Ben Choi from Next Legacy joins David on El Pack to answer your questions on how to build a venture capital fund. We bring on 3 GPs at VC funds to ask 3 different questions.
Gilgamesh Ventures’ Miguel Armaza, also host of the incredible Fintech Leaders podcast, asks Ben what is the timing of when a GP should consider raising a Fund III.
Similarly, but not the same, Strange Ventures’ Tara Tan asks when an LP backs a Fund I, how do they know that this Fund I GP will last till Fund III.
Arkane Capital’s Arkady Kulik asks how one should think about building an LP community, especially as he brings in new and different LP archetypes into Arkane’s ecosystem.
Ben manages over $3.5B investments with premier venture capital firms as well as directly in early stage startups. He brings to Next Legacy a distinguished track record spanning three decades in the technology ecosystem.
Ben’s love for technology products formed the basis for his successful venture track record, including pre-PMF investments in Marketo (acquired for $4.75B) and CourseHero (last valued at $3.6B). He previously ran product for Adobe’s Creative Cloud offerings and founded CoffeeTable, where he raised venture capital financing, built a team, and ultimately sold the company.
Ben is an alum and Board Member of the Society of Kauffman Fellows (venture capital leadership) and has also served his community on the Board of Directors for the San Francisco Chinese Culture Center, Children’s Health Council, Church of the Pioneers Foundation, and IVCF.
Ben studied Computer Science at Harvard University before Mark Zuckerberg made it cool and received his MBA from Columbia Business School. Born in Peoria, raised in San Francisco, and educated in Cambridge, Ben now lives in Los Altos with his wife, Lydia, three very active sons, and a ball python.
[00:00] Intro [05:05] Ben’s 2025 Halloween costume [06:44] Jensen Huang’s leather jackets [07:24] Jensen Huang’s answer to Ben’s one question [10:05] Enter Miguel, Gilgamesh Ventures, Fintech Leaders [14:43] What are good signals an LP looks for before a GP raises a Fund III? [22:35] Why does Ben say ‘established’ starts at Fund IV? [25:08] Who’s the audience for Miguel’s podcast? [27:52] In case you want more like this… [28:32] Enter Tara and Strange Ventures [32:46] How does Ben know a Fund I will become a Fund III? [36:53] How does Ben know if a GP will want to build an enduring career? [40:58] How does Tara share a future GP she’d like to work with to Ben? [42:43] Marriage and divorce rates in America [43:34] What should a Fund I do to institutionalize? [46:28] Should you share LP updates to current or prospective LPs? [48:57] Enter Arkady and Arkane Capital [51:09] How does one think through LP-community fit? [1:01:31] What’s Arkady’s favorite board game? [1:03:08] Ben’s last piece of advice to GPs [1:09:50] My favorite Ben moment on Superclusters
“The dance of fundraising is when you do have [your thesis], the LP has to figure out is this a rationalization of the past or is it actually what happened? Was this known at the time? Because if it was, we can have some confidence in the future going forward. But if it was just a rationalization of some randomness, then it’s hard to know if Fund IV or V or VI will benefit from the same pattern.” — Ben Choi
On solo GPs bringing in future partners by Fund III… “The future unidentified partner is the largest risk that we have to decide to accept. So there actually isn’t a moment where we decide this GP is going to be around for Fund III. It’s actually the dominating risk we look at and we get there, but it’s a preponderance of other things that we need to build our conviction so high that we’re willing to take that risk.” — Ben Choi
“It’s brutal. It’s a 30-year journey. For any GP who raises a single dollar from external LPs, it’s a 30-year journey.” — Tara Tan
“I don’t think anyone goes into this business to raise capital, but your ability to raise capital is ultimately what allows you to be in this business.” — Ben Choi
On community… “Your core question is how much diversity—in the technical term of diversity—can you tolerate before you lose the sense of community.” — Ben Choi
“Most letters from a parent contain a parent’s own lost dreams disguised as good advice.” — Kurt Vonnegut
“Fundraising is a journey of finding investors who want what you have to offer; it’s not convincing somebody to do something.” — Ben Choi
Stay up to date with the weekly cup of cognitive adventures inside venture capital and startups, as well as cataloging the history of tomorrow through the bookmarks of yesterday!
The views expressed on this blogpost are for informational purposes only. None of the views expressed herein constitute legal, investment, business, or tax advice. Any allusions or references to funds or companies are for illustrative purposes only, and should not be relied upon as investment recommendations. Consult a professional investment advisor prior to making any investment decisions.
