Being late but still being early

I heard about Bitcoin for the first time in 2011. I was on a trip to Tahoe with my dad when highway patrol closed I80. During the winter it's the only road connecting the Bay Area and the Sierra Nevadas, so we had to spend the night in a motel in Auburn. We turned on the little TV to a news reporter losing their mind that this internet currency - totally made up, exclusively digital - just crossed $5 in value. It was named Bitcoin of all things. My dad shook his head and said something about dutch tulips. It's currently at $88,000 down from $100k earlier this year.

I became intimately familiar with Nvidia in 2015, when we were using their chips for ML training jobs¹. Its stock with the current split was $0.70, but it was trading at an unbelievably high P/E ratio. We all figured we were in a bubble and put our internship profits into the other "more diversified" FAANG stocks instead. Their stock is up 200x since then.

I was objectively early. But I felt late both times.

I understood the technical foundation of both Nvidia and Bitcoin. They were solving hard technical problems in game theory and matrix parallelization. And I could see from my vantage point in the weeds that they were succeeding. My main dilemma was pricing them. Is this price high or low? Will there actually be market adoption? I had no idea and that indecision led me to opting out.

I suspect technical people are biased towards this failure mode. Our "missing out on bitcoin" stories are rarely about a lack of knowledge. They're more often about our conviction on when the rubber meets the road. Or maybe better said when tech meets capital markets. I ironically don't see any of my financier friends have this same fear. They're quite open about having no idea about the tech. But they feel confident in the charts moving.

In little ways and big ways, we're always trying to do some estimate of where we're falling on the adoption curve. It influences the value of your stock options, obviously, but I also see it crop up in more subtle ways.

Case in point - I think about this phenomenon a fair amount when it comes to our podcast. Podcasting is already an established medium: all the big shows during 2020 are pretty much the same big ones that are around now. Nor do we have the advantage of platform level whitespace like existed in the early days of TikTok, Instagram, LinkedIn, and YouTube where there were more viewers trying to watch than content to serve them. You could get a good baseline of impressions by posting almost anything. By all measures we're showing up to the party as people are already putting away the beer cans.

But perhaps this anchors on the wrong thing. Even if everyone has heard of a podcast, not everyone has recorded one. I'm starting to notice an early cohort of my Stanford classmates getting into content production. Some of that is producing content for its own sake, chasing the influencer dream. But a lot of it is more incremental - increase deal flow for their firm, find some new clients, or just exercise some creative muscle. These are people who have been aware of social platforms for a decade and are only now deciding to make something. There's a very real future in which they start, fail, and are decried as the last wave of "wannabee influencers." Or they could be the start of a new trend where for every 1 of them there are 100 more in the coming years.

We might be reaching the high water point on podcasts. Or we might actually be at the beginning of a new wave. After all, if coding agents turn software engineers into something closer to managers than individual contributors I could imagine there will be some new found interest in tuning into a new podcast while you wait for your PR. I genuinely don't know. But I've stopped trying to answer that question, because I don't think it's answerable.

I find it's easy to feel like you're late to a trend when you're living in San Francisco. You probably aren't the first to hear about something. You might not even be in the first hundred thousand. But relatively speaking to market adoption, you might as well be the first one to know. The reference group is just distorted. You're comparing yourself to the small slice of people who heard before you instead of the 99.99% who haven't heard at all.

I can admit I don't have a native skill in accurately assessing future market conditions. To be honest, I don't think almost anyone is.² But I would rather take some the opportunity for asymmetric reward by knowing the tech, versus trying to figure out if we were early or late.

What I can answer is whether there's a gap. Is there something missing that I could make? For the podcast, the answer feels like clearly yes. ML is moving so fast that the coverage can't keep up. The people doing the technical work often don't prioritize explaining it, and the people explaining it often don't have the technical depth. I can't time the market on podcasts any better than I could time it on Bitcoin. So this is a different bet - not "is this the right moment" but "is this the right thing." The first question has always been impossible for me to answer. The second one I can actually take a swing at.

Back then tensorflow was really the only computational graph game in town. ↩
There's a reason why VC's hit rate is usually only 1/100 within a fund's vintage. This also reminds me of the story of McKinsey trying to price the cellphone market size back in 1980. They guessed 900k by 2000. The answer was actually 109 million. Oops. ↩

Footnotes