I didn't go to an Ivy League school, so breaking into VC felt impossible.

Instead, I found my way through the side door. I started at Lyft during the pink mustache days, co-founded their employee syndicate, and helped 300+ employees deploy $30M into startups.

That led me to help other tech companies (Airbnb, Square, Pinterest, Stripe) build their own alumni investing communities.

Eventually, I realized my real passion was making angel investing accessible to people who aren't in the traditional VC club.

That's how Angel Squad was born.

Today, I run Angel Squad at Hustle Fund. It's a community of 2,000+ professionals learning how to angel invest. TechCrunch called us the "YC of Angel Investing."

We've deployed $30M+ together, and our members include everyone from Google PMs to airline pilots to physical therapists. Basically, anyone who wants to learn how to write $1k checks into startups.

I also write Small Bets, a weekly newsletter where I share lessons on startups and angel investing - the wins, the losses, and everything in between.

If you're curious about angel investing or just want to learn more about the startup world, let's connect.

Brian Nichols

Uber's first investors got in at a $4 million valuation. Anthropic's first investors got in at $623 million.

Uber IPO'd at $82B, Anthropic is raising at $350B.

That massive difference in entry price is why Uber's seed investors made 5,000x returns at IPO and Anthropic's first investors are currently at 100x.

Both companies are generational.  

But the math on what that means for early investors couldn't be more different.
Uber's seed round in 2010 raised $1.25 million. First Round Capital put in $510,000 and turned it into $2.5 billion at IPO. Two angels invested $5,000 and walked away with nearly $25 million each.

Anthropic is now raising at $350 billion, a 500x+ valuation increase from their Series A four years ago. After dilution from $30B+ in funding rounds, early shareholders are looking at roughly 100x. Still exceptional. But not 5,000x.

The difference comes down to perceived risk at entry.

Uber in 2010 was two guys with a black car service in San Francisco. Mark Cuban passed. Gary Vaynerchuk passed twice. The valuation reflected that uncertainty.

Anthropic came out of the gate at $623 million because Dario Amodei was already a known quantity. Former VP of Research at OpenAI and early AI team at Google. He brought with him a crazy impressive team from OpenAI. The market priced in the potential before the company had a product.

Entry price is everything in this game. By the time everyone agrees something is valuable, most of the value has already been captured.

Founder of Angel Squad | I write about startups, investing, and hard-earned lessons | Small Bets newsletter

If you invested $5k in Webflow when Hustle Fund did, do you know how much it'd be worth today?

$2.3M.

Getting access to a deal like that and learning why we said yes is something you don't learn from blog posts or Twitter threads.

You learn it by:
👉 Getting the reps in evaluating actual deals in a fund's pipeline
👉 Discussing products and markets with other investors
👉 Sitting in on live pitch meetings with tier 1 founders and investors

VC is an opaque industry, but there's a shift happening. Leaders in this space are putting in serious groundwork to democratize access.

- Peter Walker consistently shares data and insights that have proved crucial for emerging fund managers

- Nicole DeTommaso produces incredible resources on breaking into VC

- And Haley Bryant went from operator to Partner at Hustle Fund - proving there's a legit path there

You'll work directly with our GPs - Elizabeth Yin, Eric Bahn, and Shiyan K. - learning how they evaluate startups by digging into real companies from our pipeline. These are Stanford classmates who've been investing together for years.

The outcomes from past venture fellows speak for themselves. We've helped MBA students go full-time into VC, operators build track records with $1k-$5k angel checks, and aspiring fund managers take the first step toward raising from LPs.

----

Apply: https://lnkd.in/gPxkC5iM

–--------

Shoutout to some of the Squad Members that have graduated from previous cohorts: Aaisha Bhuiyan |  Alfred Y. Bentley III, PhD | Alice Qinhua Zhou | Ansel Chew |  Bart Hofkin | Bima Bimanywaruhanga | Dee Zheng | Dimple Kochikar | Francisco Guerrero | Gana N. | Jonathan Kennell |  Kartik Agarwal | Leon Jon | Nalina Murthy | Parul Benien | Peter L. | Phill Sohn | Raechele Smalls | Rishi Solanki | Ryan Stoner | Sal Arif, MSc/MMAI | Sandy Naidu | Shankarsun Sahu | Tony Cueva Bravo |

+ Many more!

