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Think like an LP to Get a Job in VC

For years, I’ve recommended my friends who were looking at startup job opportunities to think like a VC. And having chatted a number of firms over the years about scout, associate/analyst, venture partner roles, I’ve come to a new revelation. Or rather one that I’ve practiced for a while, but haven’t connected the dots until recently.

When you’re looking for VC job opportunities, think like an LP. I’ve written about the LP calculus a few times before, like:

Here are some questions I usually consider:

  • How have you thought about your own differentiation that gets you access to some of the uniquely fund-defining opportunities you have?

  • What are the startups in your anti-portfolio? And what have you learned since from them?

  • [if their funds are wildly different in fund size (i.e. Fund I — $20M, Fund II — $100M)] How do you think about fund strategy now versus Fund [t_now-1]?

  • For context, usually each subsequent fund doubles in size. i.e. Fund I $20M, Fund II $40–50M, Fund III $80–100M

  • [If they have fund advisors, EIRs, and/or scouts] How do you pick advisors? What is your mental model for picking scouts?

  • Or one of my favorite phrasings: How do you differentiate the good from the great [advisors/scouts]?

Over the weekend, my friend sent me a great podcast for me to unwind. In it, I found an unlikely hero soundbite. “Your library holds a lot of value that you may not know until the story arrives. […] No one’s selling characters ’cause they’re one story away from this character becoming a hit.” While its context is related to why Marvel won’t sell any of its superheroes, Alex Segura‘s, co-president of Archie Comic Publications, anecdote proves just as insightful to the world of venture.

Discovering first-time early-stage founders is hard. The same is true for finding the next killer GP or venture firm. AngelList’s Rolling Funds are democratizing access to capital, lowering the barrier to entry for emerging fund managers. And really the success of a fund is determined by its MOIC — multiple on invested capital. 5x and up would be ideal. And that, like I mentioned in my last blogpost, boils down to the fund’s top one or two winners. Loosely analogized to a fund’s unicorn rate (percent of portfolio that are unicorns). In other words, the “one [investment] away from this [fund] becoming a hit.”

To see if a fund can consistently find those stories boils down to its systems. Often times, you’re joining a fund that has yet to have a runaway success. Or a fund that has a fund returner. So, instead, you’re looking at their thesis and if their thesis allows them to be:

  1. The best dollar on the cap table of a startup in their scope

  2. Forward-thinking enough to see where the market is heading, rather than where it’s been

  • And by definition of being forward-thinking, taking bets/risks that few other VCs would, yet calculated enough to make logical sense given the trajectory of the market. In other words, is the thesis grounded on first principles, yet able to capture their second-order effects?

  • That, in turn, requires you as a VC applicant to have decent literacy in the market the firm is betting in.

As James Clear, author of Atomic Habits, wrote, “You do not rise to the level of your goals. You fall to the level of your systems.” What are their mental models? Fund strategy? How do they think about portfolio construction? About capital allocation? And more importantly, time allocation?

If you’re looking to learn more about GP-LP dynamics, I highly recommend Samir Kaji’s Venture Unlocked podcast and Notation Capital’s Origins podcast.

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