Q&A: Angel Investing Ticket Size & Equity, Investment Pitfalls and Media & Art Trends (NFTs & Generative AI) - E244

In this episode of BRAVE, Jeremy Au and Adriel Yong discuss the typical ticket size for angel investors and its expected equity, LP fund allocation on specific verticals, pitfalls to avoid, current media and art initiatives and trends like NFTs and generative AI and transitioning to a VC role from a corporate partnership director background.

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Jeremy Au: (00:00)

Hey, Adriel. Another Q&A session from another listener. So what do you have for me?

Adriel Yong: (56)

Yeah, so this listener's profile, he's an executive at a large payments company. He’s looking to start getting involved as an angel investor and even as an LP incident fund. So he has questions around those types of stuff. First, as an angel investor, what are the typical ticket sizes and how much equity should an angel expect from getting a ticket?

Jeremy Au: (05:37)

What's interesting is that these numbers are really for Southeast Asia, which is a very large market with different geographies, right? And each geography has also its own specific dynamics. I would say, and feel free to disagree with me, whoever's listening, is that I think the entry-level is probably around $5,000 for many startups, especially for example, in countries like the Philippines or, you know, kind of like areas that have less capital.

And then it may be a bit higher, for example, maybe around a 10 grand mark in Singapore, right? Or Indonesia. And then obviously that flows up all the way to as much as you wanted to put in. But you may see up to like, 10 grand, 20 grand, 50 grand, even a hundred grand for angel check sizes depending on their approach and how much conviction they have. I think what we're also seeing is that as there are more angel syndicates and SPV vehicles are starting to be built, and so they're trying to push that floor down to like about $1,000 so that anybody who is accredited but is willing to kind of like come in, gets the opportunity to come in.

So that's an interesting dynamic where they're trying to make it more accessible to folks. I think the tricky part that was asked was like, you know, for how much equity would such a check size give you? And obviously at one level is, the more money you put in, the more equity you're gonna get, right?

And so I think that makes a lot of investors who are excited about the company tend to, for example, put in larger check sizes. What's unclear of course is what is the exact price of, you know, for each quantum of a dollar that you put in. And so the truth of the matter, the market in Southeast Asia has pretty much moved away from price rounds that historically used to be priced, you know, say even five years ago was very common in Southeast Asia, but now I think almost everybody using some version of the SAFE note, which is a form of convertible debt.

Another way of saying it is that there is no assignment of the price for that quantum, but it’s determined by the price of the next round when an institutional investor comes in. And that's the transaction. That's the due diligence. That's the negotiation and sets a price. And so at the next funding round, hopefully in two years, for example, then all these SAFE notes, comfortable debt gets converted at the same time. And so on average, the angel investors who came in around earlier than the institutional seed investors should hopefully get a lower price. Or now we're saying is that they tend to get more shares for the equivalent, the same quantum that institutional investors get, right. In other words, earlier, investors are rewarded for taking on that risk premium by getting a little bit more ownership for the same buck.

Now that's theoretical. I think what we've seen actually, of course, is that a lot of the SAFE notes, especially for high-performing companies, and when I say high performing is that they're good at fundraising or they've very great revenue numbers, is that they tend to have reset, I think what used to be the two variables that used to give this reward for taking on the risk premium.

So, that would be the discount rate, as well as the valuation cap. So discount rates, historically, for example, it was very common to see a 20% discount rate, which basically means that hey, for coming in this round early, uh, two years in advance of the next round, you'll basically get 20% more shares compared to the person who comes in in two years time, which I think is actually very theoretically sound, especially because if you look at the numbers out there, there's actually, I think at least a 50% death rate from the angel round to the next round, or you may even argue is even higher on average if you include, you know, just all the other startups that try to raise. And so what that implies a little bit is that I think the average investor, angel investor tends to actually already, take on too much risk, you know because they're not adequately compensated. The risk of coming in two years early for that 50% death rate, but they only get a 20% discount for the upside, right? So, that being said, I think obviously there's a fair point that for the best high-performing companies, et cetera, the reason why they no longer discount rate is because they're basically saying like, you know, this is your only chance to be able to come in.

