Latest / The Learning Corner by Precursor / Episode #85: Venture's Cognitive Dissonance Moment, Cold Pitches Actually Work, Building Your Moat Later

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Episode #85: Venture's Cognitive Dissonance Moment, Cold Pitches Actually Work, Building Your Moat Later · The Learning Corner by Precursor

• 0:00
  I think part of the problem in cold email is a tragedy of the comments.
• 0:04
  Most of it is terrible.
• 0:05
  Even if you're a credible person and you have a good message, you're competing with all of the
• 0:10
  perception that it's junk because a lot of it's junk.
• 0:12
  What I always think is, why is this person reaching out to me cold?
• 0:15
  I wouldn't tell most people to go cold as the first option, but if your choices are not reach
• 0:21
  out to the person at all or write a really good cold email, cold.
• 0:24
  It's the week of July 6.
• 0:26
  Welcome to the Learning Corner, a Precursor Ventures podcast.
• 0:31
  Welcome to the Learning Corner by Precursor.
• 0:33
  I'm Mia Farnam, and I'm joined by our GP and managing partner Charles Hudson, where we will
• 0:38
  be talking through the articles and Goodreads that caught our team's attention over the past
• 0:42
  week.
• 0:42
  Our first piece this week comes from our friend, Samir Khaji, who draws on his twenty
• 0:47
  seven years in private markets to argue that we are living in two truths about AI venture all
• 0:52
  at once.
• 0:52
  On one hand, the froth is unmistakable.
• 0:55
  Companies are repricing every five to six months.
• 0:57
  For sure, as everyone knows, went from roughly 2,500,000,000 to $60,000,000,000 acquisition by
• 1:03
  SpaceX in about eighteen months, and a $100,000,000 plus seed rounds are pricing in
• 1:07
  the option value of being early rather than the business itself.
• 1:10
  The access market has grown noticeably undisciplined too with these multi tiered SPVs
• 1:16
  piling fees on top of unauthorized secondary transfers.
• 1:20
  And on the other hand, every super cycle has produced bigger winners than the last, and this
• 1:25
  one really is no exception.
• 1:26
  SpaceX is roughly $1,700,000,000,000 IPO.
• 1:29
  We've got Anthropix raised close to a trillion dollars itself, and OpenAI at $852,000,000,000
• 1:35
  could together just exceed the total exit value of the last decade in venture.
• 1:40
  Sameer's conclusion is that the percentage of real winners will be far smaller than the
• 1:44
  percentage of companies people believe are winners, which means the split between winners
• 1:48
  and losers this cycle will be more extreme than anything Venture has produced before.
• 1:52
  His practical takeaway for allocators is really blunt.
• 1:54
  Portfolios without at least one top five to 10% asset of this cycle will significantly
• 1:59
  underperform, and average exposure to the AI theme will be worth close to nothing.
• 2:03
  So Charles wanted to pause here first.
• 2:05
  Curious if you feel like the broader sentiment beyond Smir's article is also headed in a
• 2:09
  similar direction to what he was saying.
• 2:10
  I feel like there's been this interesting vibe shift in Venture where for the last years, it's
• 2:16
  been like, just invest in AI.
• 2:18
  It's the only thing that matters.
• 2:19
  It's where all the alpha's gonna be.
• 2:21
  There's gonna be a lot of winners To a market where that's not the case, where everyone's
• 2:25
  like, oh, okay.
• 2:26
  Well, now that, like, the dust has settled a little bit, maybe it's only a really narrow set
• 2:30
  of companies that are gonna make the majority of the money, and the rest of the stuff is
• 2:35
  going to be less valuable.
• 2:36
  In my mind, that's a pretty big narrative shift from people, which is that maybe three or four
• 2:40
  years into the cycle, we have a better sense of the companies that are most likely to be
• 2:44
  valuable, and does that mean that everything else ends up being remnant?
• 2:48
  And I I don't know if that's the answer.
• 2:51
  It goes back to this whole something we've talked about.
