We stole all your great statistics, Rebecca. But the statistics are shocking, and I'm interested in what you think the new benchmark is and how many of those 1400 actually still vindicate a $1 billion valuation. Yeah, I think the number I've heard is

it would take about 20 years for all of those unicorns to actually make it to the public market. And only 15% are profitable. And on top of that, a lot of them have been around for over 12 years.

So, just way too long to really hit their stride and hit profitability. I think with Jenny, I know a lot of the metrics we've seen in the past aren't really the metrics we're looking for in the future for success.

You know, unicorn status, I think people have said that we need a new beast. I think that's absolutely true. And, you know, getting to that billion-dollar valuation is not really meaningful anymore. And then on top of that, what we're seeing, McKenna AI, is an incredible

opportunity to generate revenue quickly. We're seeing this in the statistics about how quickly companies can get to $1,000,000 of revenue. It used to take companies quite a lot longer. And right now with Jenny AI, the median is 11 months.

Right. And we actually saw a company the other day that got to $1,000,000 of ARR in two weeks. And so, you know, at like, is that something it's not? No, no, I don't think so.

I think what's happened is I don't think it's sustainable. So what we're really looking for are companies that have a unique insight and very deep industry knowledge in their area. We think that's more important than ever before.

And I think this ARR ramp we're seeing, which so many VCs were relying on for so long, is really ephemeral. So what's happening is these big enterprise companies

and consumers are signing up and paying money to pilot the technology, while seeing massive enterprise companies like Salesforce hire 1400 new

salespeople.
Yes. You capture that opportunity.
How many agents, Rebecca, know Salesforce?
How many agency companies are contacting you at the moment?
Oh, my gosh. Dozens a day.
Dozens a day.

And I think those are features of large enterprise companies in the future.
The features. So what is the reality?
What companies do you want to see built?
What problems do you want to see solved that are unique right now?
I love that question.

Thank you.
Yeah, it's so exciting to be in venture right now. There are so many opportunities we've wanted to invest in for a long time. And there are companies that tried, but the technology just wasn't there

yet.
I mean, a prime example, you know, it was a company that was
impacted by generative AI.  It was Casetext.
Casetext was doing really well. They had 10,000 customers, but they
couldn't fulfill the last part of their

promise, which was truly to stand
in the shoes of a legal counsel. And when Gen AI came along, they could do
that. And that was a huge unlock and why they
were purchased very quickly by Thomson Reuters.
Another one that we've wanted to see for

a very long time is voice.
And I think that is the most exciting thing about generative AI right now.
And so when we were in AI Doc SimCity for many years, I just thought,
you know, we should be taking the entire

patient call volume, both
inbound and outbound, off the shoulders of the physicians' offices.
That should just happen, and the tech just wasn't there yet.
We've been looking for this tech ever since.
We led Siri's investment many moons ago,

right?
And with generative AI, it suddenly is there. So we invested in a company
pretty recently called Parakeet.  The founder has super deep technical
knowledge in the medical space. And they're doing just that.
They're taking the call volume, the

inbound and outbound call volume off the
shoulders of a doctor's practice. And that to me is really, really
exciting. We listen to you because of the number
of times you're on a Midas list, the number of times you've called one of the
top VCs, but also because of the exits

that you have seen and you call out case techs, which is M&A. We've also seen, as you just mentioned, well, Luminar, for example, which actually managed to do the public kind of route.

How are you anticipating some of your portfolio going public come 2025? Yeah. I mean, I think the window is starting to open. There are so many companies that are ready. I think the market's ready. I think with the new administration, people are ready for the unlock.

And I do think we'll see the public markets start to open up. Maybe I'm too optimistic. I don't know. But I do think that that's a very viable option for people going forward. The other thing is, I think M&A, I mean, I actually prefer M&A every single time

because it's a much more linear exit for founders often. And so I think founders should always keep both options in mind. My most successful companies have had a very exciting IPO path but have also dual-tracked with an M&A path at the same time.

Reevaluating the Benchmark of 'Unicorn' Status

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오래된 유니콘 지표와 새로운 벤치마크의 필요성

유니콘에 대한 기존 통계는 많은 사람들에게 10억 달러라는 기업 가치의 타당성에 의문을 제기하는 충격적인 결과입니다.

유니콘이 상장되기까지 약 20년이 걸리며, 그 중 15%만이 수익을 창출합니다.

과거의 성공 지표는 더 이상 적합하지 않으므로 성공에 대한 새로운 정의가 필요합니다.

10억 달러의 기업 가치는 더 이상 큰 성과가 아닙니다.

빠른 수익 창출과 고유한 인사이트의 중요성

이제 기업들은 평균 11개월이 걸리던 매출 1,000,000달러를 훨씬 더 빠르게 달성할 수 있습니다.

일부 기업은 2주 만에 1,000,000달러의 ARR을 달성하기도 합니다.

지속 가능한 성장을 위해서는 고유한 인사이트와 심도 있는 업계 지식이 필요합니다.

이전에 보였던 급격한 ARR 증가는 지속 가능하지 않습니다.

엔터프라이즈 기업의 미래와 바람직한 기업 특성

매일 수십 개의 에이전시가 연사에게 연락하여 수요를 강조합니다.

연사는 고유한 문제를 해결하는 회사를 만들고 싶어 합니다.

제너레이티브 AI의 영향과 투자 기회

제너레이티브 AI를 통해 케이스텍스트는 약속을 이행할 수 있었고, 빠른 인수를 이끌어냈습니다.

제너레이티브 AI는 환자 통화량 자동화와 같이 이전에는 불가능했던 솔루션을 가능하게 합니다.

의사들의 통화량을 자동화하기 위해 생성 AI를 사용하는 회사인 Parakeet에 투자했습니다.

향후 포트폴리오 이벤트 예상(IPO 및 M&A)

발표자는 2025년에 IPO를 위한 창구가 열릴 것으로 예상합니다.

연사는 창업자의 보다 선형적인 출구 전략으로 M&A를 선호합니다.

가장 성공적인 기업들은 IPO와 M&A를 동시에 추진했습니다.

Reevaluating the Benchmark of 'Unicorn' Status

Reevaluating the Benchmark of 'Unicorn' Status

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