So better for you to come in early, otherwise you can be squeezed out by the seed investors down the road, right? So, that being said, discount rates disappeared during the bull markets of, you know, 2021 and even 2022. What's interesting to see in 2023 is that discount rates are starting to come back because again, I think, you know, this is a fun, you know, it's a market setting price mechanism, between the supply of capital from angel investors and the demand for capital, by founders who need capital, so this is pricing mechanism or equilibrium that's starting to be debated. And then cause valuation caps are also quite complicated.

And now, now we're saying that if the company outperforms that target, that valuation cap, then the early investors get rewarded for that. Which again is a nice way of saying that if you're super bullish in a company, then you know, you get a bump on that, you can see Ray breaks down pretty fast again, because quantitatively 50% of companies at least die in the stage.

And it's hard to predict which ones are, on average, most angel investors, especially newer angel investors, are too optimistic. And so, I think this is often something that, you know, angel investors kind of like understand the math only two years in or three years in, and then, they’re kind of like, oh no, you know, didn't really get rewarded.

For a whole range of outcomes, for example, they hit their performance target or they were below the performance target, but still viable. Then there's no spread of reward. So personally, I think if you're an intro investor, I think if you're a choice, I think a discount rate of 20% gives you a flat, consistent, reward for coming in two years earlier, being the first believers in the company across a whole range of outcomes from you.

Average to above average to great performance. So I think that's what I recommend angel investors to look at. But I think, the market probably uses more valuation caps, so all in all, I think what the price is set at the end of the day, down the road by the next round investors. But I think the question is how much more of a premium do you get, right? And so I really recommend a book called Venture Deals by Brad Feld. There's also a lot of online courses around SAFE notes, but I think these are great ways to train and understand the math because you have to do the math, right? That being said, when you think about that, you have to think about price, but also you have to think about the death rate. Or on the converse of that is your ability to pick the winners unicorn pick rate, as well as thinking about capital efficiency, right? How much capital are they gonna raise? Because at the end of the day, what you get at the end of the transaction, in 10 years or 15 years, is what is the capital diluted ownership stake at the end of that time period, right? And so for example, if the company obviously died, then you get nothing, right? If the company was highly successful, you get more money. That being said if the company was highly capital efficient, then you get more money. But if the company burned a lot of cash and was capital-inefficient, then they had to raise a lot of funding. And so your dilution of the ownership stake is quite substantial. And so you have a much smaller stake than you would have had even though it was a successful outcome. So I think you think about those three. Think of it as a triangle, what's the price they're getting in at right now, of course.

Second is your ability to pick the winner. And also to avoid picking the companies that will die. And the third, of course, is the capital efficiency that you expect for the invest investment. So as a result, what it means is that price does matter, and it's one part of that tripod. That being said, you have to act as part of a syndicate because most angels don't have negotiating leverage. And so, you know, to some extent, if you can't negotiate, then why think about price? Just take the price. But if you can negotiate with other folks, then that's worth discussing with the founder. And I think one thing that's also a bit underrated is, if you are deploying certificate sizes and deploying equity, you're making a decision about the price.

Do you also actually improve the startups odds? So if you actually help the startups substantially and you actually help improve the odds, you double their success rate, et cetera, then to some extent, you could probably use that to negotiate a better price. Or you can be more comfortable with a more expensive price to you because you know that the success rate would be much higher than the market would expect it to be.

Adriel Yong: (14:46)

Yeah. And you know, I think after this, there's also this question about when you invest in a fund as an LP, is it possible to request for allocation on specific initiatives?

Jeremy Au: (15:01)

Yeah. So, you know, I'm gonna take this question as specific initiatives as in like, can you go towards certain investment verticals or can you go for a certain mandate? And the answer is that for the general LP, the answer is no, because your ticket size is probably too small for the fund to justify a whole novel structure, to you know, especially when there are so many other LPs to do, right?

So you can imagine it's a big decision. And the truth is if you really do believe, a specific initiative that you really believe in, maybe it's better for you to look for a fund that actually reflects those full initiatives within mandate, right? Rather than look at trying to incentivize a fund to kind of like do those sub things.