Soooooooo… (I know, what a great word to start a blogpost) I started this essay, with some familiarity on one subject. Little did I know I was going to learn about an entirely different industry, and be endlessly fascinated about that.
The analogy that kicked off this essay is that re-upping on a portfolio company is very much like re-signing a current player on a sports team. That was it. Simple as it was supposed to sound. The goal of any analogy was to frame a new or nuanced concept, in this case, the science of re-upping, under an umbrella of knowledge we were already familiar with.
But, I soon learned of the complexity behind re-upping players’ contracts, as one might assume. And while I will claim no authority over the knowledge and calculations that go into contracts in the sports arena, I want to thank Brian Anderson and everyone else who’s got more miles on their odometer in the world of professional sports for lending me their brains. Thank you!
As well as Arkady Kulik, Dave McClure, and all the LPs and GPs for their patience and willingness to go through all the revisions of this blogpost!
While this was a team effort here, many of this blogpost’s contributors chose to stay off the record.
The year was 1997.
Nomar Garciaparra was an instantaneous star, after batting an amazing .306/.342/.534. For the uninitiated, those are phenomenal stats. On top of batting 30 home runs and 11 triples – the latter of which was a cut above the rest of the league, it won him Rookie of the Year. And those numbers only trended upwards in the years after, especially in 1999 and 2000. Garciaparra became the hope for so many fans to end the curse of the Bambino – a curse that started when the Red Sox traded the legendary Babe Ruth to the Yankees in 1918.
Then 2001 hit. A wrist injury. An injured Achilles tendon. And the fact he needed to miss “significant time” earned him a prime spot to be traded. Garciaparra was still a phenomenal hitter when he was on, but there was one other variable that led to the Garciaparra trade. To Theo Epstein, above all else, that was his “fatal flaw.”
Someone that endlessly draws my fascination is Theo Epstein. Someone that comes from the world of baseball. A sport that venture draws a lot of inspiration, at least in analogy, like one of my fav sayings, Venture is one of the only types of investments where it’s not about the batting average but about the magnitude of the home runs you hit.
If you don’t follow baseball, Theo Epstein is the youngest general manager in the history of major league baseball at 26. But better known for ending the Curse of the Bambino, an 86-year curse that led the Red Sox down a championship drought that started when the Red Sox traded Babe Ruth to the Yankees. Theo as soon as he became general manager traded Nomar Garciaparra, a 5-time All-star shortstop, to the Cubs, and won key contracts with both third baseman Bill Mueller and pitcher Curt Schilling. All key decisions that led the Red Sox to eventually win the World Series 3 years later.
And when Theo left the Red Sox to join the Chicago Cubs, he also ended another curse – The Curse of the Billy Goat, ending with Theo leading them to a win in the 2016 World Series. You see, in baseball, they measure everything. From fly ball rates to hits per nine innings to pitches per plate appearance. Literally everything on the field.
But what made Theo different was that he looked at things off the field. It’s why he chose to bet on younger players than rely on the current all-stars. It’s why he measures how a teammate can help a team win in the dugout. And, it’s why he traded Nomar, a 5-time All Star, as soon as he joined, because Nomar’s “fatal flaw” was despite his prowess, held deep resentment to his own team, the Sox, when they tried to trade him just the year prior for Alex Rodriguez but failed to.
So, when Danny Meyer, best known for his success with Shake Shack, asked Theo what Danny called a “stupid question”, after the Cubs lost to the Dodgers in the playoffs, and right after Houston was hit by a massive hurricane, “Theo, who are you rooting for? The Dodgers so you can say you lost to the winning team, or Houston (Astros), because you want something good to happen to a city that was recently ravaged by a hurricane.”
Theo said, “Neither. But I’m rooting for the Dodgers because if they win, they’ll do whatever every championship team does and not work on the things they need to work on during the off season. And the good news is that we have to play them 8 times in the next season.”
You see, everyone in VC largely has access to the same data. The same Pitchbook and Crunchbase stat sheet. The same cap table. And the same financials. But as Howard Marks once said in response how you gain a knowledge advantage:
“You have to either:
Somehow do a better job of massaging the current data, which is challenging; or you have to
Be better at making qualitative judgments; or you have to
Be better at figuring out what the future holds.”
For the purpose of this blogpost, we’re going to focus on the first one of the three.
What is value?
