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15 results for “unicorn outcomes”
founders that are trying to build a company in the physical world, there are two things that I'm looking for. Number one is a sense of being hyper optimistic. You're starting with nothing, with a clean sheet, and you have to spend lot of time and a l
6:01 / 7:03
from transcript6:01 – 7:03
...unicorn prediction. So who would you pick for a future unicorn? Hey. I mean, I think, you know, we've talked about lovable, so why not pick pick them? I mean, the product is just great. You know, I think we can all see that. I think we can also see t
40:28 / 41:33
from transcript40:28 – 41:33
...today. That's what Crunchbase says. Close enough. Right? Rich Wong from Excel said this last week, 20% will fail. Okay, so that leaves us with, what, 1,200? How many can do easily do tender offers of scale? 1%? Done. 2%? Like, we've got 1,200 viable
20:55 / 22:02
from transcript20:55 – 22:02
...hundred unicorns, you know, valued at more than 1,000,000,000, and the SVP did that analysis. I think something like 30% of them have a decent growth profile and scale.
1:05:08 / 1:06:17
from transcript1:05:08 – 1:06:17
...unicorn prediction. You're very welcome to pick one of your portfolio companies, but is there a company that you've seen at the early stages that is, is on your radar that you think might go all the way and become a unicorn? Yeah. Well, I'm mentionin
37:26 / 38:30
from transcript37:26 – 38:30
...ain't gonna get you there. I would certainly agree. What's the quest the exact question here is gonna have to do It says 46. How many are actually unicorns? You know, it's worth a billion dollars in hard cash today. Here's what I'm worried. And and s
1:12:40 / 1:13:46
from transcript1:12:40 – 1:13:46
...actually unicorns? You know, it's worth a billion dollars in hard cash today. Here's what I'm worried. And and so so 20% was kinda what the SBB data said. Right? Which sounds about right to us. Right? It's an unfortunate number. It's smaller than we'
1:13:30 / 1:14:32
from transcript1:13:30 – 1:14:32
...unicorn story, and, yeah, we we watch your whole portfolio continue to, you know, hit hit new hit new records and and wish you all the best with it.
45:00 / 46:04
from transcript45:00 – 46:04
I think that's pretty fair to say. How how common is it though that where you're seeing founders maybe maybe their ideas isn't quite right, but where they actually combine those two first pieces, which is, you know, very optimistic and driven, but al
7:31 / 8:30
from transcript7:31 – 8:30
...in the world, something like that. And when you look at the stats, the vast majority are software businesses, and the second biggest category is financial services. And so I suppose I'm going to choose one that, a business that I invested in at the m
46:30 / 47:30
from transcript46:30 – 47:30
...unicorn prediction. So a company that you've seen early on that you think is gonna become a unicorn, it can be in your portfolio or it can be in a different company, just a cool company that you think is gonna go all the way. Yeah. So this one, I'm I
38:11 / 39:32
from transcript38:11 – 39:32
...a unicorn, it can be in your portfolio or it can be in a different company, just a cool company that you think is gonna go all the way. Yeah. So this one, I'm I'm not gonna choose something for my portfolio because there are so many. I couldn't choos
38:57 / 40:09
from transcript38:57 – 40:09
...to a to a unicorn, hundreds of millions growing pretty good growth. Right? Not being killed by AI, but not necessarily benefiting it, but enough. Right. To be in to eventually compound to a better IPO than that, but not an open evidence. And we did a
1:05:37 / 1:07:05
from transcript1:05:37 – 1:07:05
...riding unicorn story. Excel is obviously very well known fund, and the track record is incredible. And, I love the little descriptions you have of each company on your LinkedIn. They just sound like
36:44 / 37:48
from transcript36:44 – 37:48
...a unicorn, or why are we making the investment, which means it has to have a great team, you know, good product velocity, and going after a big market. And so then you have to ask yourself, is this worth
17:03 / 18:17
from transcript17:03 – 18:17
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