Episode #15: Andrea Funsten, Robert Vinall, Manny Medina

It would be really cool to see memos on companies that didn't turn out to be large successes, completely unedited, because most of the things that end up happening with the company that made it maybe turn out to not be a success. I doubt were in the memo to begin with. It's the week of January 13th. Welcome to the Learning Corner, a Precursor Ventures podcast.

Welcome to the Learning Corner by Precursor. I'm Mia Farnam and I'm joined by our GP and Managing partner Charles Hudson, where we'll be talking through the goodreads and articles that caught our team's attention from the past week. Our first article is by Andrea Funston titled why Venture Capitalists Rarely Share Investment Memos. Andrea dives into the cultural hesitancy among VCs to share investment memos. She argues that the primary reason memos are rarely circulated isn't about confidentiality or competitive disadvantage. It' really about fear, specifically the fear of being wrong and being scrutinized for it. Andrea points out that this gatekeeping creates a barrier to transparency and learning in the venture ecosystem for investors and founders. Equally, sharing memos could foster greater collaboration, allow others to learn from your thought process, and even spark valuable conversations about risk, conviction and strategy. So Charles, we've had great conversations internally about memo culture, so there is a lot of directions to take this discussion. But I really love how how her argument really calls on investors to embrace the discomfort of being wrong as a way to build trust and openness and ecosystem. So obviously would love to hear what you thought.

Yeah, it's funny, I saw Andrea basically the day before she published this blog post at Blue Bottle of Pacific Heights and we had a chat about it. So I'm glad that she published it. You know, we don't really write memos at Precursor. I've always thought it's both difficult and frankly strange to write long memos about pre seed companies with no product, no traction, no historical financial really just people in an idea. But I respect and understand that other people's processes are really different. And I've talked to some firms who really feel like hey, memos help me think, they help me organize my thinking, they clarify like the why that we're doing this investment. You know, while we don't do formal memos, we do record a lot of our in real time thinking. And I've always thought what keeps me from publishing our memos. In most cases I'm actually not afraid of being wrong. We make a lot of investments that even at the time we make them, people tell me that I'm wrong. So I'm not really worried about people being able to pull out the file. I've always felt the one thing that's usually sensitive in a memo is anything you have to say about their team that's usually based on a moment in time assessment that may or may not be complete or accurate and might not stand the test of time. And of all the things that I tend to analyze about teams, the stuff about the people is always the hardest thing to share with people because I think it takes a lot of trust to feel like you can tell somebody, hey, I have concerns about your co founder and the probability that they're going to stick around or whether they're technically sophisticated enough to build the thing that you want to do because the person's already made the decision to work with that person. I've worked at places that had written memos and we've gone back and looked two years later and almost in every case you laugh. Either you laugh because something you thought was definitely going to be true turned out to be totally not true or something you thought would absolutely not happen ended up happening. And then there's the unknown we have the little why did I invest field. In most cases for us it's always the same. I think this person has high managerial potential and they have a good idea and I think they're going to be successful. And in most cases it's actually not that much more of complicated than that. But I admire Andrea for sharing these, these memos and I think oftentimes the only memos that get shared are the winner memos. This is the pitch deck of the company that raised $25 million Series A where this company went public. Here's the really crappy version of the pitch deck they used to raise their seed round. And I feel like in some cases those are more about puffing one's chest up and showing that we had access to this cool deal or we had foresight than it is about sharing for educational purposes. So I don't know. I'm always thinking how can we share more of our thought process behind the investments that we're making without sharing more than is appropriate about a team or a set of people that still finding their way and figuring things out and will probably end the journey as better founders than they began.

It would be really cool to see memos on companies that didn't turn out to be large successes completely unedited because most of the things that end up happening with the company that made it maybe turn out to not be a success. I doubt were in the memo to begin with. It is truly the notes on the back end, the conversations over the phone that you have with the other investor who's looking at the deals. I appreciate Andrea sharing because you really do get to see how thoughtful, intentional she was when she wrote it. When I know that a lot of memos that I've read that have been shared, it's really more of a regurgitation of thoughts and repeated things that everyone would say. It's nothing really unique. The culture on memos is that they're proprietary, but they're essentially all the same if you compare them fund over fund.