To begin, we have to first define a term that’ll be booking its frequent flier miles for the rest of this piece – expected value.
Some defined it as the expectation of future worth. Others, a prediction of future utility. Investopedia defines it as the long-term average value of a variable. Merriam-Webster has the most rudimentary definition:
The sum of the values of a random variable with each value multiplied by its probability of occurrence
On the other hand, venture is an industry where the beta is arguably one of the highest. The risk associated with outperformance is massive as well. And the greatest returns, in following the power law, are unpredictable.
We’re often blessed with hindsight bias, but every early-stage investor in foresight struggles with predicting outlier performance. Any investor that says otherwise is either deluding you or themselves or both. At the same time, that’s what makes modeling exercises so difficult in venture, unlike our friends in hedge funds and private equity. Even the best severely underestimate the outcomes of their best performers. For instance, Bessemer thought the best possible outcome for Shopify was $400M with only a 3% chance of occurring.
Similarly, who would have thought that jumping in a stranger’s car or home, or live streaming gameplay would become as big as they are today. As Strauss Zelnick recently said, “The biggest hits are by their nature, unexpected, which means you can’t organize around them with AI.” Take the word AI out, and the sentence is equally as profound replaced with the word “model.” And it is equally echoed by others. Chris Paik at Pace has made it his mission to “invest in companies that can’t be described in a single sentence.”
But I digress.
Value itself is a huge topic – a juggernaut of a topic – and I, in no illusion, find myself explaining it in a short blogpost, but that of which I plan to spend the next couple of months, if not years, digging deeper into, including a couple more blogposts that are in the blast furnace right now. But for the purpose of this one, I’ll triangulate on one subset of it – future value as a function of probability and market benchmarks.
In other words, doubling down. Or re-upping.
For the world of startups, the best way to explain that is through a formula:
E(v) = (probability of outcome) X (outcome)
E(v) = (graduation rate) X (valuation step up from last round) X (dilution)
For the sake of this blogpost and model, let’s call E(v), appreciation value. So, let’s break down each of the variables.
Graduation rates
What percent of your companies graduate to the next round? I shared general benchmarks in this blogpost, but the truth is it’s a bit more nuanced. Each vertical, each sub-vertical, each vintage – they all look different. Additionally, Sapphire’s Beezer recently said that it’s normal to expect a 20-30% loss ratio in the first five years of your fund. Not all your companies will make it, but that’s the game we play.
On a similar note, institutional LPs often plan to build a multi-fund, multi-decade relationship with their GPs. If they invest in a Fund I, they also expect to be there by Fund III.
Valuation step ups
How much greater is the next round’s valuation in comparison to the one in which you invested? Twice as high? Thrice? By definition, if you double down on the same company, rather than allocate to a net new company, you’re decreasing your TVPI. And as valuations grow, the cost of doubling down may be too much for your portfolio construction model to handle, especially if you’re a smaller sub-$100M fund.
It’s for the same reason that in the world of professional sports, there are salary caps. In fact, most leagues have them. And only the teams who:
Have a real chance at the championship title.
Have a lot in their coffers. This comes down to the composition of the ownership group, and their willingness to pay that tax.
And/or have a city who’s willing to pay the premium.
… can pay the luxury tax. Not to be too much of a homer, but the Golden State Warriors have a phenomenal team and are well-positioned to win again (at least at the time of this blogpost going out). So the Warriors can afford to pay the luxury tax, but smaller teams or teams focused on rebuilding can’t.
The Bulls didn’t re-sign the legendary Michael Jordan because they needed to rebuild. Indianapolis didn’t extend Peyton Manning’s contract ‘cause they didn’t have the team that would support Peyton’s talents. So, they needed to rebuild with a new cast of players.
Similarly, Sequoia and a16z might be able to afford to pay the “luxury tax” when betting on the world’s greatest AI talent and for them to acquire the best generative AI talent. Those who have a real chance to grow to $100M ARR, given adoption rates, retention rates, and customer demand. But as a smaller fund or a fund that has a new cast of GPs (where the old guard retired)… can you?
Dilution
If a star player is prone to injury or can only play 60 minutes of a game (rather than 90 minutes), a team needs to re-evaluate the value of said player, no matter how talented they are. How much of a player’s health, motivation, and/or collaborativeness – harkening back to the anecdote of Nomar Garciaparra at the beginning – will affect their ability to perform in the coming season?