That being said, if you are like the largest LP, you know, for example, you are a very large institution compared to a small fund, or you know, you are by far the anchor investor. So you are the first investor and you're doing a very large chunk of the total, you know, first capital call for example, then you may have leveraged to be able to do that request, right?

So perhaps you may request for a common one. Requesting for specific ESG goals to be reported, and metrics to be collated and achieved. Or for us, you may mandate and ask for the opportunity to be able to have the first right to co-invest in a follow one round, for example. So, the answer’s generally no. But there are exceptions, especially if you are the largest LP.

Adriel Yong: (16:42)

And how about pitfalls to avoid, whether it's an LP.

Jeremy Au: (16:48)

I think I focus more on the angel side. You know, I think first of all is, you know, overall the truth is technology is really hard, right? And what that means is that you know, AngelList for example, had data that only one in 40 US startups that have received a high-quality seed round will actually make it to become a unicorn eventually, right? And that's really tough arts. This is the US ecosystem that is more mature, more capital, and probably more curated than than, for example, in Southeast Asia. And you know, it's just a hard, hard, hard, domain to build, right? And so a lot of respect post the founders who are willing to take those odds, and build for the future, you know, for a lot of investors as a result, they underestimate how hard it is. And so, you know, if you have one fault, how it's like effectively equivalent to roulette, right? So you know, how many spins out the roulette wheel do you have to do, and how far to be successful? So what has to be done is, first of all, understand that you have a growth curve.

So I think, you know, roulette is hard, right? And so the truth is the average investors picking effectively the average investors picking at average, right? Because this average investor pick average, you know, track record, right? And again, all these companies will have some high-quality signals why they receive a C capital, right? So, tech is hard to build. And tech investing is also hard because it limits capital. And so I think, the pitfall to avoid is to avoid underestimating how hard it is that dispute is and therefore how hard it is to actually invest and pick the winners. So what that means is that some folks, perhaps they come in, they think it feels easy, it feels like there's a lot of great people. They're very excited and they tend to invest a lot. They tend to invest early and they tend to invest quickly. And so, what they undervalue is that they're gonna get smarter over time as they see more and more companies. They see at least 40, 80, 120, 160, you know, 400, right?And as they see more and more companies, then their ability to discern companies improves over time. And so, what you may find is that a lot of angels kind of like, got much smarter in one year, two years, three years, four years, but then ended, having insufficient capital for this latter part period of their investing time because they spent all of it upfront.

So, that's one way to think about it. Another pitfall is investing. The tickets are too large. So it's another version of what we just said, which was investing too early in the early experience curve. But in this version, you're investing very large tickets. And the reason why investing large tickets can be a problem is that again, obviously you're excited for the company, so you think it's gonna be a success.

So you're always going to put in more quantum because you think that is going to give you more ownership. So I think broadly, that makes sense. You always wanna put more money into the companies that you're more confident about. That being said, this is a portfolio. So in investing, they say diversification is the only free lunch in investing. And what that means is that, the truth is even though you think they're great, you know, perhaps they're insufficiently diversified for geography, or founder type, or vertical, or approach, or go-to-market. And so basically, you need to aim for a portfolio actually of about 40 investments and you perhaps wanna disperse that across.

You know, for example, four years, right? Or five years or six years. But you wanna disperse over a certain period of time because, so that you have different time diversification for the vintages. And you generally want to, again, because of the experience curve we just mentioned, you wanna invest less in earlier years and invest more in year three, year four, year five.

And you wanna have about that for all the investments because again because that gives you a better chance to be able to pick versus if your portfolio was just like, for example, five investments. I think the math shows quite, statistically quite clearly that you have a much worse chance of actually generating a return because you're much more likely to miss that one hour, 40 chance that generates that unicorn outcome.

So I think there's a good benchmark. I think some people obviously aim for more, they aim for a hundred investments, for example, but they may do that over 10 years. So I think just being thoughtful about that is quite key. The last thing that I think is a bit underappreciated is actually, you know, investing in yourself first, right? And then invest in for example, your health insurance, then your non-health insurance, then your house, then your stocks, then your bonds, right? And then maybe your exotic instruments, which includes private capital like LP investments or angel investments. And the reason why of course is that, to be very frank, your angel investments or even your LP investments are very illiquid.