In 2017, my boss at Zoox told me something during a performance review that stuck with me.

"The thing I like most about managing you is that if you say you're going to do something, it always gets done."

I didn't think much of it at the time.

I just assumed that's how things worked. You commit to something, you do it. 

Then I got deeper into my career and realized...not everyone is great at it.

Following through on what you say you'll do - and closing the loop when you do - is a genuine differentiator.

If you're early in your career, this might be the simplest edge you can build.

I've been teaching this to my kids for a while now. They've shortened it to "daddy, you say it, you do it."

(And yes - they've found creative ways to use that against me 😅)

Early investors in Brex just saw 700x+ returns.

Capital One acquired the company yesterday for $5.15 billion. Headlines focused on the "haircut" from Brex's $12.3B peak valuation in 2022.

But for pre-seed investors who backed two 22-year-old Stanford dropouts in 2017, this is a monster outcome.

YC invested at the pre-seed. Ribbit led the Series A soon after. The company was worth basically nothing at that point - two Brazilian founders pivoting from a VR idea three weeks into the accelerator program.

This is the power law in action.

The catch is that you had to believe in two 22-year-olds with no US credit history pitching corporate cards for startups. Most people wouldn't have (and I'm sure most people that they pitched didn't).

That's the trade-off with early-stage investing. The upside is astronomical. But you're betting on founders before the data makes it obvious.

Just like my Uber v. Anthropic post earlier this week, by the time everyone agrees something is valuable, most of the returns have already been captured.

You don't need a fund to build a track record in venture. You don't even need to write angel checks.

At Angel Squad, we've syndicated $5.5M+ into almost 30 companies over the past four years from deals sourced by an Angel Squad member.

We call them Scouts.

Here's how it works: Squad Members refer deals they've found through their networks. If Hustle Fund invests or the deal gets syndicated, the member becomes a Scout and earns upside on that deal.

No fund or personal capital required. Just know good founders.

Some of the companies our 20+ Scouts have surfaced this year:

→ A biotech automation platform - essentially "Zapier for lab experiments" - letting biologists connect robotics modules to automate R&D end-to-end

→ A home energy company founded by a former Tesla Powerwall and SPAN engineer, making plug-and-play batteries at a fraction of traditional system costs

→ The first agentic AI marketing platform — their Autopilot product is on a crazy growth trajectory

→ A voice AI company decoding human behavior to build compatible work relationships

→ An ecommerce platform solving the Shopify flexibility problem for mid-market brands

Through these deals, we've invested alongside top funds like Floodgate, General Catalyst, Tiger Global, Lowercarbon, and Initialized Capital.

Many of these Scouts have since started their own funds, landed VC jobs, or now work closely with Hustle Fund.

The path into venture isn't as narrow as people think if you put in the work as a Scout.

Sebastiano Armeli has led engineering teams at Spotify, Snap, PayPal, Pinterest, Upwork, and now Meta. Fifteen years of building products used by billions of people.

He joined Angel Squad two years ago to learn how to invest in startups.

That still kind of blows my mind.

You'd think someone with his resume would just... figure it out (or at least assume that they can!). 

He's shipped products at massive scale and watched companies grow from the inside. 

But evaluating a pre-seed deck is a completely different skill than leading an engineering org. Knowing what makes a great product doesn't automatically tell you what makes a great investment.

Sebastiano said his favorite part was the community - "genuine and professional individuals from various domains." 

Or in other words, ambitious, decent humans with no a-holes allowed.

We've got airline pilots in Angel Squad. Physical therapists. Allergists. Lawyers. Directors of Engineering at trillion-dollar companies. 

They all sit in the same sessions and learn from each other's blind spots.

The engineer picks up how a healthcare professional thinks about medtech. The lawyer flags term sheet issues nobody else caught. 

Sebastiano's been at this for 2+ years now. He's made investments, gained exposure to early-stage startups, and built relationships with angels in his area through our quarterly local events.

Not bad for someone who already had fifteen years of tech experience and still decided he had more to learn.

Sara Blakely kept her Spanx idea secret from friends and family for a full year.

Her reasoning: "Out of love, they might prevent me from taking a risk."