I also know a bunch of people who are using AI to write their investment memos now, and I wonder if that's going to increase or decrease the quality and useful Mia, you know me, you know I actually have an opinion, so I shouldn't pretend that I don't have an opinion. Actually, I think it's going to decrease the utility and quality of investment memos because I think a lot of whenever I've written something longer about an investment we're going to make, it really does force me to figure out like, hey, I wrote that sentence. Do I really believe what I just wrote? Or wow, that was easy to write. Or wow, I'm like struggling to write why I'm excited about this team. Is it because I don't have the words? Or is it because I'm not actually that excited about the prospect of working with this team? I do think and worry that the ability of AI to quickly take a bunch of random notes and spin them into a memo kind of robs the writer of the process of having to synthesize all of that. And I think that's a lot of the value is the synthesis of all the many data points you got during diligence and getting to know a team and trying to create one canonical document that summarizes that. I think the effort is part of the journey.

I appreciate her sharing because at least it fosters maybe an ecosystem where we feel okay about being wrong. It's okay part of the job.

Also, I think for founders, there's this weird thing that happens where it's like you spend all this time with someone and they go away and they write something about you and then they make a decision, but you don't actually know what they wrote about you. And in fact, Mia, the same is true as a GP when you're fundraising. Because I've asked a few of our LPs, hey, could I See the memo you wrote? And they're like, like ah, you know, we don't really do that. I'm like, well can you give me a little bit of color on what's in there? And they're like, hey look, you got the money. So absurd.

But that's such a strange concept that you have maybe like a 20 page memo about yourself, your track record, your personal everything. And you'll never see it probably. And for every founder there's probably 20 different versions of it. So it's a really interesting part of our culture. I wish that we were more transparent about it. So I applaud Andrea for kicking off conversation around it. So thank you for sharing that. The next piece, it's a 19 slide deck made by Robert from RV Capital. Titled Mistakes of Omission. It discusses the reality and pain of missed opportunities and investing deals that you saw but didn't act on and later turned out to be massive successes. Any early stage investor knows the feeling of seeing successful companies raised rounds later on after passing. And oftentimes you look back into your notes and have to reason through. Why did we not jump into this one? Robert highlighted the many ways that you can miss an opportunity. Opportunity could be lack of preparation, maybe it wasn't at the price that you wanted, maybe just simply wasn't an area of interest at the time. But more importantly, he talks through why do we not just jump in enthusiastically across venture? And a lot of it is rooted in this feeling that losses hurt more than foregone profits. And so Robert outlines five business profiles with different characteristics. Higher growth rate, lower opex, zero cost inflation and ultimately presents a graph showing over time great businesses always win, certainly more than businesses that were simply at a better deal price. He closed with a good bullet for the truly long term investor. The great businesses properly analyzed beats all other businesses at almost any price. So across our team we see a very high volume of deals. So passing is naturally something that happens more time than not. Shout out to Aaliyah on our team in Q4 alone we had almost 2000 new companies enter our database. 0.5% of those we will see in a closed deal on the precursor side. So we definitely have to get comfortable with not jumping in. But how have you become comfortable or at peace with this? As a pre seed generalist investor I.

