Latest / The Learning Corner by Precursor / Episode #15: Andrea Funsten, Robert Vinall, Manny Medina

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Episode #15: Andrea Funsten, Robert Vinall, Manny Medina · The Learning Corner by Precursor

• 0:00
  It would be really cool to see memos on companies that didn't turn out to be large
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  successes completely unedited because most of the things that end up happening with the
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  company that made it maybe turn out to not be a success, I doubt we're in the memo to begin
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  with.
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  It's the week of January 13th.
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  Welcome to the Learning Corner, a Precursor Ventures podcast.
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  Welcome to The Learning Corner by Precursor.
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  I'm Mia Farnham and I'm joined by our GP and managing partner, Charles Hudson, where we'll
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  be talking through the Goodreads and articles that caught our team's attention from the past
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  week.
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  Our first article is by Andrea Funston titled, why venture capitalists rarely share investment
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  memos.
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  Andrea dives into the cultural hesitancy among VCs to share investment memos.
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  She argues that the primary reason memos are rarely circulated isn't
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  about confidentiality or
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  competitive disadvantage, isn't about confidentiality or competitive disadvantage.
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  It's really about fear, specifically the fear of being wrong and being scrutinized for it.
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  Andrea points out that this gatekeeping creates a barrier to transparency and learning in the
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  venture ecosystem for investors and founders equally.
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  Sharing memos could foster greater collaboration, allow others to learn from your
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  thought process, and even spark valuable conversations about risk, conviction, and
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  strategy.
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  So Charles, we've had great conversations internally about memo culture.
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  So there is a lot of directions to take this discussion, but I really love how her argument
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  really calls on investors to embrace the discomfort of being wrong as a way to build
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  trust and openness and ecosystems.
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  So, obviously, would love to hear what you thought.
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  Yeah.
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  It's funny.
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  I saw Andrea basically the day before she published this blog post at Blue Bottle Pacific
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  Heights, and we had a chat about it.
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  So I'm glad that she published it.
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  You know, we don't really write memos at Precursor.
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  I've always thought it's both difficult and frankly strange to write long memos about pre
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  seed companies with no product, no traction, no historical financials, really just people and
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  an idea.
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  But I respect and understand that other people's processes are really different, and
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  I've talked to some firms who really feel like, hey, memos help me think.
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  They help me organize my thinking.
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  They clarify, like, the why that we're doing this investment.
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  You know, while we don't do formal memos, we do record a lot of our in real time thinking.
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  And I've always thought what keeps me from publishing our memos.
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  In most cases, I'm actually not afraid of being wrong.
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  We make a lot of investments that even at the time we make them, people tell me that I'm
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  wrong.
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  So I'm not really worried about people being able to pull out the file.
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  I've always felt the one thing that's usually sensitive in a memo is anything you have to say
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  about their team that's usually based on a moment in time assessment that may or may not
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  be complete or accurate and might not stand the test of time.
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  And of all the things that I tend to analyze about teams, the stuff about the people is
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  always the hardest thing to share with people.
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  Because I think it takes a lot of trust to feel like you can tell somebody, hey.
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  I have concerns about your cofounder and the probability that they're gonna stick around or
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  whether they're technically sophisticated enough to build the thing that you wanna do
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  because the person's already made the decision to work with that person.
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  I've worked at places that had written memos and we've gone back and looked 2 years later.
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  And almost in every case, you laugh.
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  Either you laugh because something you thought was definitely going to be true turned out to
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  be totally not true.
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  Or something you thought would absolutely not happen ended up happening.
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  And then there's the unknown.
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  We have the little why did I invest field.
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  In most cases, for us, it's always the same.
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  I think this person has high managerial potential, and they have a good idea, and I
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  think they're gonna be successful.
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  And in most cases, it's actually not that much more complicated than that.
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  But I admire Andrea for sharing these memos.
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  And I think oftentimes, the only memos that get shared are the winner memos.
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  This is the pitch deck of the company that raised them $25,000,000 series a, where this
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  company went public.
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  Here's the really crappy version of the pitch deck they used to raise their seed round.
