Hey, OP here. I view it like this: if you were to take all technical people on the market for launching a startup and plot them on a distribution to find the "valuable in early stage" subset, you would find that 35% are good enough to get a startup off the ground. They don't need to be extraordinary programmers, just good enough but with a lot of drive.*
However, for non-technical folks that are on the market, the distribution is worse. Only the top 10% ~ 15% actually have sufficient abilities to pull it off. The remaining fall into the archetype I wrote about here.
The caliber for what's in the market is skewed thus the technical person has to be a whole lot more picky than the other way around to avoid ending up with a dead weight.
[*]: This excludes specialized skills like Deep Learning or chemical bio-engineering, etc...
If you're taking a fail fast type approach, the business guys fail faster when they can't get a tech co-founder to rally around their ideas. If you can't do that, you probably can't sell the MVP either. On flipside, the tech guys will spend month and even years polishing their 'product' without ever actually launching it with actual attempts to sale it. So they fail slowly after sinking tons of time. They'll talk about it as a side-project to minimize the appearance of failure but if they put all that work in they really do want it to succeed. They just get to the point where code is good enough and can't force themselves to transition to marketing/sales/etc.
This list is a pure fallacy of statistical understanding. Skewed data and cherry-picking while also being strengthened by our subjective biases. I would appreciate the list way more if it also included founders who applied but were rejected, or for any other reason were not invested in.
For stuff like this I recommend the book, May Contain Lies by Alex Edmans, he does a fantastic job explaining how most of the time we seek data to confirm our hypotheses, instead of seeking a hypotheses that confirms our data.
> However, for non-technical folks that are on the market, the distribution is worse.
And that's where I took issue with your post -- that you are lumping all these people as "business co-founders".
That's false. To call yourself a business co-founder, you need to have the same kind of business and management chops as a technical co-founder has technical chops.
Your post seems to be complaining about co-founders who are just idea people who don't have any business skills at all. It's misleading to call them "business co-founders". You should call them "idea co-founders" or something.
If I had to re-summarize your point, I'd put it this way:
1. Success is very little on the idea, almost entirely on the execution
2. Execution has both a technical side and a business side, and can fail from a poor execution either way.
How this applies to your target audience:
You have an idea for a business? Nice -- that's almost worthless (1). You can't influence execution on the technical side, so you need to bring execution from the business side (2).
I like the numbers -- "a waitlist of 1000 people or LOI from 20 businesses" gives a better idea what kind of execution a non-technical co-founder should be capable of.
These discussions also get wrapped up in what "non-technical" means.
It can mean management skillset.
It can mean people-networking and sales skillset.
For an early-stage startup, the former doesn't bring much value (management value literally scales with employee count) while the latter absolutely does.
However, for non-technical folks that are on the market, the distribution is worse. Only the top 10% ~ 15% actually have sufficient abilities to pull it off. The remaining fall into the archetype I wrote about here.
The caliber for what's in the market is skewed thus the technical person has to be a whole lot more picky than the other way around to avoid ending up with a dead weight.
[*]: This excludes specialized skills like Deep Learning or chemical bio-engineering, etc...