• 2:53
  If returns are really concentrated in a handful of companies, if they're not in those
• 2:56
  companies, there's almost no way to catch up on a comparative basis.
• 3:00
  The other question I have for some people, like how repeatable is some of this stuff?
• 3:04
  If you do catch lightning in a bottle, will you catch it again?
• 3:07
  And I think if I were a fund manager who had one of those companies and was in market, would
• 3:11
  absolutely say, yes, we can.
• 3:12
  And let me tell you why we the process we have will help us find the next version of one of
• 3:16
  these.
• 3:17
  I do think if this narrative shift continues, there will be a moment where things change and
• 3:21
  it becomes hard for AI companies to raise.
• 3:23
  People express real skepticism about revenue terminal, and that just hasn't, in my opinion,
• 3:28
  really been happening in the sector.
• 3:29
  So I think this could be a big shift, and in some ways it sort of reminds me of the turn
• 3:35
  that happened in 2021 where everyone was like, well, I guess it's okay to pay a 100 x revenue
• 3:40
  for a really amazing software company, but not just for any company.
• 3:44
  I think when that shifted, it really did change the way people operate and behave.
• 3:48
  And I have to believe that some of this vibe shift has to do with the fact that we're seeing
• 3:52
  some of the most consequential outcomes hit the public market.
• 3:55
  And then you have to look at your portfolio and say, are my companies going to hit the public
• 3:58
  market in that way?
• 4:00
  Because those could quite possibly be real.
• 4:02
  And once it's real, it gives the opportunity for a lot of things to be shown as fake.
• 4:06
  And I think that had not been available to people over the past couple of years because
• 4:10
  everything could truly be quote unquote fake for so long.
• 4:12
  And so I do believe in Samir's statement that you must be in in the top five to 10% of in
• 4:19
  some way, shape, or form because the outcomes are gonna be so large.
• 4:22
  On the flip side, is is there some point about access that still rings through that if it's
• 4:27
  maybe, I don't know, in the top 20%, but it's a hot company, that still gets rewarded from LPs.
• 4:32
  And I maybe these are two different arguments happening, like Yeah.
• 4:35
  Return versus, like, what's helpful for fundraising.
• 4:37
  I think we might be going back to a world where absolute and relative return are different.
• 4:42
  So I think if you're like, hey, my goal is to produce a top decile fund, that's a relative
• 4:47
  comparison.
• 4:48
  And I agree with Samir's argument, is that you probably do need to be in at least one of the
• 4:52
  big names.
• 4:53
  Because ironically, some of the people who are gonna be competing with you will be in multiple
• 4:57
  of the big names.
• 4:58
  So I don't know how you get there if you're not in at least one $1,015,000,000,000 dollar
• 5:02
  outcome.
• 5:02
  It's gonna be really really hard to get there.
• 5:04
  On the flip side, if your goal is to produce great absolute returns by historical venture
• 5:09
  standards, you can probably do that without being in one of these really big companies.
• 5:12
  And you could produce a five, six, seven x fund, which by historical standards would be
• 5:16
  really, really great, and maybe in this moment feels like less impressive.
• 5:20
  The last piece that I wanna talk about is a quote that Smir said, which was after a period
• 5:25
  of disillusionment, we will see another wave of slope of enlightenment, and that period will
• 5:29
  likely see far more expansive growth than we have ever seen from technology.
• 5:34
  How much do you agree with that statement?
• 5:36
  Somebody called me a Luddite a few weeks ago.
• 5:39
  I was like, I didn't know that expressing even a little bit of skepticism about whether the
• 5:43
  first generation of AI companies will be the ones that matter.
• 5:46
  And when I look around, I'm just like, okay, what's really happening?
• 5:50
  We've had this boomlet of this new technology.
• 5:52
  It's clearly powerful.
• 5:53
  It's also clearly not being fully utilized by most companies.
• 5:57
  It just isn't.
• 5:57
  Partially because they don't know how to use it, partially because to really get the gains,
• 6:01
  you'd have to rip out processes and start over.
• 6:03
  And it does remind me a lot of when people discovered digital technology.