You know, they can only be there and be cashed out in 10 or more years, which means that it takes forever to unlock it. Right? And with no guarantee of return, because we don't know whether you're a good investor or not. And so this illiquidity of the investment basically effectively means that you can't use it for anything else. You can't use it to pay for your kids' school. You can't use it to pay for class. You can use it for your, you know, health insurance. So this capital's effectively locked, and it's so hard to unlock it because if you wanna sell secondaries, for example, in the VC fund or in the individual investments that you made, these secondary sales aren't, can be at 30% or even up to 50% discount versus the actual value, which effectively wipes out any of the gains that you have from picking, which makes it very, I think, ineffective as a way to get liquidity.

So in other words, I think you wanna invest in the fundamental layers first. And if you're trying to invest in experience, then yeah, if you have to do it, just do the smallest check possible, join syndicates, put in one grand, and lean towards that lower end at a start, and then kind of ramp up over time once you get more comfortable with the actual reward-risk dynamics into investments.

Adriel Yong: (24:28)

Yep. And I think the next question we have is, an aspiring angel is thinking about what are the top three initiatives this year and whether there are any related to like media and art. So I think what are some of the teams and sector trends that you're seeing in relation to that, you know, from a VC funding perspective?

Jeremy Au: (24:50)

Well, uh, I think, in the past few years it was all about NFTs, right? Non-fungible tokens, which is the concept of digital scarcity. It does feel like the wave has passed. So, especially with the crash of the asset prices where you know, the truth of the matter is, I think digital scarcity is a real thing.

I think it's a great invention and innovation to cryptographically create unique items. So I do think, obviously there's value there in terms of technology. I just think that using it as an investment instrument, or even as a commodity, you know, I think it's very much subject to the actual intrinsic value of this asset. Compared to the infinite copies they can make of the asset as well. Effectively, so I think, let's not confuse the two things. I think there's real value with NFT’s standard, fungible tokens and digital scarcity, which will continue to be relevant for media and art in the medium to long term. But I think a lot of the hype has been let out of the entire wave. And so I think there's a bit of a sober conversation now, which is how does NFTs, for example, really relate to that? I think the second thing that's a key initiative is really, of course, generative AI, which is basically a concept of AI-generating content, right?

So historically, AI, you know, was a function of digitizing, for example, things that are very automatable. So primarily numbers, right? So for example, the concept of excel and accounting and you know, we call it AI automation or just rule base or scenarios. But the core concept was basically numbers will flow from A to B to C. And you know, this is certain logic to it, right? And so I think there was a big future where I think McKinsey did a good report, which was like, hey, you know, accountants are very high risk of AI. Automation and replacement because, you know, they're just doing math right? And so computers can totally do math.

What really came out of nowhere was that the concept that digital designers and writers, you know, if you actually look at that McKinsey report on digitalization, it was not really considered high-risk because it was, it felt that there was a level of creativity and, you know, value of work that just made it hard to replace. And what has turned out is that actually because the whole internet has been open, you know, basically AI was able to scrape live journal, Tumblr, Twitter, you know, everybody's web pages, blogs, every news article and has been able to basically use that database to pass and obviously with, you know, GPT 2.5 and now GPT 4 coming up, be able to transform and basically use those content and resize patterns, right?

And it turns out that most of us who are writers are not much better than AI. Because of it just passing what we read and then we rewrite it. So I think it's not that AI has gotten really good. I think it's just that the average writer has given themselves too much credit, including myself, about what the novelty is in terms of writing.