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  And I feel like in some cases, those are more about puffing one's chest up and showing that
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  we had access to this cool deal or we had foresight than it is about sharing for
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  educational purposes.
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  So I don't know.
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  I'm always thinking how can we share more of our thought process behind the investments that
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  we're making without sharing more that is appropriate about a team or set of people that
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  are still finding their way and figuring things out, and will probably end the journey as
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  better founders than they began.
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  It would be really cool to see memos on companies that didn't turn out to be large
• 4:17
  successes completely unedited because most of the things that end up happening with the
• 4:21
  company that made it maybe turn out to not be a success, I doubt were in the memo to begin
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  with.
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  It is truly the notes on the back end, the conversations over the phone that you have with
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  the other investor who's looking at the deals.
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  I appreciate Andrea sharing because you really do get to see how thoughtful, intentional she
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  was when she wrote it.
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  When I know that a lot of memos that I've read that have been shared, it's really more of a
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  regurgitation of thoughts and repeated things that everyone would say.
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  It's nothing really unique.
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  The culture on memos is that they're proprietary, but they're essentially all the
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  same if you compare them fund over fund.
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  I also know a bunch of people who are using AI to write their investment memos now, and I
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  wonder if that's going to increase or decrease the quality and useful Mia, you know me.
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  You know I actually have an opinion, so so I shouldn't pretend that I don't have an opinion.
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  Actually, I think it's going to decrease the utility and quality of investment memos because
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  I think a lot of whenever I've written something longer about an investment we're
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  going to make, it really does force me to figure out, like, hey.
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  I wrote that sentence.
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  Do I really believe what I just wrote?
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  Or wow.
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  That was easy to write.
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  Or wow.
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  I'm, like, struggling to write why I'm excited about this team.
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  Is it because I don't have the words?
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  Or is it because I'm not actually that excited about the prospect of working with this team?
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  I do think and worry that the ability of I had to quickly take a bunch of random notes and
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  spin them into a memo kinda robs the writer of the process of having to synthesize all of
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  that.
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  And I think that's a lot of the value is the synthesis of all the many data points you got
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  during diligence and getting to know a team and and trying to create one canonical document
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  that summarizes that.
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  I think the effort is part of the journey.
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  I appreciate her sharing because at least it fosters maybe an ecosystem where we feel okay
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  about being wrong.
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  It's okay in part of the job.
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  Also, I think for founders, there's this weird thing that happens where it's like you spend
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  all this time with someone and they go away and they write something about you.
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  And then they make a decision, but you don't actually know what they wrote about you.
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  And in fact, Mia, the same is true as a GP when you're fundraising.
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  Because I've asked a few of our LPs, hey.
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  Could I see the memo?
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  You were and they're like, you know, we don't really do that.
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  I'm like, well, can you give me a little bit of color on what's in there?
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  And they're like, hey.
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  Look.
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  You got the money.
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  So what?
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  Absurd.
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  But that's such a strange concept that you have maybe, like, a 20 page memo about yourself,
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  your track record, your personal everything, and you'll never see it probably.
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  And for every founder, there's probably 20 different versions of it.
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  So it's a really interesting part of our culture.
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  I wish that we were more transparent about it.
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  So I applaud Andrea for kicking off conversation around it.
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  So thank you for sharing that.
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  The next piece, it's a 19 slide deck made by Robert from RB Capital titled Mistakes of
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  Omission.
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  It discusses the reality and pain of missed opportunities in investing.
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  Deals that you saw, but didn't act on and later turned out to be massive successes.
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  Any early stage investor knows the feeling of seeing successful companies raise around later
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  on after passing.
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  And oftentimes you look back into your notes and have to reason through why did we not jump
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  into this one?
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  Robert highlighted the many ways that you can miss an opportunity.
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  Could be lack of preparation.
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  Maybe it wasn't at the price that you wanted.
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  Maybe it just simply wasn't an area of interest at the time, but more importantly, he talks
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  through why do we not just jump in enthusiastically across venture, and a lot of
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  it is rooted in this feeling that losses hurt more than foregone profits.
