Been looking at my historical chats and emails to understand how I thought about #bitcoin.
I think it’s a great way to adjust mental models for the future.
1/ In a 2011 chat, someone said they’re buying $5k worth of bitcoins (when it was $30 per bitcoin).
I told them I think it’s a bubble :)
2/ As per the emails, I and friends were pretty excited about it in 2013.
Understood the technology properly.
We were even cooking up ideas to make bitcoin transactions simple, like a PayPal for bitcoins.
But at $600 per bitcoin, I decided it was overhyped.
3/ Multiple times opportunity arose and I passed up because I believed that even though the technology was really beautiful, the value was hard to pin down and hence at all prices, it seems over-valued.
4/ I think the massive (90% or more) crashes in price eventually hardened the skepticism and I stopped paying attention.
5/ My conclusion is that it’s easy to know something is breakthrough but what’s harder is:
- to know how big it’s going to
- whether that potential is already priced in today in the valuation
I knew bitcoin was big but not whether at $30/bitcoin, it justified itself.
6/ My engineer’s point of view was sharp but investor’s point of view was blunt.
(Another evidence of it is that at parent’s insistence, I had bought real estate, something I now know to be a stupid investment decision)
7/ What’s my current view?
I’m agnostic to whether bitcoin overvalued or undervalued because I haven’t done enough analysis.
My main concern for it is in its contribution to carbon emissions, something that’s counter acted by it’s benefit to people in oppressed nations.
8/ As for the investor’s hat, I think I’m getting better at being able to recognise big breakthroughs early on.
It’s an intellectual challenge too: understanding the curve of technology and how society changes with it.
9/ I expect this drive to assess potential early will help avoid the cognitive bias that over-values the past that has happened (in which a tech is a toy) but under-values the future that’s yet to happen (in which tech is the incumbent).
10/ I recommend everyone to regularly recalibrate their mental models by reflecting on their past.
Ask yourself:
- What did you predict that turn put to be not true?
- How should you adjust to be less wrong in future?
11/ Although remember: in retrospect, everyone is a billionaire :)
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1/ Balaji is a deep thinker on crypto and its implications.
Formerly the CTO of Coinbase and General Partner at Andreessen Horowitz, he’s believes crypto technologies such as bitcoin will change the world the say way Internet did.
Here's the podcast:
2/ We touch on a lot of topics in the podcast.
• How to assess a strange new thing's potential
• How technologies rise and fall
• How to tell what's a fad and what's real
• How to identify nascent technology that will change the world
This thread is based on that paper, so if you’re intrigued, highly recommend reading the entire thing arxiv.org/pdf/2104.01191…
2/ One of the most awe-inspiring insights from the paper is that many of the galaxies we see in the Hubble deep field image are FOREVER beyond our reach.
I don’t mean just practically, but even theoretically.
All startups belong to an ecosystem that makes or breaks them.
(a 🧵 thread on this mental model)
1/ All startups live in an ecosystem where different businesses directly or indirectly support one another.
e.g in the case of the automotive industry, the ecosystem consists of car manufacturers, parts manufacturers, petrol stations, service centers, car insurance companies.
2/ All of them mutually support the entire ecosystem, which means the growth or decline of one business will directly impact all other businesses.
You've heard of AI. But have you ever heard of IA?
🚀🚀
Today, at @VWO, we're announcing a big shakeup of the A/B testing industry.
(a thread about our breakthrough innovation)
1/ Our mission to help marketing and product teams reduce the effort required for figuring what works best for their business
In 2010 we pioneered the DIY visual editor for business teams for editing webpages and creating their variations for A/B tests without involving IT teams
2/ That innovation cut the effort to launch an A/B test from weeks to hours
But, as anyone who has run an A/B test knows, you still have to wait for weeks in order to start getting statistical significant results about which version is better.