Before Spanx, she sold fax machines door-to-door for 7 years. Not a stepping stone gig. Seven years of actual rejection at people's front doors. 

If I had been lucky enough to meet her after that and she told me that story, it would've been impossible for me not to invest.

She started the company with $5,000 in savings.  

Her early tactics were scrappy in a way that doesn't get talked about enough. She paid friends to buy Spanx off shelves to create movement. 

She'd go into department stores and physically move her product closer to cash registers. 

She got a meeting with Neiman Marcus by cold-calling the buyer, flying to Dallas, and doing a live before/after demo in the bathroom.

Her pure grit and determination helped her become the youngest self-made female billionaire in America.

I think about this story a lot when founders tell me they need to raise a big Seed round before they start building.

🤦🏻‍♂️...please be more like Sara.

The best way to predict Nvidia's next move isn't their earnings calls. It's their investment portfolio.

They backed OpenAI, Anthropic, and Cursor before anyone was paying attention. Now they're writing checks into companies most people haven't heard of yet.

Ayar Labs — $155M round (Dec 2024) They're replacing copper wires in data centers with light. Literally. Their optical interconnects move data faster with less power. AMD, Intel, and Nvidia all participated in the same round. When three competitors agree on something, pay attention.

Sandbox AQ — $150M round (April 2024) Spun out of Google. Building "large quantitative models" for complex numerical analysis. Now valued at $5.75B. The bet here is that not everything in AI is about language models.

Hippocratic AI — $141M Series B (Jan 2024) Healthcare LLMs for non-diagnostic tasks like pre-op procedures and patient monitoring. Valued at $1.64B, now at $3.5B after another raise.

Weka — $140M round (May 2024) AI-native data management. Training models is only as good as how fast you can feed them data.

Runway — $308M round (April 2024) Generative AI for video and media production. Valued at $3.55B. Nvidia's been in since 2023.

Bright Machines — $126M Series C (June 2024) Smart robotics and AI-driven manufacturing software. Physical world automation.

Kore AI — $150M round (Dec 2023) Enterprise AI chatbots before ChatGPT made it trendy.

Reka AI — $110M round (July 2024) Multimodal AI research lab now valued at $1B+.

But the most interesting one is Enfabrica.

Nvidia participated in their $125M Series B back in September 2023. The company builds networking chips that can unify 100,000+ GPUs into a single computing system.

Then in September 2025, Nvidia spent $900M to acquihire the CEO and license the technology.

If you want to understand where Nvidia thinks AI is going, don't just watch their chip announcements. 

Watch where they're putting money 2+ years before anyone else notices.

A trillion dollars in paper gains. Ten AI startups. And unless you're investing in private markets, you couldn't touch any of it.

Look at this chart.

OpenAI went from ~$30B to $500B in two years. xAI didn't exist until mid-2023 now it's worth $230B. Anthropic barely registered in early '23. Today it's at $350B.

Meanwhile, retail investors are stuck choosing from ~700 AI-related public stocks. 

Most of the new additions are AI companies with no intention of going public anytime soon.

The math is stark:
- AI captured 50% of all global VC funding in 2025

- $202 billion poured into private AI companies

- Robinhood is now building funds specifically to give retail access to private AI

That last one is telling. Even the platforms built for everyday investors are finally admitting: the game has moved.

The explosive growth phase is primarily happening before IPO. By the time these companies go public (if they ever do), most of the upside has already been captured.

This isn't a bug in the system. It's the system working exactly as designed - just not for most people.

(but sure, go bet on Polymarket or buy lotto tickets - just don't touch private markets. Way too risky!)

Head of Insights at Equidam, the Startup Valuation platform | Crunchbase contributor

Supporting entrepreneurs around the world with developing innovative products and raising capital.

Dan G.

According to a survey of 885 VCs (at 681 firms) on the most important component of generating returns:

- 49% said deal selection
- 27% said value-add
- 23% said deal flow 

While these answers do broadly reflect the common perception of venture capital, they don't accurately reflect the data. 

In reality, selection is messy and inconsistent and value-add is questionable, while deal flow is fundamental and often underprioritised — despite research emphasising the importance. 

As a matter of simple maths, VCs can achieve better investment outcomes with a relatively minor improvement to their pool of opportunities versus a much greater improvement in their picking skill. 