And so I think generative AI is a big piece. And I think a lot of startups are trying to re-skin or create a 10 layer to, you know, kind of like apply this generative AI. So they're trying to create or example, unlimited ads, creation for the copy, and images for startups. Or another one I think I've seen is that they want to automate the writing of children's books for other parents, right? They're just trying to replace and create that highly personalized, infinite content creation, but also hopefully more curated or tailored right for that mainstream requirement. And of course, do that at effectively almost zero cost or very low cost. So I think that's a really crazy thing that's happened. And I think this honestly is way more transformative in many ways. I think because the previous, what we talked about was the monetization of a new content category. This is what we're doing we're actually breaking the cost barrier and curve content means. And what that means honestly, is a third trend that comes out from median art is there's gonna be a barbell of the content creation industry. So what that means is that I think historically, the biggest example from my perspective is this is like the creation of the mechanical loom. People used to weave, right? So there was this huge weaving industry where folks at home were basically sewing, right? And they were sewing quilts and clothes and all these things. And so basically they were literally like millions of garments being built across, sold across hundreds of thousands of homes. And obviously there were great weavers and there were like average weavers and there were weavers who were not really very good. And so there was a very nice, you can call it, you know, bell curve of weavers, right? But with the mechanical loom, basically, they automated the creation of, you can call it blankets, you can call it clothes, and so, so forth.

But they automated the weaving of it using steam power, electric power. But also, they simplified the job tremendously. And basically what it did was that it barbelled the industry. So instead of creating a kind of like a bell curve, it created a barbell, right? So the middle disappeared, which is that basically, you know, on one end, you had all these folks who basically became factories, right?

So factory owners basically built these giant factories with lots of mechanical looms and with lots of low-skilled labor to basically generate lots of high commoditized, you can call it low quality, but you know, it was good to average quality, acceptable quality, but at a much lower price, right?

And so, you know, the middle-class weaver just disappeared, right? And had to re-skill, retrain and do something else, or, you know, join one or the other. And these mechanical factory owners one and our other side, you know, you had this flight right to quality in a sense that some of that folks save themselves by becoming very artisanal, very bespoke, very high-quality weaving for the nobility and for an upper class. And so, you know, it's like, okay, if you're trying for a million white shirts, you're never gonna get it right. But you know, if you're looking for that bespoke silk of the en velvet combo, is directly tailored to your size and so, so forth, right? This could not be automated, you know, at that point of time. And so people were able to create that, you know, artisanal luxury approach, right? I think that's like gonna happen to content actually, which is, I think most people would just be average writers, right? You know and average writers don't mean necessarily mean that they can't write good quality content, but the truth of the matter was that to write great quality content was gonna take a week, you know, a lot of time, or you could write something pretty terrible in like 30 minutes, right? And so most people will count. Average writers are kind of like in that dynamic, including myself. What's gonna happen is that when you've generated AI, they can basically make something really, you know, better than my terrible writing, but do that for free and do that in one minute effectively.

Plus I'm editing or they could. Me, using AI could generate a high-quality piece, but do that in three days instead of like seven days. Then basically what is gonna happen is that there's, the average stay home writer doesn't exist anymore. Or this average stay home designer doesn't exist anymore. And so I think that’s what we're gonna see. The folks, the factories are really going to be able to best leverage this AI because they can mechanize it, they can have the best practices, and they have the capital. and they can use cheaper than average labor to do what that happens, right?

And so I think we really started seeing that now, which is, I think CNET and Buzzfeed both announce that they're gonna use a ton of generated AI content. And so they, CNET is basically saying, hey, we generate a whole bunch of really standardized content as SEO-friendly, right? So stock prices you can argue that product reviews are highly standardized. And so instead of paying this person a couple of hundred dollars to write it and take two days to write and actually try it for themselves, they can pay 1 cent, right? And get it done in one minute. And so, for them, instead of generating a hundred great pieces, they should generate a million acceptable pieces. And Google just gets totally swamped and says this is the best content we've ever seen. And, you know, just deals out of traffic. Right? Uh, so the conversion rate is lower per page, but you know, you have, you went for a million times, more web pages.

Doesn't really matter, right? I think the factory owners will win, and I think the best writers are gonna flee toward us writing very like membership, get the content, prove that they actually thought about it, prove that they actually are able to deliver it, right? Maybe they show that they're writing, they show that they're speaking, show that they're actually thinking about it. So that it's gonna be this artisanal writer, right? Or designer that can do something really special. So I think that's good. Those are the three trends, right? I know NFTs, obviously, which is digital scarcity. The second thing is generative AI and the thin, slash tick layer on top of it. And the third is the barbelling of the creator industry.

