Narayan Chowdhury

which has its own issues.

And then there is that, still there's a bias of, well, you have that, it's nice to hear that there's an independent correlation because you're still gonna then deal with the fundamental LP bias that is driving those portfolios.

So for example, let's just say you got an LP submitted dataset

But the underlying LPs were very large FOIA-based investors, right?

They would have different access than either the broader market or, say, best-in-class access.

And access, of course, is a huge deal in venture.

So there are still some problems.

But then there's also the problem of, okay, you make a conclusion about, wow, this group or this segment is interesting, right?

Well, OK, it was interesting then, but that this perhaps this group that you've identified there, there are five X the size of when when their peak performance happened.

Right.

So they're essentially competing in a new market.

So is is the you know, the the dangers of being backwards looking on that data analysis?

It could be that maybe the sector has completely gone away or it's overfished.

And so the magic was you were on the front end and the valuations were two times revenue and now they're 20 times revenue or whatever it might be.

For me, Untethered just means when I would think about, you know, I was very fortunate.

I've said this before on a different podcast, just being very fortunate to meet Josh Koppelman in 05.

And, you know, the beautiful thing there was meeting somebody who had some insights that not a ton of other people had and getting into that first mover community of micro VCs like Idan Sankat or Mike Maples or Manu Kumar or...

Steve Anderson, like they were all kind of seeing it.

And it didn't really get overfished, become ultra obvious.

I remember a lot of the larger cap VCs at the time really dismissing that strategy.