Episode Summary

In this 101 episode, Cheryl and Maxine go deep on the fundamentals of pre-seed investing, from how the stage came to exist to why the perceived risk gap between pre-seed and seed is much smaller than most investors think.

They break down the history of how venture stages evolved from single rounds to alphabetized series, how seed investors eventually got pushed up the stack, and why pre-seed emerged around 2017 to 2019 as a distinct category. They unpack why PitchBook's definition of pre-seed as "whatever the investor calls it" muddies the water, how seed preempts from larger funds are inflating average valuations, and why thinking in risk stages rather than round labels is a better framework for evaluating early companies.

You'll also hear why graduation rates from pre-seed to seed don't support the idea that pre-seed is two to three times riskier, why the Australian ecosystem is sitting on a talent surplus with a capital gap at pre-seed, and why this stage is particularly well suited for angels building diversified portfolios of 20 to 40 companies. Cheryl shares her framework for evaluating pre-seed opportunities through the lens of problem pain, frequency, and market size, and Maxine walks through how to think about return profiles, dilution, and valuation at a stage where there are no outputs to measure.

Time Stamps

00:00 Intro

01:56 – A brief history of venture stages: how pre-seed became a thing

07:14 – Why round labels are broken and risk stages are a better framework

09:23 – Seed preempts: how big funds are blurring the line between pre-seed and seed

11:48 – Is pre-seed actually riskier than seed? The case that it's not

16:41 – Graduation rates: what the data says about pre-seed to seed conversion

22:59 – Valuation dynamics: what pre-seed rounds look like in Australia vs the US

28:36 – Why Australian founders are leaving for the US at pre-seed and what that means

31:29 – How to evaluate pre-seed companies: inputs over outputs

35:05 – Cheryl's pain framework: frequency, intensity, and willingness to pay

38:28 – Why pre-seed is the best stage for diversifying who gets funded

43:44 – The AI revenue problem: why getting in early matters more than ever

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