This is why firms with truly differentiated origination (examples of Also Capital, 1517 Fund, Compound) continue to provide positive alpha in an increasingly enmeshed and beta-driven environment. 

More on this in my latest article for The Odin Times, linked below.

(Survey data from "How Do Venture Capitalists Make Decisions?", by Paul Gompers, Will Gornall, Steven Kaplan, Ilya Strebulaev.)

Research Lead @ Odin | Writer on Private Markets

The chart below (courtesy of Sapphire Ventures simulation data) is a good illustration of why LPs may be wary of reserves being “bolted-on” to your venture capital fund strategy.

Reserves often end up reducing net fund multiples but only increase management fees (from larger funds) and carry income (tied to total profits, not efficiency per dollar), potentially misaligning incentives in the relationship.

If you decide to include reserves in your portfolio design, you must clearly articulate:

1) How you monitor portfolio company progress to make effective follow-on decisions (choosing the right opportunities). 

2) Your assumed math of the eventual outcomes, with the ultimate influence on fund performance (how you drive performance up).

3) How considerations like signalling risk, sunk-cost bias, and portfolio support are built into your thinking. 

i.e. You must be clear on both the strategic/qualitative logic of the reserves strategy, plus the target quantitative outcome, and the systemic factors. 

Full article on venture capital reserve logic in The Odin Times, linked below.

Answering Trae Stephens' question: how can every firm have "top decile" performance?

You can't raise your next fund without showing top decile performance, so every manager has top decile performance — but only when they raise. 

Other than the forms of benchmark jiu-jitsu listed by Endowment Eddie on X (linked below), GPs have also been observed inflating portfolio company valuations to boost performance.

"Using novel round-level pricing data, we show that VC investment pricing decisions are distorted by fundraising incentives. Before raising another fund, VCs boost interim performance by strategically investing in follow-on rounds of current portfolio firms at abnormally high valuations"

(source: "Does Fundraising Pressure Incentivize Strategic Venture Capital Deal Pricing?")

Why would other VCs in the syndicate agree to irrationally high prices on these rounds? Because they'll want to do the same thing at some point. 

"Our analysis also suggests that reciprocity is a reason for why non-fundraising syndicate members would bear the cost of investing in strategically overpriced rounds and that LP experience and relationship can restrain strategic overpricing incentives of GPs"

Of course, this means that portfolio performance is likely to fall shortly after fundraising as these companies struggle in subsequent rounds. Research supports this conclusion. 

"The current fund’s performance rank is at its peak when the GP is concluding fundraising for a follow-on fund. Finally, we find that NAV markdowns are both larger and more frequent in the post-fundraising periods."

(source: "Interim Fund Performance and Fundraising in Private Equity")

This results in what the Ewing Marion Kauffman Foundation called the "n-curve" of venture capital, where (instead of the expected j-curve) fund performance is inflated up until a subsequent fund has been raised. 

"Quarterly data over the past seven years from Fenwick & West confirm what our “n-curve” results suggest: GPs write up portfolio company valuations considerably and frequently  early  in  their  fund’s  life,  which  results  in  early  positive  returns instead of a negative IRR dip."

(source: "We Have Met the Enemy And He is Us")

In addition to generally slipping returns, this helps to explain why VC has such weak persistence, where interim metrics on a previous fund are a weak indicator of future performance. These metrics only become somewhat predictive after most of a decade.

"The performance of a general partner’s previous private investment funds can predict future fund performance to a degree, but that’s only with at least eight years of hindsight."

(source: "Fund performance data unhelpful for LPs when it counts")

So, how does every VC fundraising pitch show top decile performance? 

Because they're fundraising, so they must. 

That can be achieved by cherry-picking performance data, manipulating benchmarks, or simply by inflating portfolio marks in a systematic and syndicated manner.

If you’ve read much of what I’ve published in the last few years, you’ll recognise the goal of making private markets more efficient and meritocratic; helping the right founders and managers raise capital. 

Reflecting the power of money plus incentives, Mary Lin and Patrick Ryan describe Odin as “Shopify for private markets” in the short term, and a “progress machine” in the long term. 

Odin provides the rails to make sure funding can get to the most important ideas, via the right people. Not necessarily the loudest or most obvious, but those that will drive technology forward the furthest. 