• 6:07
  They're like, oh, let's just digitize faxes.
• 6:10
  So now we have, like, the ability to send it into fax.
• 6:13
  Like, why don't just get rid of the fax?
• 6:14
  Well, you have all the stuff that's tied to the fax machine, so we're gonna just digitize
• 6:17
  faxes.
• 6:18
  And I feel like we're in the digitized faxes era, which is why I think everyone's so excited
• 6:22
  about these AI native companies because there's no rework.
• 6:25
  You're not like, oh, we have this accounts payable process or, oh, we have this other
• 6:29
  process that stinks.
• 6:30
  We have to retrofit AI.
• 6:31
  You're like, no.
• 6:32
  We could just decide today that we're just gonna skip the landline era and go right to
• 6:36
  mobile.
• 6:37
  And so I think it's gonna take another generation of people really getting comfortable
• 6:42
  with technology, really understanding what it can do, and really being willing to, like,
• 6:45
  break the way that they work to imagine new ways in order for this to happen.
• 6:49
  I think that's typically what happens when you get a breakthrough technology, is it feels
• 6:54
  incremental for a long time until people are willing to just do something different.
• 6:59
  And we're meeting companies where we're just like, hey, we're gonna build mobile first.
• 7:01
  Everyone's like, no, you gotta have a website.
• 7:03
  Like, well, no, you don't.
• 7:04
  Like, we're building for an audience of people who don't care about desktop web.
• 7:07
  Desktop web is a secondary experience for them.
• 7:09
  And that produced a ton of really interesting breakthroughs, and I could say the same thing
• 7:12
  about almost every phase where there were companies who just said, we're just gonna skip
• 7:15
  the old stuff.
• 7:16
  And we're not I don't think most people are there yet in AI.
• 7:18
  Well, our second piece is from Stanford's Ilyas Drebulev, who ran one of the largest field
• 7:23
  experiments ever conducted on cold outreach, sending over 80,000 fictitious pitch emails to
• 7:30
  more than 28,000 real investors despite VCs predicting the emails would go nowhere, so on a
• 7:37
  true cold outbound.
• 7:38
  Close to 10% of investors responded with interest, and the top performing pitches hit
• 7:43
  response rates of 13 to 17%, meaning roughly one in six VCs replied to a total stranger.
• 7:49
  The piece traces this back to asymmetry and how VCs think about regret.
• 7:54
  Nobody remembers the deal they lost money on, but everybody remembers the unicorn that they
• 7:59
  passed on.
• 8:00
  And the practical findings are very specific here.
• 8:03
  Keep the email short.
• 8:04
  If you're doing cold outbound.
• 8:06
  Lead with the problem rather than the solution.
• 8:08
  Establish credibility right away and match the pitch to an investor's actual thesis rather
• 8:13
  than mass blasting a generic template.
• 8:15
  All things that I think we've probably heard in different forms.
• 8:17
  He also flags a real operational risk that roughly a quarter of the emails in his
• 8:21
  experiment never even landed because spam filters caught them, so infrastructure and
• 8:25
  deliverability matter as much as the pitch itself.
• 8:28
  The data suggests, again, that about 10% of all VC deals start with a cold email holding steady
• 8:34
  across fund sizes and track records.
• 8:36
  Does that number surprise you?
• 8:38
  Because I know early in his piece, he mentions this experiment in a large conference room with
• 8:44
  a bunch of VCs, and they all nodded when he said that cold outbound is just not a great way
• 8:48
  to get in front of investors, but then he has this 10% number.
• 8:51
  I have a lot of thoughts about this.
• 8:52
  I think most VCs, my hunch is they tell people cold email doesn't work because they don't want
• 8:57
  more of it.
• 8:57
  And so I don't know if you saw this in your LinkedIn feed.
• 9:00
  I saw tons of people who had the CEO of Cursor had reached out to them on a LinkedIn DM, and
• 9:06
  they had, like, never replied or left them unread.
• 9:08
  And and I think part of the problem in cold email is, like, a tragedy of the comments.
