Venture Capital Strategies: Mega-Funds vs. Specialized Funds

Venture capital is shifting towards specialization, with early-stage funds focusing on non-consensus opportunities for greater returns.

### The Evolving Landscape of Venture Capital: Strategies and Opportunities
* 💼 Lily Lyman from a_BC highlights a bifurcation in the venture capital market, distinguishing between **mega-funds** and **specialized early-stage firms**.
* 📈 Last year, **80% of capital raised** was funneled into established firms over 500 million, increasing their market representation from **2% to 25%**.
* 🔍 This trend indicates a **consolidation among pre-seed funds**, prompting specialized firms to differentiate and support **non-consensus founders** to **capture true alpha**.
* 💰 The multi-stage strategy at the seed stage operates like an **index game**, which can **dilute the early-stage class** if not countered by **focused investments**.
* ⚖ Founders are now more selective about their investors, considering how the investment **aligns with their company-building process**, especially in the context of the **changing market environment**.
* 🤖 With over **30% of venture capital** now in AI, there is a surge in AI-native companies, benefiting from **new models and capital structures** that enhance **operational efficiency**.
* 🏙 While a_BC invests across the US, they remain particularly optimistic about Boston's ecosystem, which excels in **producing top talent** and **solving complex problems** in various sectors.

The theory here is that you're getting two very different strategies, not both of which are particularly complementary. That's right, Caroline. It's great to be here. Thanks for having me again. I'm Lily Lyman, I'm at a_BC, we are a community-driven

early-stage venture firm based here in Boston. We invest in the pre-seed and seed stages in the world of B2B software. And your question is the right one. We're seeing the emergence of two very different strategies in venture, and it's bifurcating the market in a way that

almost looks like a barbell. On one hand, you have these big multi-billion dollar, multi-stage venture firms that are mega-firms. They're really sort of financial institutions at this point, and I hear LPs refer to these as venture beta.

On the other side of the spectrum, you have smaller funds, more specialized, targeted strategies. That's where we come into play, and it's because of our belief that's where you can still get venture alpha—that three-to-five, even 10X return—what's

happened over the last 18 months or so, though, is we're seeing a heavy concentration of LP dollars going into the mega-funds. So, 80% of capital raised last year went to established managers of firms sized over 500 million, and the representation of

these firms is increasing. So it's gone from about 2% to 25% in the venture market. And that over-representation has a lot of implications for LPs, for managers, and for founders. Okay, let's talk about what that means for VCs.

Ultimately, you're going to see more consolidation among the pre-seed stage funds.  Do you need the breadth of more focused funds?  Consolidation is happening in the middle. I think what it means is that we're

going to see more specialization at the earliest stages. So firms like ours need to really lean into differentiation, get to founders early, and back perhaps non-consensus, non-obvious founders and ideas, because that's how you can capture true alpha.

What's happening with the multi-stage strategy at the seed stage is that they play more of an index game, putting out a lot of checks and then backing the winners. But the implication is that they're not always

very price-sensitive, and it can dilute the entire early-stage class if you can't counter that and really dig in and go earliest and non-consensus. So that's how we've been thinking about it in order

to counteract some of the implications of the multi-stage indexing model at the seed stage. It kind of takes me back to when SoftBank first unveiled their $100 billion fund and everyone felt that the Vision Fund was just going to give enormous amounts

of money to individual founders or companies and sort of drown out the rest of the competition. Does that happen, or does it just inflate valuations? What is the real impact on those very early-stage bets?

I think it could have multiple impacts. I think, on one hand, the indexing can impact valuations for everyone, so it can actually dilute returns across the board. But on the other hand, if you can get in early or invest in non-consensus opportunities, I think you can still generate real alpha.

I think part of the implication is a question for founders as well. I think we're seeing founders think a lot about who they bring to their table at which stages of company building. In the market peak during the zero-interest-rate policy (ZIRP) era, there was a lot of speed dating; a lot of capital went out the door very quickly.

Then, two years later, we had a much tougher environment, and it was hard for founders. So I think we're seeing founders—both new and sophisticated—think about what kind of investments and investors they want around their table for each stage of company building.

And they're thinking more about alignment: What does that check mean to that firm, and how does that infer how they'll act during the company-building process? I'm assuming that most founders you're seeing are having to lean into generative AI, even if they are not an AI-specific company.

But what does that mean in terms of trying to uncover the least-covered areas or the particularly non-consensus builders and founders you want to find? We're certainly seeing a ton of opportunity in AI, and over 30% of venture capital is in this area.

Past year, we invested in AI companies, and we expect that number to increase next year. But what we're seeing is companies that are AI-native, both in their product offerings and in how they're built.

I think one of the things that makes this time particularly exciting to be an early-stage investor is that companies are being built with a new model and a new capital structure, allowing for greater efficiency. Engineering, sales, and marketing can all be much more efficient.

So there's a mentality of 'doing more with less.'  Outside of foundational models and infrastructure—areas where we invest heavily—in applied and vertical AI applications, I think you can build pretty big companies with a totally different capital structure, given the increased efficiencies of building with AI itself.

How many of those companies are in Boston, or are you looking across the US?

We invest across the US, but we're very bullish on Boston. Over half of our capital is deployed here.  That's because Boston's ecosystem consistently produces top talent, top research and development, and consistently solves hard problems in areas like healthcare, biotech, life sciences, financial services, cybersecurity, energy, and climate.

It's consistently solving really hard problems in areas like healthcare, biotech and life sciences, financial services, cybersecurity, and energy and climate.

So, you know, these three factors are part of what makes us very excited to invest in the Boston ecosystem, particularly in this age of applied AI.

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Emergence of Two Distinct Venture Capital Strategies

Two contrasting venture capital strategies are emerging: large, multi-stage firms and smaller, specialized funds.

Large firms are described as mega-firms or venture beta, acting like financial institutions.

Smaller funds focus on specialized strategies and aim for higher returns (venture alpha).

A significant portion of capital is flowing into mega-funds, leading to increased representation in the market.

This shift has implications for LPs, managers, and founders.

Implications for Venture Capitalists (VCs)

Consolidation is expected among pre-seed stage funds, leading to increased specialization.

Smaller firms need to differentiate themselves by focusing on early-stage, non-consensus founders and ideas.

Multi-stage firms employ an indexing strategy, making them less price-sensitive and potentially diluting early-stage investments.

The impact of large funds like SoftBank's Vision Fund on early-stage investments is discussed, considering its potential to inflate valuations.

Impact on Founders and Investment Strategies

Indexing can impact valuations, but early investments in non-consensus opportunities can still yield high returns.

Founders are becoming more selective about investors and alignment with their company-building process.

Founders are increasingly incorporating generative AI, even in non-AI-specific companies.

Opportunities in AI and Efficient Company Building

Significant venture capital is flowing into AI, with a focus on AI-native companies.

Companies are being built with new models and capital structures, leading to greater efficiency.

A 'doing more with less' mentality is emerging, particularly in applied and vertical AI applications.

Investments are made across the US, but a significant portion is deployed in Boston.

Boston's ecosystem is praised for its talent, R&D, and problem-solving capabilities in various sectors.