Have so many thoughts. That's another deck that I found looking at some of Jay Ripley's other quarterly emails of five articles. And this was from one, I think it was maybe last year. One thing I've always enjoyed About Pre Seed it's counterintuitive. I've often told people it's impossible to have total deal coverage in Pre Seed. There's just simply too many companies. Whereas if you're a growth stage investor, I think you can canvas the majority of companies that fit. If you're like, hey, we're only looking for SaaS businesses between 25 and $50 million in ARR growing 2 to 3x. Like, let's just say that's your filter. I actually think if you're clever and exhaustive, you can actually find almost all of the companies that fit your filter. Doesn't mean you'll have time to ever meet with them all. Whereas in Precede it's an impossible T. So I just assume we will never see everything. And seeing everything is an impossible goal and not something I strive to do. What I've learned though, is the ones that are most painful are fumbling. The ones that you should have done. We met the team at Whatnot when they were first getting started and I don't frankly have a great set of reasons why we didn't invest in whatnot. I knew Grant from his time working with one of our other portfolio company founders. It's funny, I was telling my friend about like, oh well, here's what the company was. He goes, you know, it sounds a lot like ebay in the beginning. If you just submit substitute like Funko for PEZ dispenser. And I can tell you now a million reasons why things happen that I didn't anticipate. I didn't anticipate the growth of live shopping, I didn't anticipate TikTok shops, I didn't anticipate the company growing beyond its initial I can give you a bunch of good reasons why I didn't say yes, but in the end I just should have said yes. And I think there's this tension in Pre Seed investing and you've probably seen me go through this pendulum of there are quarters in years where I invest almost entirely based on my enthusiasm for a team and an idea with less analytical rigor around total addressable market size and business model. It is much more like how excited and enthusiastic am I about this? And I've had other years where I've been much more circumspect around the idea and the market and how much they figured out. And every time I go back and look at like, well, where did my best investments come from? It's actually from enthusiasm. And enthusiasm is hard to explain. And I think this actually Kind of bridges back to the memo conversation. At some point in most firms you have to explain to somebody else else why you're excited about something. And the more people you have to explain something to, I think the harder it is to get to a yes. And if I think about some of our best investments, people were just like, what, what is, what is that thing like, why would you get so excited about that idea? I think a lot about how do I not lose the ability to get excited and enthusiastic about a new person that I don't know very well when statistically I know most things we do probably won't work out. And so I've made every and the stake in that deck. The other lesson I learned early in my venture career, that was very hard to understand. I talked to some of the people who invested in the Facebook round at $500 million and they told me two things. One is good businesses are rarely cheap and the good ones always end up being bigger and more valuable than you could ever envision. And I think a lot about people who went into Facebook At 550, people who went into Stripe at a billion, people who went into OpenAI at a billion. It turns out actually there's actually a non trivial amount of overlap between the people who are in those circles. And I think sometimes one of the hard things to do in ventures to figure out, is this a really special business that I should overpay for and not worry about entry price, or is this like a normal business where the amount of money I'm going to make is a function of my entry price? And so I think, you know, we went through this phase where everyone's like, well, entry price doesn't matter. That was a very 2017-2021 kind of energy because everything was going up and you were getting 20x multiples. So if it was going to be big, you could tell yourself a story like, it doesn't matter, it's going to be so big, who cares? And what I've concluded is there's a relatively small number of outlier businesses that will always feel expensive every time you invest. And two years later it will feel like the world's greatest deal. And so the only question is, is this a special outlier company or is this a normal company? If it's a normal company, you shouldn't overpay and the laws of gravity exist. If it's a special outlier company, it's probably more important to invest and get on board than it is to worry about whether you've got the valuation down to the penny.

I would argue there is some conversation or at least there's a reality in venture that a higher price actually creates more enthusiasm for some investors. So I almost find myself like chicken or egg scenario. I don't want to get caught into that, especially at pre seed where you know, there's nothing behind it. Exactly why we don't write memos beyond the people or the market itself. So how do you say this price is too high or too low when.

It'S that early in sort of like peak SaaS momentum in 2020? Someone I know said, hey, you know, the greatest predictor of future deal momentum is current deal momentum. And I was like, that's either true or that's a very clever rationalization for momentum investing in venture. In either case, it doesn' it might be true. And I think there are times when it's true and there are companies for whom it's always true. So I don't know. I think about this a lot. Which is why we give ourselves permission at precursor to invest in companies at prices and valuations that don't fit our normal parameters. Because sometimes you have special companies and it's worth paying up for those.

Our final topic is a LinkedIn post by Manny Medina titled Sorry to Break an uncomfortable truth to SaaS founders. Manny dives into a harsh reality SaaS founders are facing in 2025 as AI matures and features exp and the revenue margins are decreasing. And that traditional SaaS model of 80% is really a thing of the past. Broken down even more bluntly, in the good old days, SaaS companies kept $80 out of every 100 in revenue. But with the rise of AI driven features, costs are skyrocketing and companies are now keeping closer to $65 per 100. And the cost of running these tokens and models increases as customers use them. And worse, customers are starting to just expect AI as a standard offering, so you don't even get bonus points when you have it, making it harder to pass on the cost to the customer. So Manny believes that the future belongs to the companies who can figure out how to charge for outcomes instead of subscriptions. And he argues that SaaS companies will have to reinvent their pricing strategies and move away from subscription fees and focus on delivering measurable value to their customers. So charging based on outcomes was actually one of the future scenarios we had touched upon in an earlier episode of the Learning Corner. And it's funny, within maybe a month more people have come come around this outcome scenario, at least on LinkedIn or in those social media channels. But I have to be honest, I've seen fewer of that pitched from founders in meetings. Still just kind of curious what you're seeing as well.