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  And so Robert outlines 5 business profiles with different characteristics, higher growth rate,
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  lower OPEX, 0 cost inflation, and ultimately presents a graph showing over time, great
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  businesses always win.
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  Certainly more than businesses that were simply at a better deal price.
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  He closed with a good bullet for the truly long term investor.
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  The great businesses properly analyzed, beats all other businesses at almost any price.
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  So across our team, we see a very high volume of deals.
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  So passing is naturally something that happens more time than not.
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  Shout out to Aliyah on our team.
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  In q 4 alone, we had almost 2,000 new companies enter our database.
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  And 0.5 percent of those, we will see in a closed deal on the precursor side.
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  So we definitely have to get comfortable with not jumping in, but how have you become
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  comfortable or at peace with this as a pre seed generalist investor?
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  I have so many thoughts.
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  That's another deck that I found looking at some of Jay Ripley's other quarterly emails of
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  5 articles, and this was from 1, I think it was maybe last year.
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  One thing I've always enjoyed about pre seed, it's counterintuitive.
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  I've often told people it's impossible to have total deal coverage in precede.
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  There's just simply too many companies.
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  Whereas if you're a growth stage investor, I think you can canvas the majority of companies
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  that fit if you're like, hey.
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  We're only looking for SaaS businesses between $25,050,000,000 in ARR growing 2 to 3 x.
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  Like, let's just say that's your filter.
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  I actually think if you're clever and exhaustive, you can actually find almost all of
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  the companies that fit your filter.
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  Doesn't mean you'll have time to ever meet with them all.
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  Whereas in pre seed, it's an impossible task, so I just assume we will never see everything,
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  and seeing everything as an impossible goal and not something I strive to do.
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  What I've learned though is the ones that are most painful are fumbling the ones that you
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  should have done.
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  We met the team at Whatnot when they were first getting started.
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  And I don't frankly have a great set of reasons why we didn't invest in Whatnot.
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  I knew Grant from his time working with one of our other portfolio company founders.
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  It's funny, I was telling my friend about, like, oh, well, here's what the company was.
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  He goes, you know, it sounds a lot like eBay in the beginning if you just substitute like funco
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  for Pez dispenser.
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  And I could tell you now a million reasons why.
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  Things happened that I didn't anticipate.
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  I didn't anticipate the growth of live shopping.
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  I didn't anticipate TikTok shops.
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  I didn't anticipate the company growing beyond its initial.
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  I can give you a bunch of good reasons why I didn't say yes.
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  But in the end, I just should have said yes.
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  And I think there's this tension in precede investing, and you've probably seen me go
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  through this pendulum of there are quarters years where I invest almost entirely based on
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  my enthusiasm for a team and an idea with less analytical rigor around total addressable
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  market size and business model.
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  It is much more like how excited and enthusiastic am I about this.
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  And I've had other years where I've been much more circumspect around the idea and the market
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  and how much they figured out.
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  And every time I go back and look at, like, well, where did my best investments come from?
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  It's actually from enthusiasm.
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  And enthusiasm is hard to explain.
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  And I think this actually kind of bridges back to the memo conversation.
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  At some point, in most firms, you have to explain to somebody else why you're excited
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  about something.
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  And the more people you have to explain something to, I think the harder it is to get
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  to a yes.
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  And if I think about some of our best investments, people were just like, what?
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  What is what is that thing?
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  Like, why would you get so excited about that idea?
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  I think a lot about how do I not lose the ability to get excited and enthusiastic about a
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  new person that I don't know very well.
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  When statistically, I know most things we do probably won't work out.
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  And so I've made every mistake in that deck.
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  The other lesson I learned early in my venture career that was very hard to understand, I
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  talked to some of the people who invested in the Facebook round at $500,000,000, and they
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  told me 2 things.
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  1 is good businesses are rarely cheap, and the good ones always end up being bigger and more
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  valuable than you could ever envision.
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  And I think a lot about people who went into Facebook at 5:50, people who went into Stripe
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  at a 1,000,000,000, people who went into OpenAI at a 1,000,000,000.
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  It turns out actually there's actually a non trivial amount of overlap between the people
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  who are in those circles.
