Reflections from Our 2025 AGM - $1T Private Companies, AI Fundraising, and Outbound Sourcing

Sharing a few of the most interesting conversation topics from our 2025 AGM

We had our annual general meeting right before Thanksgiving, and every year I share some of what we covered. Last year, I shared this post about three potential states of the venture capital world, as I felt we were in the middle of significant shifts in the early-stage venture capital market. This year didn’t have a unifying theme, but I did discuss making sense of the returns potential for multi-billion-dollar VC funds, how AI companies are setting the bar for everyone when it comes to fundraising, and how outbound sourcing has changed over time.

The Math on How Multi-Billion Venture Funds Can Work - We Need $1T Companies

There has been a lot written about whether multi-billion-dollar VC funds can deliver meaningful returns for LPs. There is one loud camp that talks about the law of large numbers and how difficult it will be for those funds to generate attractive returns, whether measured by IRR or cash-on-cash multiple. In the back half of the year, I spent some time talking to LPs who are investors in these funds or looked closely at investing, as I was curious about how they thought the math could work - after all, they are the folks who are putting and keeping these multi-billion-dollar funds in business.

The LPs who made the strongest arguments for why these funds could work focused on rethinking the upper bound of terminal outcomes for VC-backed companies. We already have several private VC-backed companies valued at over $100B (including most of the Elonosphere companies, OpenAI, Stripe, Databricks, and Anthropic, to name a few). The math for a given large VC fund looks far less daunting if you believe we will see another step change increase in the upper bound of what’s achievable for private companies.

What if we are on the cusp of an era where we see $1 trillion private companies? While that seems a bit hard to imagine, it’s worth noting that 10-15 years ago, $1B private companies were rare enough that we called them unicorns.

I’ve lived through a variation of this myself. When I started working on Precursor in 2014, most of the portfolio modeling assumptions LPs used assumed that $1B valuations for private companies were rare and would remain rare. In such a world, it would be hard for funds like mine with larger portfolios and lower average ownership to deliver great returns. Thankfully, we are in a world with far more private companies valued at $1B or more than modeling predicted back then.

AI Companies Set the Terms for Everyone’s Fundraising

One of the most common conversations I had with founders this year was what it takes to raise money in this market. Particularly, those who are not in AI want to know why these AI companies are raising so much money so quickly while non-AI companies struggle to get attention. Most founders who ask this question underestimate the asymmetry of the VC business. Related to the point above about $1T companies, most venture capitalists are looking for companies they think will be outliers, not just good, solid companies.

Right now, rapid AI-driven traction is what gets VCs’ attention. Founders have figured this out, so they are doing whatever they can to generate steep revenue ramps over short periods of time to get venture capitalists’ attention. In some cases, what is being counted as “revenue” wouldn’t meet the traditional tests that we used for SaaS companies. But we are in a moment where deeply investigating the quality of a revenue number might be at odds with winning an allocation in a hot deal.

The asymmetry is a big part of what’s happening here. Put yourself in the shoes of a venture capitalist looking for massive home run outcomes. Is it easier to believe that a company that appears to be growing will continue to grow or that a company that isn’t growing as quickly will begin to grow quickly when it gets access to your capital? Betting on something that’s already working and continues to work could return your whole fund. If growth slows or it never was quite what you thought it was when you invested, the amount of money you’ll lose is likely something you can absorb. It is far more costly not to be in the winners than it is to make a few false positive investments if you’re managing a large pool of capital.

By far, the greatest challenge in fundraising today is rising above the noise floor, given the level of activity in the ecosystem and the number of companies competing for investors’ attention.

The Realities of Outbound Sourcing - Founders Understand the Game, Too

Once upon a time, firms that were effective at outbound messaging to founders had an edge, as many firms didn’t have the capabilities to execute it or any interest in making it a key part of their founder sourcing strategy.

Fast forward to today, many venture firms are very focused on outbound sourcing to find the most promising companies even earlier. The spectrum ranges from firms with entire software teams building custom tooling to those that use off-the-shelf software with custom queries. What was once an edge is not a standard tool in the VC sourcing arsenal.

Over the past few years, I have noticed a substantial increase in the number of inbound messages the portfolio founders we work with receive. Some of the messages are very well written, while others feel more like generic, trigger-based outbound templates. The reason I wanted to talk about this at our AGM is that I’ve seen more and more people who have learned how these trigger-based early-detection systems work. They’ve become quite strategic about when they send out the subtle signals they know will result in more attention and inbound.

If there was an era when simply having an early signal put you at the front of the line for meeting with a new founder, that era is long over. In addition to early signal, your outreach needs to come with more than just a recognition that you know or suspect the person might be starting a new company - the best founders are discerning and being first or early doesn’t mean what it used to in a world where everyone has their own system for surfacing people who are on the verge of starting new companies.