The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 8 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Dylan Field: Better AI Code Generation Makes Human Design Matter More
“It feels to me that the better code generation gets, the more design matters, and the more that actually the human pushing on design matters too, because even if you have a good starting spot from your design system, from, you know, AI generation, whether it b…”
Field: Front-end engineering will survive because translating design is merely mechanical
“That's not like a comment on oh, front-end engineering is dead. There's so much more to front-end engineering. Than just that translation step. That's kind of like the most mechanical part, and actually thinking through all the states, all the intended behavio…”
Field: Broad peer consensus on an investment thesis is a warning sign
“If you're investing in something, unless you're just going after momentum, which a lot of people do, but otherwise you need to have some point of view that like a lot of people would just blanket disagree with. And it should be scary to you if you're investing…”
Field: Deep learning was necessary to achieve 100% in visual generation
“Some more computational photography, you know, plus on blending and some of these early techniques that you kind of get like 85% of the way there to something awesome, but not a hundred percent. And it wasn't until, you know, we really had deep learning that y…”
Dylan Field: AI Research and Deterministic Software Require Completely Different Team Motions
“It's very different to be in a context of, you know, more deterministic software building. Than AI research. There are completely different motions of how you kind of run those teams in those areas.”
Field: Evaluating technology should start with upside potential, not failure modes
“The meta lesson I think that I've learned is, don't look for reasons why things are not gonna work. That's important, too, But it's not the place to start from. The place to start from is like, what could this be? How big could this be? How important could thi…”