Best of LinkedIn: Venture Capital CW 45/ 46

00:00:00: Provided by Thomas Hallgeier and Frennis, based on the most relevant LinkedIn posts about venture capital in CW, forty five and forty six.

00:00:08: For context, Frennis specializes in B to B market research for venture capital teams, providing landscape screenings and startup segmentations with a strong focus on the tech space.

00:00:18: Welcome back to the deep dive.

00:00:20: We've got a curated stack of high impact intelligence across the venture capital landscape from the last couple of weeks.

00:00:26: And the message is pretty clear,

00:00:28: crystal clear.

00:00:28: The party is over and the spreadsheets are

00:00:30: out.

00:00:31: Exactly.

00:00:31: We're seeing this massive shift from, you know, pure deployment strategies to a relentless focus on discipline, on portfolio math, and real operational excellence.

00:00:41: That's the core tension we see across all these sources.

00:00:44: It's no longer enough to find a fast growing company.

00:00:46: VCs now have to prove they can generate liquidity, actual returns in a market where exits are, well, they're deferred.

00:00:52: So our

00:00:52: mission today is to really synthesize the strategic implications of that shift.

00:00:56: Right.

00:00:57: We'll cover four main areas, how LPs are demanding structural change, the new operational models VCs are adopting for an edge, what hard data founders need to bring to the table, and finally, the singular dominating thesis of AI and deep

00:01:12: tech.

00:01:12: Okay, let's jump right in with theme one, LP alignment and the economics of discipline.

00:01:17: It feels like the discipline really starts at the top, right?

00:01:20: With the fund structure itself.

00:01:21: It has

00:01:22: to, and LPs are forcing VCs to confront these structural issues.

00:01:26: Mike Chan brought up a fascinating disconnect.

00:01:28: Oh, this one was great.

00:01:29: Yeah.

00:01:30: LPs who commit capital right before a fund closes get the exact same benefits as the very first investor who wrote a check maybe two years earlier.

00:01:37: Which is so different from startup investing, where early risk gets you better terms.

00:01:41: Exactly.

00:01:41: There's no structural incentive for LPs to commit early in a fundraise, and that just naturally slows down the whole... whole cycle.

00:01:47: And that timing issue is just getting worse.

00:01:50: Maria Mollendorf observed that funds are now taking up to fifteen months to close.

00:01:54: A huge drag on capital deployment.

00:01:57: And more importantly, she highlighted that LPs are obsessing over DPI.

00:02:01: That's distributions to paid-in capital.

00:02:03: Right,

00:02:03: over DPP or total value to paid-in.

00:02:06: And that shift from TVPI to DPI is huge, especially for listeners outside of Pure VC.

00:02:12: TVPI is theoretical.

00:02:14: It's paper returns, unrealized gains.

00:02:16: DPI is cash.

00:02:17: It's

00:02:17: cash in hand, realized returns.

00:02:20: When LPs focus on DPI, it means they want firms that can deliver liquidity now.

00:02:25: Meenlendorf argues that emerging managers have to secure extensive follow-on capital because they just can't rely on quick returns anymore.

00:02:31: That focus on realized returns really validates what Idioressi is arguing.

00:02:36: That smaller funds are destroying bigger ones.

00:02:38: Right.

00:02:38: He laid out the math so simply.

00:02:40: The ten million dollar fund needs one one billion dollar exit to return ten times.

00:02:46: A five hundred million dollar fund needs multiple ten billion plus exits to get that same return.

00:02:51: And that calculus is definitely shifting LP dollars toward emerging and sector specialist managers.

00:02:55: But the efficiency challenge continues when you look at portfolio construction.

00:02:59: Philippe Mayter reminded us of the brutal math of power

00:03:01: law.

00:03:02: the unicorn probability.

00:03:03: It's incredibly low.

00:03:04: We're talking point five percent to two point five percent per seed investment.

00:03:08: So to get even a sixty four percent statistical chance of landing one unicorn, you need to take about fifty shots.

00:03:15: which leads right to the challenge Pablo Prada identified for emerging GPs.

00:03:19: Exactly.

00:03:19: Balancing diversification with ownership.

00:03:22: If a thirty-five million dollar fund tries to take fifty shots, they end up with tiny ownership stakes.