Take, for instance, the durability of a player. If there ‘s a 60% chance of a player getting injured if he/she plays longer than 60 minutes in a game and a 50% of tearing their ACL, while they may your highest scorer this season, they’re not very durable. If that player missed 25% of practices and 30% of games, they just don’t have it in them to see the season through. And you can also benchmark that player against the rest of the team. How’s that compared with the team’s average?
Of course, there’s a parallel here to also say, every decision you make should be relative to industry and portfolio benchmarks.
How great of a percentage are you getting diluted with the next round if you don’t maintain your ownership? This is the true value of your stake in the company as the company grows.
How does one use the appreciation value equation?
E(v) = (graduation rate) X (valuation step up from last round) X (dilution)
If the expected value is greater than one, the company is probably not worth re-upping. And that probably means the company is overhyped, or that that market is seeing extremely deflated loss ratios. In other words, more companies than should be, are graduating to the next stage; when in reality, the market is either a winner-take-all or a few-take-all market. If it is less than or equal to one, then it’s ripe to double down on. In other words, the company may be undervalued.
And to understand the above equation or for it to be actually useful (outside of an abstract concept), you need market data. Specifically, around valuation step ups as a function of industry and vertical.
If you happen to have internal data across decades and hundreds of companies, then it’s worth plugging in your own dataset as well. It’s the closest you can get to the efficient market frontier.
But if you lack a large enough sample size, I’d recommend the below model constructed from data pulled from Carta, Pitchbook, and Preqin and came from the minds of Arkady Kulik and Dave McClure.
The model
The purpose of this model is to help your team filter what portfolio companies are worth diving deeper into and which ones you may not have to (because they didn’t pass the litmus test) BEFORE you evaluate additional growth metrics.
It is also important to note that the data we’ve used is bucketed by industry. And in doing so, assumptions were made in broad strokes. For example, deep tech is broad by design but includes niche-er markets that have their own fair share of pricing nuances in battery or longevity biotech or energy or AI/ML. Or B2B which include subsectors in cybersecurity or infrastructure or PLG growth.
Take for instance…
Energy
Energy sector appreciation values and follow-on recommendations
The energy sector sees a large drop in appreciation value at the seed stage, where all three factors contribute to such an output. Valuation step-up is just 1.71X, graduation rates are less than 50% and dilution is 38% on average.
Second phase where re-upping might be a good idea is Series B. Main drivers as to such a decision are that dilution hovers around 35% and about 50% of companies graduate from Series A to Series B. Mark ups are less significant where we generally see only an increase in valuation at about 2.5X, which sits around the middle of the pack.
Biotech
Biotech sector appreciation values and follow-on recommendations
The biotech sector sees a large drop in appreciation value at the Seed stage. This time, whereas dilution seems to match the pace of the rest of the pack (at an average of 25%), the two other factors shine greater in making a follow-on decision. Valuation step up are rather low, sitting at 1.5X. And less than 50% graduate to the next stage.
In the late 2023 market, one might also consider re-upping at the Series C round. Main driver is the unexpectedly low step-up function of 1.5X, which matches the slow pace of deployment for growth and late stage VCs. On the flip side, a dilution of 17% and graduation rate of 60% are quite the norm at this stage.
In closing
All in all, the same exercise is useful in evaluating two scenarios – either as an LP or as a GP:
Is your entry point a good entry point?
Between two stages, where should you deploy more capital?
For the former, too often, emerging GPs take the stance of the earlier, the better. Almost as if it’s a biblical line. It’s not. Or at least not always, as a blanket statement. The point of the above exercise is also to evaluate, what is the average value of a company if you were to jump in at the pre-seed? Do enough graduate and at a high enough price for it to make sense? While earlier may be true for many industries, it isn’t true for all, and the model above can serve as your litmus test for it. You may be better off entering at a stage with a higher scoring entry point.
For the latter, this is where the discussion of follow on strategies and if you should have reserves come into play. If you’re a seed stage firm, say for biotech, using the above example, by the A, your asset might have appreciated too much for you to double down. In that case, as a fund manager, you may not need to deploy reserves into the current market. Or you may not need as large of a reserve pool as you might suspect. It’s for this reason that many fund managers often underallocate because they overestimate how much in reserves they need.
If you’re curious to play around with the model yourself, ping Arkady at ak@rpv.global, and you can mention you found out about it through here. 😉
Stay up to date with the weekly cup of cognitive adventures inside venture capital and startups, as well as cataloging the history of tomorrow through the bookmarks of yesterday!
