This Is Going To Hurt is, read with a clinical eye, a textbook case study of moral injury and post-traumatic stress in a competent doctor, narrated by the patient himself, with the diagnosis hidden in plain sight.
A regular boring but non-superficial SaaS app would do well 5 years ago but now it might not get anyone to sign up because it's so easy to vibe code by tens of thousands of other people
I was thinking about how I recognize AI writing, and one big tell is excessively colorful verbs. A handful of journalists might write that a proposal "drew" 100 votes, but any normal person will just say "got".
which is why I think like a simple drawing of a pencil can stand for writing in some ways better than a chrome pen with a reflection, which is real very fancy, but it's a very particular kind of pen that not everybody might write with.
But if you need to reach superhuman levels of performance in a fully autonomous agent in a safety-critical environment, uh, just doing kind of that basic vanilla end-to-end is not enough.
There are many many unsolved problems in the world, many great ideas hiding in plain sight that were actually solvable that could have been multi-billion or multi-t trillion dollar businesses a while ago, but nobody's building them and not for any reason other than nobody went and did it.
I do the research I do the plan I do the implementation I throw the docs out and the next time I need research I just do it from scratch because tokens are cheap and my time is expensive
the ballerina and the kind of performer, that's the wrong reference class. Right now we have a lot of jobs where you have different tasks. So this is the task-based model jobs where you have like a lot of different tasks. So like a doctor, what is their job? They're filling out insurance documents. They're you know, going and like calling different pharmaceutical companies. And one of their tasks is to actually see the patient and talk to them, but that's like actually not the main part part of the job.
let's say we get into a narrative where like if you're a firm and you're not laying people off, then you're seen as like not adapting AI enough. So like then you'll get you're going to just get a cascade effect of firms like just needing to keep up with the Joneses in terms of like starting to lay people off.
The second is that most of the work that you do is actually going to happen on your computer in an environment like Codex or Cloud Co-work that becomes the sort of operating system for it becomes the sort of operating system for how how you do all of your work, whether that's your email, the documents you create, like all that kind of stuff.
did you know that according to the legal documents you yourself signed, your company's literal charter that you have right now, and this is not some hypothetical future thing, you've already put in motion, a rule that says you have a fiduciary duty to say yes in this situation.
According to Harvard Law School, among venturebacked companies that have the standard best practices set up that you got from your lawyer, okay, only 20% of founders are still the CEO 3 years after going public.
It used to be that you have documentation for other people who are going to use your library, but like you shouldn't do that anymore. Like you should have instead of HTML documents for humans, you have markdown documents for agents.
I'm mad at Amazon for laying off 16,000 people and blaming AI without an AI strategy for it. Those people are not going to be able to find jobs, by and large, and they're the first of many to come and nobody has a plan for this.
Melissa Perri explains how laying the foundation for great product management can help companies solve real customer problems while achieving business goals. By understanding how to communicate and collaborate within a company structure, you can create a product culture that benefits both the business and the customer.
Because of how source survival works, or indeed, how architectural survival works, we are often encouraged to think of the past as a place populated entirely by the wealthy elite.
A reminder that my novel Metallic Realms is available at a bookstore near you. Reviews call it "brilliant" (Esquire), "a total blast" (Chicago Tribune), "unrelentingly smart and inventive" (Locus), and "just plain wonderful" (Booklist). Maybe the perfect holiday gift for the booklover in your life?
So the Navy hired the shoe runners unit from the SS, paid them money, and then gave them drugs, different kinds of drug combinations, methamphetamine combined with cocaine and chewing gum and all kinds of things. So this is a big thing, you know. And there are documents to it.
So the instant assumption is, okay, so you can tell female from male. No, we can tell laying female from everything else. So males won't have medullary bone. Young females won't have them. Females outside of the breeding season won't have it.
Say goodbye to cycles of mock and doc feedback, and say hello to code-first prototypes with constant iteration (on prompts, models, etc) to answer three key questions.
Retrieval-augmented generation (RAG; Lewis et al., 2020), which conditions on the LLM's generation on retrieved documents is the most practical paradigm IMO.
The United States of America didn’t want the Soviet Union to collapse and disintegrate. They didn’t want that at the start of the Cold War in 1948. We now have the strategic documents. They were concerned about that, they didn’t want to do that. And certainly they didn’t want to do that in the year 1991.
I want to see more tools and fewer operated machines - we should be embracing our humanity instead of blindly improving efficiency. And that involves using our new AI technology in more deft ways than generating more content for humans to evaluate. I believe the real game changers are going to have very little to do with plain content generation.
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