• 9:13
  Most of it is terrible.
• 9:14
  And so if you're going through the cold channel, even if you're a credible person and
• 9:18
  you have a good message, you're competing with all of the perception that it's junk because a
• 9:23
  lot of it's junk.
• 9:23
  I think AI has accelerated the production of bad cold email.
• 9:27
  What I always think is, why is this person reaching out to me cold?
• 9:30
  So I think students have an unfair asymmetric advantage in cold email because I don't expect
• 9:36
  a student to have a network adventure that would land them in my inbox through a warm
• 9:39
  intro.
• 9:40
  You've been working in Silicon Valley for twenty years and you reach out cold and I was
• 9:43
  like, well, this is strange.
• 9:44
  There's probably somebody who knows you, who knows me, who could help bump you up in the
• 9:48
  queue.
• 9:49
  I think people who are reaching out to me from geographies or places in the country, again,
• 9:53
  where I'm like, well, I don't have network there, so I understand why this person's going
• 9:57
  direct.
• 9:58
  And I read them.
• 9:59
  I replied to a cold email late last night.
• 10:01
  A student wrote me a funny it had a funny subject line, I opened it, and I thought the
• 10:06
  thing was interesting, and I was like, nice job, like, we should chat.
• 10:09
  Truly because I was like, I liked the style of the email.
• 10:11
  But the ones that are hard for me are the ones that are five paragraphs and I get to the
• 10:14
  bottom and it's like, oh, I'm a placement agent for this company and the company is raising a
• 10:18
  $25,000,000 mezzanine round.
• 10:20
  And I'm like, why did I even get this email?
• 10:22
  Why did I even get this email?
• 10:23
  So we try hard to tell people like, this is what's in spec for us.
• 10:25
  This is like what's not in spec for us.
• 10:27
  We talked about this internally as a team.
• 10:29
  I wouldn't tell most people to go cold as the first option, but I think if the op if your
• 10:34
  choices are not reach out to the person at all, or write a really good cold email, Cold.
• 10:38
  And, you know, in our CRM, increasingly, I see companies that reached out cold, and we were
• 10:44
  working our way through them in the queue, and then somebody else flagged it for us.
• 10:47
  And then you have this, like, multi touch attribution.
• 10:49
  Well, was it really cold or was it warm?
• 10:52
  You're like, well, does it really I don't know if it really matters.
• 10:54
  But this whole attribution problem, think, I think this is why VCs would think it's lower.
• 10:59
  Because if you had if someone reached out to you cold and someone else nudged them and made
• 11:03
  you pay attention to it, what's the real source?
• 11:06
  Also, I think VCs would all love to claim that their deal flow is proprietary and relationship
• 11:13
  based.
• 11:13
  And so there's something a little bit like if you said that a large percentage of your deal
• 11:17
  flow that you looked at came in cold, think there's something that they're like, oh, is
• 11:20
  that an interesting enough story to tell people to show them that I have a very ring fenced
• 11:25
  deal approach?
• 11:26
  But a VC, I think, would say, but don't stop sending me stuff if it's good.
• 11:30
  Like, it's cold, I don't want you to do that.
• 11:32
  But I wouldn't go all around saying that I'm answering all of my cold inboxes, emails, when
• 11:36
  in fact there is some good stuff that comes out.
• 11:37
  I also just think a lot of people associate the cold channel with desperate.
• 11:41
  And then, like, sometimes it is, but sometimes it's just disconnected.
• 11:44
  I know some people who are just like, I'm gonna make a zero investment in cold.
• 11:47
  I'm just gonna assume that like it's all worthless, which is a historical VC
• 11:51
  perspective.
• 11:52
  And I think the hardest thing to do is to do some cold.
• 11:55
  I think you'll be like, look, I'm gonna look at everything.
• 11:56
  I'm gonna give it all two seconds and decide if it's interesting.
• 11:59
  Then you're like, alright, well at least I looked at everything.
• 12:01
  I saw it all.