The views expressed on this blogpost are for informational purposes only. None of the views expressed herein constitute legal, investment, business, or tax advice. Any allusions or references to funds or companies are for illustrative purposes only, and should not be relied upon as investment recommendations. Consult a professional investment advisor prior to making any investment decisions.
It’s not every day one gets to sit down and experience a Chinese tea ceremony under a late afternoon Los Altos sun. Sitting across from me was a gentleman in a white tee who moonlighted as a tea connoisseur. As such, he was in the middle of passionately describing to me what was some of the best tea I’ve had to date.
“David, smell this blend three times. You’ll realize that each breath you take will smell completely different from the last.”
To my bewilderment, he was right.
As I handed the teapot back to him, he continued, “Now the first pour you always pour out. Here, we are just washing the tea leaves. But we use this opportunity to also coat the insides of your teacup with the flavors of this next tea.”
True to his word, he awakened the inner mold of my cup with the smoky liquid infused by leaves that had been aged longer than I’ve been alive. Then poured the first pour back onto the teapot with the lid on, creating a wet seal around the teapot. As a result, the leaves were washed. The aromas are concentrated in the pot. And the cup has been given time to get to know the tea.
When, finally, the teacup landed back in my hands, I could taste the unfiltered, rich, smoky, yet mellow aroma of a Wu Yi Shui Xian tea.
If I didn’t know any better, I’d never have guessed his “day” job was being an investor. Specifically, a pre-seed and seed deep tech investor.
Of course, you’re smart. Given the title of this blogpost, you didn’t come here to read about the intricacies of drinking tea. But about the intricacies of deep tech, which in the process of editing this piece, I realize deep tech happens to have the same initials as drinking tea. But that’s not only stretching it, but I digress.
The fine gentleman who sat across from me in a white tee, his name is Arkady Kulik, Co-Founding Partner of rpv, a fund dedicated to backing early-stage scientifically intensive teams. In other words, deep tech. Currently, the industry itself is highly fragmented. In Arkady’s words, “it’s like investing in IT in the 80s. But they’re all ventures that can completely reshape the landscape.”
As Arkady continued, he shared something else quite fascinating. “In software, you’re looking at a high market risk and low technological risk. In deep tech, it’s the exact opposite. We have a low market risk and high technological risk. The problem is not whether they can sell this to people, but rather whether they can build it.”
Naturally, as someone who spends little time looking into the deep tech world week to week, I had to double click on that. What followed was a conversation where I found myself wishing I could take notes faster.
Smelling the tea leaves
As a non-technical person, the biggest question for me has always been: How do you evaluate a deep tech deal?
To Arkady, it’s the entry point in price as a function of Technology Readiness Level. TRL, for short.
Source: rpv’s Investor Deck (and yes, Arkady gave me permission to share this)
“TRL is actually something that the team at NASA came up with. NASA has always had a lot of internal projects, and they needed some internal tool to evaluate the readiness of those projects.
“It was developed in the 1970s, but was formalized in the decade after. One through three on the TRL scale is all theory. They’re largely funded by the government through grants and such. Seven through nine on the scale is commercial, and covered by generalist VCs. Everything in between is in some form of a product development process. That’s where we come in.
Source: rpv’s Deck, citing NASA TRL levels
“To get the graph above, we take TRL levels on the X-axis and the historical round size data on the Y-axis. Then we looked at every single company, took the lowest and highest round in each vertical within deep tech, and mapped it out.”
While every firm’s “blue box” is different — and after learning about this, I do encourage every deep tech firm to go through such an exercise, rpv’s sweet spot is companies leveraging technologies TRL 3-6 whose round is shy of $1.5 million.
The first pour: Tea meets cup
After passing through the smell test, the first question Arkady tries to answer is always: Is it BS? “I look at every deck myself. No analyst. No associate.”
After Arkady looks at the deck, he then sends it to his team. “They give me one of three scores: green, yellow, or red. If it’s positive — meaning either green or yellow, I take the first meeting. We have 12 deal breakers, ranging everything from lack of ability to protect IP (it’s why we don’t do software deals) to tech, finance, or team conflicts of interest. If any of us in diligence raise a flag, we don’t continue. If not, we ask specific questions to the team.”
When meeting with the team, the question of founder resilience always comes up. Of course, every investor measures grit differently. I ask about excellence and scar tissue, but I was deeply curious as to what Arkady asks for.
