SignalRank AI retweeted
From an upcoming essay
Since 2015, the chance of a 95th percentile Seed startup successfully raising Series A in a given quarter has halved from 50% to ~25%
More: the median Seed startup graduating to Series A used to come from the 10-15% of companies. Now it's the top 2-3%
SignalRank AI retweeted
Diversification isn't just about limiting downside, and concentration isn't just about maximising upside.
It turns out, they're two fairly distinct and important strategies, and startups rely on both.
Previous writing has framed the two as opposing ideas, where one is likely to be strictly better than the other. In fact, they're totally synergetic.
Many startups would never get a chance at proving themselves if it wasn't for the risk appetite of large portfolios that can better tolerate failure.
Others wouldn't survive in the long run without more concentrated firms in their corner to provide support with subsequent financing and governance.
You can even calculate a rough equilibrium with some basic assumptions; how many of each type of firm would be most optimal for the market.
Unfortunately, it's LP expectations (as usual) which create friction in this topic.
Having been repeatedly sold the story of "the few companies that matter", there isn't sufficient appreciate for the product of diversified funds.
Thus, LP preferences have systematically limited the risk appetite of venture capital over time.
Read more: blog.joinodin.com/p/building…
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SignalRank AI retweeted
Calling scaled venture capital "beta" is not an attempt to mock the strategy; a sufficiently large portfolio of startups does begin to look like levered Nasdaq-100.
It's also not an exaggeration to say that large firms are structurally disadvantaged at recognising outliers.
Large firms are systematically data-driven because of institutional memory, process knowledge, and training patterns — and data is inherently backwards-looking.
So, they become better at recognising patterns at the expense of getting worse at recognising novelty.
Smaller firms also have a greater risk appetite, because risk translates into alpha which is the basis for outperformance. Larger firms that serve beta are structurally attracted by marginal gains, and safer incremental opportunities.
The future of scaled VC is to lean into algorithmic allocation and be the fastest-moving partner for growth. It's an elastic and theoretically low-fee product with reasonable returns for large LPs.
The strength of small firms and solo GPs is specifically their ability to recognise potential that the market has overlooked. It's the ideal product for HNWs, FOs, FoFs, states and foundations with strategic goals.
The divide between these two categories of venture investing will be dramatically widened by the impact of AI, as indicated by prior waves of technology.
Related reads:
"Venture Capital as Portfolios of Compound Options", by Sebastian Hillenbrand and Erik Stafford (2025)
papers.ssrn.com/sol3/papers.…
"Micro venture capital", by Mario Daniele Amore, Annamaria Conti and Valerio Pelucco (2023)
papers.ssrn.com/sol3/papers.…
"Bureaucracy as a Lens for Analyzing and Designing Algorithmic Systems" by Juho Pääkkönen, Matti Nelimarkka, Jesse Haapoja and Airi Lampinen (2020)
dl.acm.org/doi/10.1145/33138…
"Data-Driven Investors", by Maxime Bonelli (2025)
lbsresearch.london.edu/id/ep…
"AI and the Nature of the Firm", by Alec Litowitz, Nicholas G. Polson, and Vadim Sokolov (2026)
papers.ssrn.com/sol3/papers.…
Large firms exist because of market friction.
If you want to be well known and easily trusted, size has traditionally been the answer.
The downside of scale is greater coordination friction; larger firms become more inefficient.
This is the basic economic principle laid out by Ronald Coase in his 1937 essay, The Nature of the Firm.
For a long time, it remained unchanged. And then, in the 1990s, the IT revolution kicked it up a gear.
As computers greatly reduced market frictions in some areas, the optimal firm size fell considerably. However, in other categories they reduced internal coordination frictions, enabling much larger firms.
Essentially, it was an economy-wide barbell effect, as firm scale became more concentrated at either end of the distribution, with fewer medium-sized firms.
It is likely that AI takes this even further, pushing firms much further out on the distribution.
This is especially true for venture capital, where the market is already divisible into:
- A scaled service-oriented industry with an elastic product (private market beta / solving puzzles)
- A performance-driven cottage industry with an inelastic product (venture alpha / solving mysteries)
In the former, the scaled firms will get larger in AUM and headcount as AI reduces coordination friction by handling more of the investment process.
In the latter, the ideal size of a firm will fall to one, as AI eliminates external market friction by quantifying reality and making that more accessible.
A simple way to frame this:
The best venture investors are individuals, not firms. Peter Thiel, Cyan Banister, Oren Zeev, Charlie Songhurst, Elad Gil, Chris Sacca... They might also have firms, but their success is their own.
On the other hand, a sovereign wealth fund has no real interest allocating to individuals, because their priority is scale and (lower) risk, not performance. This is the role that firms like Andreessen Horowitz play.
One category of LP wants banging DPI. The other wants name brand firms, stable IRR and a five-star investor relations team.
This is where the market splits in two, and why AI will push participants further apart on the distribution as market frictions are reduced.
SignalRank AI retweeted
This is why earlier entry into future winners matters. Assuming access, filtering earlier stage on a winner/loser probability test and using it to screen entry can produce super results. Entering late and hoping for a public uplift, not so good. This is especially crucial for the new trend of Closed End Funds. Destiny (DXYZ); Powerlaw (PWRL) and Robinhood (RVI) are all trading at or below NAV. The market doesn't believe the upside.
Private markets and public markets value companies differently. Roughly speaking, private markets value scale while public markets value quality.
The outcome is that the more you raise while private, the more disconnected you become from public market investors. This makes late IPOs painful.