• 12:02
  Or you're like, I'm gonna look at none of it and I'm just gonna accept that, like, if there
• 12:05
  was a gem in there, I'm gonna miss it.
• 12:06
  I think it's hard to feel like, I'm gonna look at some cold and that seems to be hard.
• 12:10
  And I would say the flip side is true as well of VCs reaching out cold to founders.
• 12:14
  There is an art to that as well of what's a good note to send out that's effective and what
• 12:19
  isn't.
• 12:19
  I had a whole conversation with my friend yesterday who works at different fund being
• 12:22
  like, how do you approach cold outbound to founders and what resonates, what doesn't?
• 12:26
  And then also just being realistic that if there's founders with specific signals, there's
• 12:30
  20 other investors who have probably sent them the same notes.
• 12:33
  Like, the same dynamic is happening.
• 12:34
  It just happens on both sides.
• 12:36
  I find it funny that leading with the messages, like, I have money for you for someone who has
• 12:40
  no problem raising money does not solve a problem for that person.
• 12:43
  Yeah.
• 12:43
  That person's probably thinking, where do I find my first founding engineer?
• 12:46
  They have other needs, but capital's not one of them.
• 12:49
  And I'm surprised by the number of people who reach out to people who are clearly gonna have
• 12:53
  no problem raising money, where the first offer is money.
• 12:56
  And I'm like, okay.
• 12:56
  Gotta be something else.
• 12:57
  Gotta be something else.
• 12:58
  If you want if you wanna bubble up and get that person's attention, you have to offer them
• 13:01
  something that solves a real problem they're facing or or a real need they have.
• 13:05
  Well, our last piece is a LinkedIn post from Tomas Tungus tackling the question every
• 13:09
  founder dreads in pitches, which is, what is your moat?
• 13:13
  His framework splits moats into two types, leading moats that exist at founding, so like a
• 13:18
  proprietary dataset or a novel architecture, and then lagging moats that only get earned
• 13:23
  through years of execution, like brand and scale or embedded workflows.
• 13:27
  Infrastructure companies tend to need a leading moat just to get off the ground.
• 13:31
  Snowflake's decision to separate storage from compute bought it the runway to later build
• 13:35
  brand and switching costs, while application layer companies like Salesforce, Slack, and
• 13:39
  Figma, they won without one beating better funded or better built companies purely on
• 13:44
  commercial execution, timing, and speed.
• 13:46
  Dimash maps this onto Hamilton Helmer's seven powers framework, noting that scale economies,
• 13:51
  brand, and switching costs are lagging by construction while counter positioning and
• 13:55
  cornered resources can be leading if a founder actually has them at founding.
• 14:00
  His honest conclusion for most application layer startups is that the moat isn't there
• 14:04
  yet.
• 14:04
  And the correct answer to the moat question is simply we are building one.
• 14:08
  We obviously write a lot of checks into application layer companies that by Tomasz's
• 14:13
  own frameworks have no real moat.
• 14:15
  At founding, when a founder tells you honestly that they are still building the moat, what
• 14:19
  actually convinces you that they're capable of building it versus just aspiring to build one?
• 14:23
  About two years ago, I started going down a similar journey, which was like, if we're gonna
• 14:27
  invest in these application AI companies, there's only a couple of answers.
• 14:30
  One is like, there's no moats, and it's all commodity software, and it will all be a race
• 14:34
  to the bottom.
• 14:35
  I was like, we shouldn't invest if you believe that.
• 14:37
  Second, there are moats.
• 14:38
  We just haven't figured them out yet, and the only way to discover them is through discovery.
• 14:44
  So you make the investment, you go on the journey with the founders.
• 14:46
  Or the third one is the moats already exist.
• 14:50
  We just don't know how to describe or we can't see them yet, but there's no discovery.
• 14:54
  They exist and if you can articulate what they are.
• 14:56
  There are some categories, like for example, you wanna build a foundational model, capital
• 15:00
  and GPU access is a moat.
• 15:02
  You either have enough money to like pay for inference and pay for GPUs and do all things
• 15:06
  you have to do, or you don't.