I think it's the new thing everybody wants to talk about because I think it gets you away from seats, which I think people want an alternative from that. And it gets you away from usage based pricing. And again, I mean, it used to be in the old days the marginal cost of software was so low because once you sold people the seat, you kind of knew what they were going to consume. But AI kind of broke breaks that because the more you use it, the more it costs. And in most cases you're not paying per token or per API call. Look, I think there's a world in which eventually these costs come down and they're not as punitive and maybe software companies absorb them. Maybe we end up with AI based pricing. I agree with Manny's core tenant that until something changes, it might mean that software is a less good business. If you're providing AI features and your customers expect them as a standard, I think it's increasingly harder to charge for AI as a special feature because your competitors probably found some clever way to bundle it in. I just keep asking myself like, how do you charge for outcomes? And I've started talking to software companies about this. They've said, we're going to charge per outcome. Like, okay, let's talk about what's an outcome. You are a customer service chatbot. You're going to resolve a ticket. So I am going to pay per ticket. Some tickets are easy and some tickets are complicated. And some tickets, what if the AI escalates the ticket and tries to solve it but can't fully solve it? It hands it off to a human, but hands it off to a human teed up to solve. What if I only have 15 tickets this month and you charge me 10 bucks a ticket? Are you going to invoice me for 150 bucks? That's not a great business. And if you've been in the business of selling seats or even usage based pricing, there's a chance that an outcome for company A and outcome for company B, they don't value those things the same way an enterprise software company might place a much higher price on a ticket than a consumer company that's a freemium monetization service might place on a ticket. So I think this paper outcome, it sounds very simple and it sounds very customer aligned, but so did usage based pricing. And most SaaS vendors realized they hated it because of the volatility and it went against the notion that you could predict revenue. So I have a feeling what you're going to end up with is something that feels ironically more like old school software, which is there's going to be some platform fee that you pay just for the privilege of using the software, and that might come bundled with some number of outcomes. And you will pay for outcomes beyond that. Because every time I ask people, well, what's an outcome worth? What does it cost you to resolve a case? And then I go, well, you'd have to resolve a lot of cases on a monthly basis to get anything close to what you were getting from this customer before, which means either your customer is going to pay you a lot less for this software, which is a win for them, or you're going to have to find a new way to bundle outcomes with something else to get back to the ACV that you had before. And if you end up with the same ACV you had before, what was the point? So I haven't found anybody who's told me a really compelling way that you replace the revenue we're accustomed to in SaaS with outcomes. And maybe people are doing that. I just haven't met these folks yet, which I totally know could be possible. But I've long held that most of this AI stuff is price deflationary. And I think outcomes could be very, very deflationary. If you're just paying for resolutions and you're not paying that much per solved incident, you could end up with a lot smaller bill. And I think companies will also realize that there are intermediate outcomes. Like, hey, our AI agent worked on this ticket for 20 minutes and couldn't close it, but got it to a place where when they hand it to a human, I'd argue that's an outcome, but not a resolution. It feels like we are grasping at new business models to deal with the loss of the seat or deal with the loss of like the traditional things that have made SaaS such a great business model.

I agree. I mean, there's a lot there to be figured out in the future for something like customer support. It's going to be done by outcomes, but it's also going to be at high volume. So it's going to be expensive to do. I know there's an argument that when there's a commoditization of different LLMs and more players in, it'll lower the cost. But I think in the short term we're stuck where it's, it's expensive right now. And so we have to figure out how to solve for the here and now.

You can think of a bunch of ways this gets solved. One is small models that are cheaper to run so that the cost of AI is much cheaper. The big hosted models get cheaper over time. And so the bite of giving your customers AI functionality goes down over time. And it's not quite so expensive to do that. But right now, we're not there.

Well, we are all out of time for today. Thank you, Charles, for joining the Learning Corner and thank you everyone for tuning in. Please like and subscribe and we will see you all next week. Thank you. Bye.