“I try to gauge it from learning about founders’ past experiences (not necessarily professional ones),” he goes on, “I dig deeper on tough situations a founder has faced. Also proposing hypothetical scenarios about their fundraising or team dynamics help a lot in understanding that facet.”
Without a beat, I follow up, “For that, do you have any go-to questions?”
“Nothing formal. I try to find an experience in someone’s past that could be good grounds for showing resilience: competitive sports, PhD, previous startups, complicated and long-term projects in the corporation or something like that.
“For the hypothetical scenarios, I ask things like ‘What if you won’t gather the round?’ Or ‘What if your co-founder absolutely had to resign, what’s your action plan in the bus factor case?’
“It’s an area where you look at how they react, not just what they say. How does their body language change when they’re answering the question. It’s about the non-verbal signals. ‘Tell us an experience in the past and things didn’t go your way, and things were dragging.’ Was it when you applied to college? Or went for your PhD? Or when you were trying to go on a date with someone you liked?’
“Resilient people usually have some kind of Plan B. People who don’t have another plan and still try the same thing again and again are stubborn. We don’t seek stubbornness in entrepreneurs. We look for their ability to be honest with themselves and other people.”
The second pour: Tasting the depth
“If there are no red flags after meeting the founders, then we move into scientific due diligence. We ask everything from deep scientific questions (on isotopes or wavelengths) to the feasibility of the product — essentially a peer review on a paper by our internal, but also external scientists and advisors. The latter to get a truly unbiased opinion.
“Then we do a deeper diligence process with a scorecard of 35 items from team composition to their stage of development to their ability to protect IP to the availability of competition, each rated twice. Once by myself, and another by our advisors and venture partners. Then we average the points out for each of the 35 items and compare against our thresholds. If it’s a green light, we make an investment decision. If yellow, we follow up with the target venture’s team to see if they have a good answer to our concerns. And if not, then we say no. If red, well, we also say no. Though we have yet to give a red final score after using the scorecard since they’ve all died during the extensive due diligence process.”
In our conversation, which eventually migrated to Zoom (with some people, you just never run out of things to ask), I postulated about the variability in venture firms using scorecards. There are strong reasons why you should or shouldn’t from both sides of the aisle. Both of which have generated great returns for their LPs.
Today, many of the top tier venture firms make outlier decisions based on gut. It’s the same reason why generational or succession planning at these top firms are so hard. Once the GP leaves or retires, the next generation have a hard time making the same investment decisions as the previous generations.
On the scorecard end of the spectrum, hedge funds are, by definition, firms who employ algorithmic discipline to generate alpha. On the venture side, you have Correlation Ventures, SignalFire, just to name a few. Seven years back, Social Capital’s Capital-as-a-Service, just to name a few. The last of which seemed to have been deprecated due to the inability to scale support for a portfolio of 500 startups, rather than the inefficacy of their “scorecard.” As you might suspect, a topic I’m quite fascinated about.
“We make our decisions based on scorecards,” Arkady reaffirmed, “And if you were to look at each one we’ve done, you’ll see that it’s rare that our team sees eye to eye. We disagree a lot. It’s an individual decision and we take it. And we never try to convince the other to change their score. We trust each other to give a score we believe in. For advisors, since we have many, we take the average of all their opinions. We also ask different advisors for each item on the scorecard. Some advisors are excellent in one area, but might not be fluent in another.
“The final thing I’ll say is that when something feels off, we say no. Even if the data shows green, but we’re unsure about the validity of the data, we still pass. One of the best pieces of advice I got around hiring is if you’re not sure about a hire, pass. It’s the same with investing.”
For Arkady, that is the weapon of their choice.
In closing
Between three calls and a tea ceremony, even then, we only touched the tip of the iceberg. One I’m likely to have many more questions for Arkady and my other friends who live and breathe in this space. It’s an exciting space. To be fair, even calling it all just one space is an understatement. It’s a permutation of many that’ll be segmented when the broader investment community starts to understand them all better. Myself included.
Looking forward to it all, and appreciate you, Arkady, for all the back and forth edits, lessons, and the tea!
Stay up to date with the weekly cup of cognitive adventures inside venture capital and startups, as well as cataloging the history of tomorrow through the bookmarks of yesterday!
The views expressed on this blogpost are for informational purposes only. None of the views expressed herein constitute legal, investment, business, or tax advice. Any allusions or references to funds or companies are for illustrative purposes only, and should not be relied upon as investment recommendations. Consult a professional investment advisor prior to making any investment decisions.