Fundamentally, this is why IPOs have remained challenging for a generation of companies that had access to growing pools of venture capital.
It's not terminal. Great businesses survive, but hardly any in the top bracket (>$3B raised, US IPO) thrive.
- Robinhood had the highest 50-day returns, and is the only company in this category with positive alpha versus the Nasdaq-100 today.
- Uber and Airbnb are the next highest, and they are the only two other companies with positive lifetime returns, although they have negative alpha.
SpaceX is an interesting case. Relative to what has been achieved it not raised an insane amount. However, it will still suffer the same dislocation in the short term.
SignalRank AI retweeted
Mercor is in talks for a $20B valuation techcrunch.com/2026/07/09/me…
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SignalRank AI retweeted
Today we’re announcing that @NitraFinance has raised a combined $187 million in financing as we build the AI-native operating system for healthcare practices.
We're also announcing that Dr. Richard Park, founder of CityMD and healthcare legend, will be joining Nitra’s Board.
SignalRank AI retweeted
If someone describes market for VC firms as having a "barbell" distribution, they are laundering the maturity and stability of other asset classes.
VC does not have a barbell distribuition. There aren't independent categories of "boutique specialist" and "large generalist", in competition with each other.
Large firms trade capital for strategic deal flow and information. Small firm survival is based on serving large firm interests, or navigating around them.
It's top-heavy, enmeshed, and uncompetitive.
The alternative is to more formally divide the market into two separate categories, like small-mid cap PE vs large-cap PE. Small exits to large; no entanglement.
This produces a healthier market with better outcomes for all involved — except large firm management fees.
SignalRank AI retweeted
It’s time to build a fleet.
Prototype to production in under 12 months. The @Saronic OTA proves how we’ll build a hybrid manned–unmanned Fleet: open competition, real contracts, real hardware for Sailors and Marines not slides. This is now the standard.
SignalRank AI retweeted
Figma raised $25M in a Series B in 2018. Now worth $25B+ in the public market.
But what about the other Series Bs from 2018?
- 39% never got more valuable. Many in this tier shut down / took down rounds.
- 27% are 1x-2x more valuable
- 12% are 10x more valuable
SignalRank AI retweeted
So... a q&d analysis on whether winners are priced high early on suggests that yes, early markets actually are quite efficient. Winners in aggregate are identified and priced above median all the way back to the A round ... 👇
SignalRank AI retweeted
"What do VCs get wrong about risk management? What does risk management even mean? I thought the whole point was to be risk-on and swing for the fences?" - @johncoogan
Here's what most VCs miss about risk management:
Risk is the product of venture capital, and investors are able to take more risk on individual investments if they are spreading that risk across a properly diversified portfolio. VC is fundamentally a portfolio strategy, not a picking strategy.
"Because fund diversification also affects fund risk, risk-averse fund managers are tempted to invest in companies with higher idiosyncratic (i.e., company-specific) risk when pursuing a strong diversification strategy."
Unsurprisingly, VCs that choose riskier investments as part of a diversified strategy (rather than concentrating on traction or consensus) are more likely to outperform:
"Doing so eventually leads to higher realized fund performance on average, since investments in riskier ventures only make sense if they come with better prospects of high returns."
Thus, better risk management means taking more risk, not less — and managing it properly to deliver outperformance.
In addition to stronger returns, this also drives more capital towards genuinely innovative propositions:
"Our results indicate that especially entrepreneurial ventures in the riskiest industries or at the early stage of development may be the most affected and would gain from a greater diversification of VC funds."
As a contrast, consider ZIRP-era VC, marked by concentrated fund strategy and spreadsheet investing in low-risk SaaS companies — delivering weak performance and technological stagnation.
On the whole, diversification should be the default strategy. Concentration may be earned, over time, as a manager demonstrates an ability to consistently outperform and pick winners:
"We further find that experience can overcome the need for greater diversification, as more experienced VC firms can generate higher returns with lower diversification. The latter allows them to acquire more specialized knowledge in a given industry or stage of development, which will also benefit entrepreneurs."
(source: "Diversification, risk, and returns in venture capital")
We asked @credistick what VCs get wrong about risk management.
"If you properly manage risk, you can take more risky bets."
"According to Dave McClure, a seed stage fund should have 100 startups, because of the small % that some become unicorns or deca-corns."
SignalRank AI retweeted
“Who’s the best Series A investor?”
The answer is usually vibes based driven by recency bias, relationships, domain, or hype…
So I cut the data to see who’s actually in the Hall of Fame 🏆
→ Just 4 investors have led 3 Series A rounds that became $5B+ companies since 2012*
SignalRank AI retweeted
This is "a new era for investing.” Read Larry Fink’s Letter to Investors to learn more. 1blk.co/3PBM7ry
SignalRank AI retweeted
How many startups make it from Series A to Series B?
In a "typical" cohort, about 40% do so in 3 years.
In the hot times, it was more like 50% in 3 years.
For startups that raised A in 2022, it will likely be around 20% in 3 years.
Pop back soon?
SignalRank AI retweeted
We're coming out of a 15 year run of being afraid of our own shadow. It infected and paralyzed our culture, our society, our politics, our economics, and our view of technology. It's over, at least in the US. 🇺🇸
SignalRank AI retweeted
We know that there is a power law for early-stage VC funds, but what does this look like for growth funds? We've just updated our power law analysis to Q2 2024 and have included growth funds for the first time. Here's what we found. /1
SignalRank AI retweeted
Series B valuations.
Medians quite widely distributed, upper ends are super high.