00:03:28: Which forces them to chase these crazy high, like, one hundred fifty X exits just to hit their targets.

00:03:35: So Prada suggests the sweet spot today is probably twenty-five to forty million dollars for an emerging fund.

00:03:41: It balances portfolio scale and ownership.

00:03:44: bottom line is still that the fund strategy has to align with the firm's competitive advantage.

00:03:48: Meaning their access to that rare top one percent founder talent.

00:03:52: The

00:03:52: ones who operate outside that normal probability curve.

00:03:55: It's a game of calculated concentrated risk.

00:03:58: And yet we're still seeing capital flow.

00:04:01: Backed VC closed its one hundred million dollar fund three for European deep tech.

00:04:07: And Cephinova Partners secured a massive six hundred and fifty million euro fund for life sciences.

00:04:14: The capital is there, but it's for conviction plays with highly specialized theses.

00:04:19: Let's shift gears to theme two.

00:04:22: VC firm building and operations.

00:04:24: With capital tighter, VCs have to actually engineer better performance.

00:04:29: The passive model is out.

00:04:30: This is where we see new models designed specifically for an operational edge.

00:04:35: Louis Seegers showcased the, I mean, undeniable outperformance of Venture Studios.

00:04:40: The data is compelling.

00:04:41: It

00:04:41: really is.

00:04:42: Studio-built Ventures hit series A success at seventy-two percent versus forty-two percent for traditional startups.

00:04:48: And their IRRs are nearly double fifty to sixty percent compared to the standard twenty to twenty-five.

00:04:53: It is a staggering gap.

00:04:54: So what's driving that?

00:04:55: Is it just the shared resources or is it the higher equity they take?

00:04:58: It's the depth of the intervention.

00:05:00: Studios provide resources and operational talent from day zero, which just de-risks the whole early stage.

00:05:06: We see a similar idea in the corporate world, too.

00:05:08: Edward Bouvet detailed the total energies CVC pivot.

00:05:11: They

00:05:11: realize that CVC alone, you know, just writing checks.

00:05:14: It's not enough.

00:05:15: Exactly.

00:05:16: For complex corporate innovation, it's insufficient.

00:05:19: They needed a portfolio, a CBC fund, specialized sector vehicles like their climate investment fund, and venture building models to actively create new solutions.

00:05:28: Which suggests the value add is now active execution, not just advice.

00:05:34: Rafael Chaves-Lopes from Switch Ventures talked about this, the classic levers, add value, source better, invest better.

00:05:40: But he says the blind spot is execution intelligence.

00:05:44: That's a key term.

00:05:45: It moves beyond just quarterly reports.

00:05:47: It's about quantifiable dynamic metrics, things like their proprietary measure, execution velocity, that give you real-time signals to improve your follow-on decisions.

00:05:56: So it's moving

00:05:56: from trust and anecdotes to structured data on how FASTA team is actually building.

00:06:01: Precisely.

00:06:01: To supercharge partner judgment.

00:06:03: What's FASTA named to me is while everyone is chasing this data edge in the major hubs, some VCs are finding alpha but looking at non-consensus markets.

00:06:12: You're talking about Mark Nakers at Howdy Partners.

00:06:15: Yeah, investing in rural communities.

00:06:17: And their strategy is brilliant because it targets market reality.

00:06:21: They focus on the twenty to eighty million dollar exit range, which as Najer points out is where eighty percent of all M&A actually happens.

00:06:28: So they prove that small, focused funds with real customer insight can win by just serving markets that the big consensus funds ignore.

00:06:38: And we're seeing niche strategies drive shifts in major sectors, too.

00:06:42: Andy Michikowski noted a big change in health care.

00:06:45: The venture arms of the big health plans, Optum, CVS, SIGNA, are now funding startups directly.

00:06:51: Pulling significant deal flow away from the independent VCs.

00:06:54: Right.

00:06:54: But ultimately, all these different strategies, studios, execution intelligence, niche geography, they all boil down to what Sharon Maroon observed.

00:07:02: Real alpha comes from resilience and collective intelligence.

00:07:05: Not from hype, or as she put it, fun-sized flexing.

00:07:08: It's about demonstrating repeatable, measurable outperformance.

00:07:12: Which sets the stage perfectly for theme three.

00:07:14: Founder guidance in pitching.