I’m excited to join them on this mission, assembling resources synthesised from the vast body of private market research and data.

Onwards!

Please give a warm welcome to Dan G., who joins Odin as Research Lead! 

Dan has spent years deep in the weeds of academic literature on venture capital & private equity, and we share a passion for and belief in the massive economic value that emerging fund managers can bring to society, especially radical managers with radical ideas about how the world could look very different. 

This is the first post in a new series of guides we are producing for emerging fund managers, covering everything from sourcing through to fund structuring. 

Today we’ll dive into the thorny topic of reserves. 

In the common wisdom of venture capital, there are two competing narratives about the use of reserves:

1. Reserves are a crucial way to improve performance by doubling down on your winners. They offer an opportunity to build or preserve ownership in the best companies, generating more alpha from asymmetric insider knowledge.

2. Reserves are a scam. Subsequent rounds are typically a significant step-up in price without a meaningful change in the risk profile of the company. Good piece from James Heath on this in October last year (see article for link)

This is further confused by the fact that analysis seems to suggest that reserve strategies rarely make sense, and yet remain common practice.

So, how should an emerging manager think about reserves in the present and future of their firm? In this article, Dan runs through the considerations!

https://lnkd.in/eWGXtAnq

Open article: The Reserves Paradox by Patrick Ryan • 13 min read

Risk is the central product of venture capital. To understand a particular fund strategy, you must understand how it tackles risk. 

Large funds, in their attempt to scale allocation, are essentially trying to scale risk. However, while fund size scales linearly, risk does not. 

Consider the three main categories of risk:
 
- Idiosyncratic risk is inelastic. It is the art of making good judgements, and cannot be improved by throwing more people at the problem.

- Systematic risk is exponential. As you inflate a category or market, you herd-in capital which accelerates growth and raises the stakes dramatically.

- Execution risk is an unknown. There is a belief that patterns might reveal founders who excel, but research largely indicates these are misleading.

So, to make scaled allocation work, large firms must fundamentally change how risk is perceived. They reduce idiosyncratic risk by magnifying consensus, and build a strategy on the momentum of systematic risk. 

In a nutshell, this is the financialisation of venture capital.

The concept of "fundability" arose in response to VCs needing to assemble larger syndicates, pulling more capital into their best-looking companies.

Over time, and across cycles, the firms who are most influential in coordinating large amounts of capital have survived to accumulate assets and status.

Thus, VC has biased towards forming and funding a "local consensus", rather than identifying outliers.

Logically, this becomes like a dog chasing its own tail, where a "good" investment is one that can most easily attract capital from investors — driving concentration without consqeuence for incumbents.

This has enabled the slow death of "Alpha" in VC, and the growing mediocrity of "Beta to the Center".

In hot markets (e.g. low interest-rates) or hot categories (e.g. AI) it's relatively easy to raise large amounts of growth capital. 

Because performance is largely understood via revenue, the ideal startup is a black box that scalably converts venture dollars into ARR.

In subsequent rounds, that ARR is (recursively) priced with multiples that scale to growth expectations. 

📈 more funding → faster growth → multiple expansion → higher prices → more funding 

Thus, the amount of money a startup raises is directly connected to future round pricing, regardless of how fragile or unprofitable their activity may be. 

(i.e. If the focus is on ARR at ridiculous multiples, all that matters is the velocity of "dollars of value sold" — even if you are selling those dollars for 10c.)

This is how "price" and "value" become dislocated. 

Then, the whole thing reverses in a market correction:

📉 less funding → slower growth → multiple contraction → lower prices → less funding 

The exponential upswing rapidly becomes an exponential downturn, ending with a bonfire of LP capital and paper marks. 

This is why, almost four years on, the market is still suffering from weak exit activity and lopsided allocation. Many "unicorns" created in 2018-2022 are nowhere near that mark in reality. 

In summary, these practices have introduced an insane level of systematic risk to a strategy that was supposed to hedge against macro concerns. 

The remedy is simply to understand the difference between price and value:

- For understanding market activity or investor demand, it's appropriate to look at price data. 

- For setting the terms of a transaction or investment marks, it is appropriate to use valuation.

Investors that do not understand the difference will keep falling into the same trap. Venture capital is an exit business, and exit markets generally care about valuation, not price.

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