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  And I think sometimes one of the hardest things to do in venture is to figure out, is this a
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  really special business that I should overpay for and not worry about entry price?
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  Or is this, like, a normal business where the amount of money I'm going to make is a function
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  of my entry price?
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  And so I think, you know, we went through this phase where everyone's like, well, entry price
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  doesn't matter.
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  That was a very 2017 to 2021 kinda energy.
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  Because everything was going up and you were getting 20 x multiples.
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  So if it was going to be big, you could tell yourself a story like it doesn't matter.
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  It's gonna be so big.
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  Who cares?
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  And what I've concluded is there's a relatively small number of outlier businesses that will
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  always feel expensive every time you invest.
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  And 2 years later, it will feel like the world's greatest deal.
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  And so the only question is, is this a special outlier company, or is this a normal company?
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  If it's a normal company, you shouldn't overpay and the laws of gravity exist.
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  If it's a special outlier company, it's probably more important to invest and get on
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  board than it is to worry about whether you've got the valuation down to the penny.
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  I would argue there is some conversation, or at least there's a reality in venture that a
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  higher price actually creates more enthusiasm for some investors.
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  So I almost find myself like chicken or egg scenario.
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  I don't wanna get caught into that, especially at pre seed where, you know, there's nothing
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  behind it exactly why we don't write memos beyond the people or the market itself.
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  So how do you say this price is too high or too low when it's that early?
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  In sort of, like, peak SaaS momentum in 2020, someone I know said, hey.
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  You know, the greatest predictor of future deal momentum is current deal momentum.
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  And I was like, that's either true or that's a very clever rationalization for momentum
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  investing in venture.
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  In either case, it doesn't matter.
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  It might be true.
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  And I think there are times when it's true, and there are companies for whom it's always true.
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  So I don't know.
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  I think about this a lot, which is why we give ourselves permission at Precursor to invest in
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  companies at prices and valuations that don't fit our normal parameters because sometimes you
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  have special companies, and it's worth paying up for those.
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  Our final topic is a LinkedIn post by Manny Medina titled, sorry to break an uncomfortable
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  truth to SaaS founders.
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  Manny dives into a harsh reality SaaS founders are facing in 2025.
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  As AI matures and features expand, the revenue margins are decreasing.
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  And that traditional SaaS model of 80% is really a thing of the past, broken down even
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  more bluntly.
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  In the good old days, SaaS companies kept $80 out of every 100 in revenue.
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  But with the rise of AI driven features, costs are skyrocketing and companies are now keeping
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  closer to $65 per 100, and the cost of running these tokens and models increases as customers
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  use them.
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  And worse, customers are starting to just expect AI as a standard offering.
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  So you don't even get bonus points when you have it, making it harder to pass on the cost
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  to the customer.
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  So Manny believes that the future belongs to the companies who can figure out how to charge
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  for outcomes instead of subscriptions.
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  And he argues that SaaS companies will have to reinvent their pricing strategies and move away
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  from subscription fees and focus on delivering measurable value to their customers.
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  So charging based on outcomes was actually one of the future scenarios we had touched upon in
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  an earlier episode of the learning corner.
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  And it's funny, within maybe a month, more people have come around this outcome scenario
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  at least on LinkedIn or in those social media channels.
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  But I have to be honest, I've seen viewer of that pitched from founders in meetings still.
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  Just kinda curious what you're seeing as well.
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  I think it's the new thing everybody wants to talk about.
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  Because I think it gets you away from seats, which I think people want an alternative from
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  that.
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  And it gets you away from usage based pricing.
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  And again, I mean, it used to be in the old days, the marginal cost of software was so low.
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  Software was so low because once you sold people the seat, you kinda knew what they were
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  gonna consume.
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  But AI kinda breaks that because the more you use it, the more it costs.
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  And in most cases, you're not paying per token or per API call.
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  Look, I think there's a world in which eventually these costs come down and they're
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  not as punitive, and maybe software companies absorb them.
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  Maybe we end up with AI based pricing.