00:07:16: If VCs want measurable alpha, founders have to bring operational truth, not just a vision.

00:07:21: The bar is astronomically high, especially at Series A. Chris Totman summarized the VC mental checklist pretty well.

00:07:29: VCs are looking for evidence that you can realistically deliver a hundred X return.

00:07:34: So they're scoring you on market size, traction, PMF, team, risk, everything.

00:07:40: Totman says founders need to be brutally honest about their weak spots before they even walk in the room.

00:07:45: And that honesty is being tested hardest at Series A. Sunjoy called it the series of bottleneck where startups go to die.

00:07:53: Investors are no longer underwriting potential, they're underwriting hard metrics.

00:07:56: We're

00:07:56: talking what, minimum two million ARR?

00:07:59: Minimum two million ARR, one hundred ten percent, plush net retention, and customer acquisition payback under twelve months.

00:08:06: It's a purely operational test.

00:08:07: And if you miss those metrics, the term sheet discussions get brutal.

00:08:11: And this is critical for our M&A and PE audience to understand.

00:08:14: The deal structure now has massive implications.

00:08:17: Alex Turnbull issued a stark warning about participating preferred terms.

00:08:21: This is more than just standard preference.

00:08:23: Turnbull's example was a twenty million dollar raise with two X preference and eight percent dividends.

00:08:29: The result was investors taking one hundred forty million dollars out of a one hundred million dollar exit.

00:08:36: Wait, hold on.

00:08:37: How does that even work if the exit was only one hundred million?

00:08:40: That's the brutal math.

00:08:41: Participating preferred means they get their capital back first twice, in this case, plus dividends, and then they participate with the common shareholders on what's left.

00:08:50: In that specific scenario, the founders walked away with only about five million dollars because the preference stack just wiped out the common stock value.

00:08:57: That is absolutely brutal.

00:08:58: And Itamar Novik added another warning, say no to super pro rata rights.

00:09:03: He calls it a cap table weapon.

00:09:05: Because it lets the existing investor take up so much of the next round that you can't trade up to a better VC like Sequoia or Andreessen Horowitz later on.

00:09:14: Exactly.

00:09:15: The top tier VC can't get a meaningful ownership stake, so they cast.

00:09:18: It blocks the founder.

00:09:20: And here's a strategic shift that affects the pitch deck itself.

00:09:24: Doogoo Doldger noted that AI deck analyzers are now a thing.

00:09:29: Your first audience isn't even human.

00:09:31: This is a huge change.

00:09:33: Founders now have to optimize for AI clarity complete sentences, detailed context over the traditional punchiness you'd design for a human.

00:09:41: If the AI filter can't parse your thesis, a human partner will never even see

00:09:45: it.

00:09:45: And what VCs are measuring is also changing.

00:09:48: Harry Stebbings says up rounds are basically a BS measurement of value.

00:09:51: He says the real metrics should be pure revenue growth.

00:09:54: How fast does a seed company hit ten million ARR?

00:09:57: How fast does a series A company hit twenty five million?

00:10:00: That's the real signal.

00:10:01: But we should remember there are outlier paths.

00:10:04: Look at Guillaume Mubesha's success with Lemlist.

00:10:07: Thirty six million ARR after more than twenty VC rejections.

00:10:11: A powerful counterpoint.

00:10:12: Customer focus over external validation.

00:10:14: It can work.

00:10:15: Right.

00:10:15: It just reinforces Chris Smith's taxonomy.

00:10:18: You can choose to seedstrap.

00:10:20: raise to specific milestones, or go for hyperscaling.

00:10:23: The key is to pick one and execute.

00:10:25: And a quick note for any listeners looking to break into the investment side.

00:10:29: Louis

00:10:29: Drushke and Casey Van Mann and emphasize that VC is relationship driven.

00:10:33: You don't apply cold.

00:10:34: Right.

00:10:34: You build public value, you share deal flow, and you demonstrate your knowledge.

00:10:38: You get invited in.

00:10:39: Okay, let me pivot to our final theme.

00:10:42: AI and deep-tuck momentum.

00:10:44: It's not a trend anymore.

00:10:45: No, it is the dominant market driver.

00:10:47: The numbers are just staggering.

00:10:49: Reuben Dominguez Ibar reported one hundred ninety two point.

00:10:52: seven billion dollars flowed into AI startups in twenty twenty five.