Adriel Yong: (34:57)

Yeah, I think we had a great conversation on the eutrophication of the internet and how the desire for authenticity and the need for authenticity will get stronger and stronger and you know how then you prove that your content is authentic. And I guess the great thing is now hey, we have proof that we are two real human beings talking to each other on video and the state of deep fix is not that advanced to create such an artificial reality yet, but you know, maybe in time to come, it will. So good luck to us then.

Jeremy Au: (35:31)

At that point in time then, what we're gonna flee to is gonna flee to fireside live chats to show that we're actually not being defected, you know, and notbeing replaced by something else. So that the flight to quality improvement of humanity will continue to happen now.

Adriel Yong: (35:46)

But isn't it so fascinating cause you know, we started off with that, right? And then, the internet came and everyone started to go online, social media, whether it's text, video, or audio. And then now because of how AI has happened that you know, lack of authenticity. Authenticity is like, pushing people back into the real world again to, seek authenticity and realness before, like the volume of content of access to information.

I just find that reversal so fascinating. A bit like just how you know, we think about Uber and taxis, right? Like, we were pushed to Uber from the usage of taxis, and then now people are like, oh, actually right here's too expensive. Let me go back to taxis, right? But guess what?

Because you know, all taxi prices are now way higher than what they used to be because of Grab and Uber's existence. So I think our next question is around, what do funds look for in their investment managers today. Um, I guess maybe you have sort of hired a bunch of VCs yourself, uh, or have overseen that process, right?

So could you get the, the listeners some insight into that?

Jeremy Au: (37:03)

I think funds are looking for investment managers who will find, choose and shepherd a company that becomes a billion dollars. And so I think the way I always explain it is like, in funds, if they could, they'll invent a time machine, right? And they'll peak in the future, right? They fast forward 20 years and they say, okay, you know, you successfully found and closed and did three deals that all became billion-dollar companies.

You know, or hack even. You do one I think is really good, right? Then they'll just dial back, jump back at the time machine, back to the present day, and say like, look, you're hired. So they're really looking for certainty in mind that you are actually gonna do that. Of course, there's no such thing as a time machine, but they're trying to do that mental forecast that you're going to be able to achieve that outcome. So in the absence of that, then they will probably look for the track record of you doing so, right? Or they can see that there's a trajectory for you to be able to do so. So, that's where the ability, and we discussed that in an earlier Q&A, that we'll hyperlink to, but at the end of the day, you know, they're looking for people who can source across the network, who are able to be thoughtful in their decision-making about what actually makes a great founder and great company with great tailwinds.

And lastly, to actually be able to shepherd them in terms of adding value, for example, by increasing to the upside, by hiring, or connections and strategic advice, but also preventing downside risk by, you know, catching fraud or, or making sure that they're here to certain board practices for the next stage. So I think those are the three things that, you know, funds are really looking for the ability to find, the ability to pick, and the ability to shepherd future unicorn.

Adriel Yong: (38:54)

Yep. This brings us to our final question from this listener, which is, given his extensive corporate experience as you know a partnership director at a large payments company, how should he position himself for a VC role?

Jeremy Au: (39:13)

Yeah, so, you know, with your finance experience, I would probably say that, it's relevant to FinTech because there are lots of banks that are potential partnerships in terms of go-to-market. They also potential future customers, and to some extent, again, you know, you understand. You know your customer or anti-money laundering, a whole bunch of other skills and domain expertise that honestly are really difficult for someone outside to really understand, especially if you haven't ever been in a bank.

That being said, of course one of the key concerns from a fund perspective is that, if you spend like five years at a large bank, do you actually have the DNA, for example, I think we had an earlier Q&A where the person was the founder, right? So now in your case, the question would be, do you actually have empathy for the founder? Is your advice going to be suited for startups? Or is there gonna be more suited for large companies? Are you gonna act in a big executive way within the fund, which is not often very entrepreneurial? Or are you gonna act as a great teammate who's kind of like jumping on initiatives and getting stuff done? So I think that's really the pros again, like domain expertise that you often can have and the networking but then now the contrast is, in this case, you actually have to demonstrate that you actually have the empathy as well as the ability to give the relevant advice for the role.

Adriel Yong: (40:35)

And yep. That's the end of our listener Q&A. Thank you so much, Jeremy, for sharing all those insights in your personal anecdotes.