• 15:07
  You can't, as far as I know, bootstrap one of those.
• 15:09
  So that that's a case where I think, like, I don't even think of it as a moat.
• 15:12
  There's, a minimum requirement of capital to get in and stay in those businesses, and I
• 15:17
  think that's why you've seen this sort of by by model distribution.
• 15:21
  You have a lot of really interesting open source models, and you have a very small number
• 15:25
  of closed source expensive models, and kind of very little in between by just by construct.
• 15:31
  And I think there are, you know, people laughed at me when I said this before, I still think
• 15:34
  it's true.
• 15:35
  There are some commodity markets where simply being the most well known, most well referenced
• 15:39
  vendor is part of the it's not a moat.
• 15:42
  And I think if you say, like, a moat is, like, some weird defensible thing that people can't
• 15:45
  go by, I tend to think, like, well, what's your strategy for creating a winning company, and,
• 15:49
  what do you think your advantage is?
• 15:50
  And if you're just, hey, we're gonna become the company that's synonymous with this category.
• 15:54
  And in a world where all the products feel the same, we think the buyer will choose the best
• 15:59
  branded product, I think that's totally a reasonable strategy.
• 16:02
  I'd argue also a lot of vertical AI companies, if you really look at what they're doing,
• 16:07
  they're doing the classic like bundling strategy.
• 16:09
  Oh, have a bunch of commodity parts, how do you make money?
• 16:12
  I'm like, well, because you're not allowed to swap out this piece for that piece for this
• 16:15
  piece for that piece.
• 16:17
  You have to buy the whole bundle.
• 16:18
  And so if you have to buy the whole bundle, the only people who can compete with you are people
• 16:21
  who can offer the entire bundle.
• 16:23
  And I've seen some of our vertical AI companies, particularly in, like, voice enabled
• 16:26
  vertical AI, start off with products that today would be considered commodity, but now they've
• 16:30
  built four or five other things that are attached to that product.
• 16:33
  So the only way to rip it out is to replace it with the same stack.
• 16:36
  That will change eventually.
• 16:37
  So I think more like when I talk to founders, I'm just like, how are you going to win?
• 16:40
  And sometimes moat is the issue, but it's really like, how are you gonna win?
• 16:43
  And if they don't have a strategy for how they're gonna win, could be we're gonna be
• 16:46
  really good at marketing, we're gonna be really focused on developers, we're gonna be the
• 16:49
  cheapest, we're gonna be the fastest, we have this channel.
• 16:51
  There's gotta be some thoughtfulness around how you win.
• 16:55
  And sometimes they meet companies that have no plan.
• 16:57
  Think we are better than everybody else.
• 16:58
  I'm like, well, I hope you are.
• 17:00
  Yeah.
• 17:00
  And I have some of those in our portfolio too where I'm just like, I still don't know in the
• 17:03
  long term how the customer's gonna decide between two or three different competitors.
• 17:07
  And the moat's going to continue to evolve, especially in this market.
• 17:10
  And I think anyone who tells you otherwise, I think, is trying to probably push their own
• 17:13
  book of business.
• 17:14
  But I've found that, like, if you're pitching authentically and you can tell them the moat
• 17:18
  will come down the road, here's how I'm gonna plow through for the next round with a capital
• 17:22
  I'm raising.
• 17:23
  I find that to be a lot more thoughtful than creating an arbitrary answer about how your
• 17:26
  dataset is proprietary when maybe it's not, and you're doing something that's similar to three
• 17:31
  other competitors.
• 17:31
  Just tell me what your plan is with the capital how you're planning to run and execute on those
• 17:35
  milestones, and we can figure out the moat as it's happening.
• 17:37
  Because you can also have a plan on how to build a moat, and it's not working.
• 17:40
  And then we have to pivot and do something different, which Totally.
• 17:42
  Builds all the times for successful companies in the end.
• 17:44
  Well, are all out of time today.
• 17:46
  Thank you, Charles, for joining in.
• 17:47
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• 17:50
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• 17:54
  Thank you.
• 17:55
  Bye.