00:10:57: That's over half of all global VC dollars.

00:11:00: And I got theory noted.

00:11:02: over forty percent of recent European rounds were AI related.

00:11:05: That capital concentration is justifying premium pricing too.

00:11:08: Which

00:11:09: is key for potential M&A targets.

00:11:11: Jake Haskins confirmed AI companies are commanding of evaluation premium.

00:11:15: The median series A is fifty eight point eight million over twenty six percent higher than the rest of the market.

00:11:21: M&A is strong.

00:11:23: There's a viable exit path.

00:11:24: What's fascinating is how the funding model itself is bending to fit the tech.

00:11:28: Henry Shea shared insights from investor Yash Patel.

00:11:31: Patel recognized that traditional VC structures are just misaligned with these capital efficient lean AI companies.

00:11:38: Explain

00:11:38: that misalignment.

00:11:39: Why do they need a different structure?

00:11:42: Because the nature of AI development with its rapid validation cycles doesn't need a huge five million dollar seed round.

00:11:50: It might only need five hundred thousand to two million.

00:11:53: So Patel structured a hundred million dollar fund for smaller initial checks and a very low reserve ratio.

00:11:59: So he's focused on the three key motes.

00:12:01: Exactly.

00:12:02: Proprietary data feedback loops, distribution edges and product velocity.

00:12:06: It lets them invest earlier and more efficiently.

00:12:09: It's a highly targeted model.

00:12:10: Yeah.

00:12:11: But Patrick Casey raises a critical, maybe even existential question that our M&A and PE audience should be looking at.

00:12:18: That AI's bottleneck isn't the models.

00:12:20: It's

00:12:20: power infrastructure.

00:12:22: This is the strategic connection point.

00:12:24: Data centers are demanding exponential amounts of energy and water.

00:12:27: The fact that someone like Sam Altman is backing nuclear startups.

00:12:31: Helion, Oklo, Inc.

00:12:32: tell you everything.

00:12:33: The people building the intelligence are also racing to secure the power plants to run it.

00:12:37: So Casey is suggesting the real adjacent opportunities aren't just in the AI models, but in the infrastructure that enables AI to scale.

00:12:45: Water purification, energy optimization, grid efficiency.

00:12:49: That's where the major capital can be deployed outside of pure software.

00:12:53: And we see specialized deep tech being driven by macro forces too.

00:12:57: Matthew Braddott highlighted that European defense tech funding is up seven hundred percent.

00:13:02: And

00:13:02: the focus is shifting to single use defense tech like strike systems.

00:13:06: Geopolitics is forcing capital into hardware and defense.

00:13:10: And in life sciences, F. Matthew back the second and noted capital is concentrating on high impact areas like rare diseases, precision medicine, and next gen biologics.

00:13:20: Rounds for firms like Electra and HeMab.

00:13:22: Right.

00:13:22: The capital is flowing to platforms that can shorten those crucial drug development timelines.

00:13:27: Just to put this in macro context, Patrick Sweeney's data confirms Q-three-twenty-twenty-five as the second highest US VC deal value year ever, largely driven by these AI tailwinds.

00:13:37: But Emily M. Zhang provided the sobering counterpoint.

00:13:41: Valuations are high, but VC returns are lagging, which is probably the best evidence for why discipline and efficiency are now paramount.

00:13:49: So what does this all mean?

00:13:52: The current VC playbook demands structural discipline, whether you're a fund manager focusing on efficient fund size or a founder meeting really high operational metrics.

00:14:01: Specialized focus, particularly on AI and its surrounding deep tech infrastructure, seems to be the only way to achieve alpha in this market.

00:14:09: The power law is alive and well, but the cost of entry has just gone up dramatically.

00:14:13: We saw that the VC landscape is fundamentally shaped by power law and the constant search for massive returns.

00:14:19: So if AI is the engine driving half of global VC funding right now, and that engine is already running into power and water bottlenecks, how much of your current strategy is focused on securing the infrastructure needed for that engine to actually run?

00:14:32: If you enjoyed this episode and new episodes drop every two wins.

00:14:35: Also check out our other editions on private equity, M&A, and strategy and consulting.

00:14:39: Thank you for tuning in for this deep dive into the latest VC insights.

00:14:43: We'll see you next time.