing a 20-year retrospective analysis of angel investing.
It's like, who made what introductions? Which companies did I not reply to that ended up being successes? Which did I turn down that ended up being really important?
Do you really want to do that to yourself?
Well, I suspected it'd be worse than it was. I actually have not — I haven't missed that many explicit opportunities. I wanted to test my own stories against data, right? Because I have all sorts of stories about why I did certain things and why certain things worked out. And I have certain stories about my batting average. And I'm like, but is it true?
Let's look at some hard numbers.
The sad truth, and I have a buddy that wears the bracelet and you've seen me with the necklace around, that categorizes your AI and listens to you 24/7.
It's about 70-ish percent that we think we know, but is actually what we know. Out of the 100% of like what we think we know, this is the truth. I said I wanted a dark chocolate bar at 7:00 p.m. It's like, no, you said it at 5:00 and you said it this way.
And you said it was milk chocolate.
Yeah, exactly. So, it's always about 20% off from where you actually think your brain's at.
Well, plus, I mean, that's like last week, right? If you're talking about 15 years ago. I mean, if you listen to any genesis story of any startup, you're like, oh my god. Wait a minute now. Like, this is like a startup comic working on material, but he's been working on this one 5-minute bit so long that now he believes that's actually truth. The sanitizing and the editing of these startup genesis stories is hilarious, and there's no reason to think that I would be or you would be exempt from it. Right, when you're telling your own story, even if you're just telling it to yourself.
So, what's the number one thing that you've learned by applying AI to your life in this fashion? Like, what's the thing where you walked away and said, 'Damn, that was insightful, and I'm going to change my behavior,' or 'I learned something new about myself that I wouldn't have if I had not used AI'?
Well, I think from a holistic health perspective — by holistic I mean having enough data related to medications, supplements, predispositions, side effects, what happened to me 2 weeks ago — the LLMs have been incredibly helpful. I mean, the picture that they get and the speed with which they can deliver an answer that I can interrogate is just incredible.
What did you learn? Like, what was the thing that you...
I mean, honestly, it's mostly avoiding disaster, right? It's like, are any of these things contraindicated with one another? Could A, B, or C explain D? And you have to keep in mind, these things can still hallucinate, but you can — I don't want to say eliminate that, but minimize it by just fact-checking across LLMs. There's that. I would say that there's a lot of insight on, hopefully, that can translate to future decision-making related to investing, which investing for me is not just amassing more chips. What's fun about investing to me is it's a way to scorecard your thinking and decision-making. It's just a very objective way to decide if something was the right or the wrong decision. And you can fine-slice that, and there are ways that you could maybe question that, but if you're asking yourself, 'Was I thinking well last month?' That's not a very helpful question. Where do you go from there? If you're logging maybe every decision you make every day and then trying to cross-reference outcomes with blah blah blah. Like, yeah, but you're never going to do that. But when you're making relatively frequent investments, you can do that. You can also run counterfactuals, right? What if I did the opposite? What if I had not sold that? What if I had kept that? What if I had done this? What if I had done that?