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  I agree with Manny's core tenant that until something changes, it might mean that software
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  is a less good business if you're providing AI features and your customers expect them as a
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  standard.
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  I think it's increasingly harder to charge for AI as a special feature because your
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  competitors probably found some clever way to bundle it in.
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  I just keep asking myself, like, how do you charge for outcomes?
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  And I've started talking to software companies about this.
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  They've said, we're gonna charge for an outcome.
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  Like, okay.
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  Let's talk about what's an outcome.
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  You're a customer service chatbot.
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  You're gonna resolve a ticket.
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  So I am gonna pay per ticket.
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  Some tickets are easy and some tickets are complicated.
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  And some tickets, what if the AI escalates the ticket and tries to solve it but can't fully
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  solve it and hands it off to a human, but hands it off to a human teed up to solve.
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  What if I only have 15 tickets this month and you charge me $10 a ticket?
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  Are you gonna invoice me for a $150?
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  That's not a great business.
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  And if you've been in the business of selling seats or even usage based pricing, there's a
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  chance that an outcome for company a and outcome for company b, they don't value those
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  things the same way.
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  An enterprise software company might place a much higher price on a ticket than a consumer
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  company that's a premium monetization service might place on a ticket.
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  So I think this pay per outcome, it sounds very simple, and it sounds very customer aligned.
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  But so did usage based pricing, and most SaaS vendors realized they hated it because of the
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  volatility.
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  And it went against the notion that you could predict revenue.
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  So I have a feeling what you're gonna end up with is something that feels ironically more
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  like old school software, which is there's gonna be some platform fee that you pay just
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  for the privilege of using the software.
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  And that might come bundled with some number of outcomes, and you will pay for outcomes beyond
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  that.
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  Because every time I ask people, well, what's that outcome worth?
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  What does it cost you to resolve a case?
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  And then I go, well, you'd have to resolve a lot of cases on a monthly basis to get anything
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  close to what you were getting from this customer before, which means either your
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  customer's gonna pay you a lot less for this software, which is a win for them, or you're
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  gonna have to find a new way to bundle outcomes with something else to get back to the ACV that
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  you had before.
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  And if you end up with the same ACV you had before, what was the point?
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  So I haven't found anybody who's told me a really compelling way that you replace the
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  revenue we're accustomed to in SaaS with outcomes.
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  And maybe people are doing that.
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  I just haven't met these folks yet which I totally know could be possible but I've long
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  held it.
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  Most of this AI stuff is price deflationary and I think outcomes could be very very
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  deflationary.
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  If you're just paying for resolutions and you're not paying that much per resolved
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  incident, you could end up with a lot smaller bill.
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  And I think companies will also realize that there are intermediate outcomes like, hey, our
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  AI agent worked on this ticket for 20 minutes and couldn't close it, but got it to a place
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  where when it handed to a human.
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  I'd argue that's an outcome, but not a resolution.
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  It feels like we are grasping at new business models to deal with the loss of the seat or
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  deal with the loss of, like, the traditional things that have made SaaS such a great
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  business model.
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  I agree.
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  I mean, there's a lot there to be figured out in the future.
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  For something like customer support, it's gonna be done by outcomes, but it's also gonna be at
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  high volume.
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  So it's going to be expensive to do.
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  I know there's an argument that when there's a commoditization of different LLMs and more
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  players in, it'll lower the cost.
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  But I think in the short term, we're stuck where it's it's expensive right now, and so we
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  have to figure out how to solve for the here and now.
• 18:51
  You can think of a bunch of ways this gets solved.
• 18:53
  One is small models that are cheaper to run so that the cost of AI is much cheaper.
• 18:57
  The big hosted models get cheaper over time, and so the bite of giving your customers AI
• 19:02
  functionality goes down over time, and it's not quite so expensive to do that.
• 19:07
  But right now, we're not there.
• 19:08
  Well, we are all out of time for today.
• 19:10
  Thank you, Charles, for joining the Learning Corner.
• 19:12
  And thank you everyone for tuning in.
• 19:14
  Please like and subscribe.
• 19:15
  And we will see you all next week.
• 19:17
  Thank you.
• 19:18
  Bye.