Stop losing the good part
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A summary you can skim is easier to find and remember than a buried tab or a timestamp in your notes.
Paste a YouTube video, podcast, or article and get a clean summary you can save, organize into lists, and actually come back to.
Best mix of raw intellectual depth and long-term usefulness across math, physics, and AI.
Terence Tao presents mathematics as the study of models at the boundary between tractable and impossible, where progress often comes from identifying the right abstraction, ruling out tempting but doomed approaches, and finding deep connections across fields. He uses Kakeya, Navier-Stokes, prime number theory, Ricci flow, and formal proof systems to show that the hardest problems are less about raw computation than about discovering the right language for randomness, structure, and scale.
Read full summary →Why people keep using it
The idea is simple: take something long, make it readable, and keep the good ones together so they stay useful.
Stop losing the good part
A summary you can skim is easier to find and remember than a buried tab or a timestamp in your notes.
Organize by topic
Make a list for AI, startups, philosophy, or whatever you're digging into. Keep adding to it over time.
Share the short version
Share a readable summary instead of a two-hour video link. Let people decide if they want the full source.
How it works
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You get a structured, skimmable version with a link back to the original source.
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Open a finished collection and see what a summary actually looks like. These are full reading editions built from standout conversations, designed to be skimmed, reread, and shared.
Terence Tao presents mathematics as the study of models at the boundary between tractable and impossible, where progress often comes from identifying the right abstraction, ruling out tempting but doomed approaches, and finding deep connections across fields. He uses Kakeya, Navier-Stokes, prime number theory, Ricci flow, and formal proof systems to show that the hardest problems are less about raw computation than about discovering the right language for randomness, structure, and scale.
John Carmack's core view is that breakthrough engineering comes from understanding systems end-to-end, optimizing for user value rather than elegance alone, and exploiting constraints to find "smoke and mirrors" solutions that make impossible-seeming experiences practical. He applies this lens across game engines, VR, programming languages, and AGI: progress usually comes from a small number of deep, pragmatic insights, not from maximal abstraction or philosophical theorizing.
Knuth presents computer science as a craft of understanding across levels: from machine details to abstract theory, from formal proofs to human-readable exposition, and from worst-case analysis to practical performance. His core view is that progress comes from combining rigor, experimentation, taste, and humility about how little we truly understand.
Read the editorial notes
The point is not to watch faster. It is to keep the argument, the model, and the useful tension in a form you can recover later.
Open essayThe clean version is simple: let people get to the first good result for free, then charge in a way that stays legible after every run.
Open essayCurated examples are the beginning. The more important move is letting people turn one strong shelf into a shared place for ongoing research.
Open essayYou already have something in mind
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