reading, watching & listening to

“Most of the people I know working in AI—and I might have a biased sample size—are people who are inspired about fixing the world. They grew up on sci-fi, and they're from a really cool science fiction intellectual tradition that feels really modern, really American. I first got really caught up in that because, you know, in 2020 and stuff I was like, "Wow, the whole world is sad," and here everyone's really excited. Everyone's really happy, and everyone really wants to build America and really wants to make something great. But they are also fighting market forces. They're also just trying to stay alive.”

what we lose when everything gets summarized.

an honest reflection from Yancey Strickler on stepping out of the crypto rabbit hole. 

had to read this several times to grok it but applied to a real-life example.

It’s hard to design the perfect onboarding. but it’s easy to check: “Did the user reach ‘Aha!’ in 3 steps instead of 7?” or “Did 80% of users complete the flow?”

So the industry (and people) naturally get pulled into automated loops. this is why mid-training is powerful and dangerous. it can manufacture the appearance of discernment while dodging deeper unmeasurable criteria.

“They have learned to produce the appearance of discernment without ever developing the faculty itself.”

He’ll be like: ‘Why is that? Why? What’s the purpose? What’s the intention and what’s the purpose?’”