After all these questions [about a particular feature], the team came to the same conclusion. We decided it would be best not to go through with it.

I think we could all use more decisions like this.

In order to produce a functional piece of software from AI, you need to know what you want and be able to clearly and precisely define it. There are times when I’m writing software just for myself where I don’t realize some of the difficulties and challenges until I actually start writing code.

This is very true.

I believe AI could create the software that has already been created faster than human programmers but that’s because someone figured out what that software should do

AI in its current state is very, very good at one thing: modeling and imitating a stochastic system. Stochastic refers to something that’s random in a way we can describe but not predict. Human language is moderately stochastic. When we speak or write, we’re not truly choosing words at random—there is a method to it, and sometimes we can finish each other’s sentences. But on the whole, it’s not possible to accurately predict what someone will say next.

It’ll be interesting to see how writers adapt to these models. For example, “finish each others words”. Word probabilities are based on patterns and rules, so what will make real human writing stand out from AI writing is breaking these long-standing rules off which AI is based.

In this light, we might be in for one of the greatest creative periods in history. Not because AI will help us do what we’ve always done just more efficiently, but because AI will force us to do new things differently, as that’s the only way we’ll stand out and be different.

Zeeshan Lakhani, an engineering director at BlockFi, Darren Newton, an engineering team lead at Datadog, and David Ashby, a staff engineer at SageSure, all met while working at a company called Arc90. They found that none of them had formal training in computer science, but they all wanted to learn more. All three came from humanities and arts disciplines: Ashby has an English degree with a history minor, Newton went to art school twice, and Lakhani went to film school for undergrad before getting a master’s degree in music and audio engineering

I worked at Arc90 with these folks and this is what I loved about Arc90: the interdisciplinary education outside of computer science and design was off the charts. People from all over the spectrum of education.