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A DEVELOPER PROVED THAT MOST OF THE CLASSES YOU WRITE SHOULD NEVER HAVE BEEN CLASSES AT ALL 27 minutes from Jack Diederich, a Python core developer, on how much of your code is just a function wearing a costume. -> The moment it lands, the rule is brutal: if...

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slash1s

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265,627 просмотров • 13 дней назад •via X (Twitter)

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A DEVELOPER PROVED THAT MOST OF THE LANGUAGE RUNNING EVERY WEBSITE YOU USE IS A MINEFIELD AND THAT ALMOST NO ONE WAS EVER TAUGHT WHICH PARTS ARE SAFE An hour from Douglas Crockford, the man who invented JSON, on the good parts of JavaScript buried under a pile of blunders nobody warned you about. -> The moment it lands, every weird bug makes sense. The language never had time to be polished. It went global in months, bad parts and all, and you inherited every one of them. Global variables. Silent semicolon insertion. eval. Coercion that turns a simple comparison into a coin flip. Most people never learned to avoid them -- they just lose hours and blame themselves. Writing JavaScript that runs was never the skill -> knowing which half of it to never touch is. And when an AI agent happily generates the bad parts at scale, the person who knows the safe subset is the one who catches it before it ships. Everyone writes JavaScript. Almost no one was shown the line between the parts that save you and the parts that quietly burn you. Bookmark and Watch it ↓
1:01:03

A DEVELOPER PROVED THAT MOST OF THE LANGUAGE RUNNING EVERY WEBSITE YOU USE IS A MINEFIELD AND THAT ALMOST NO ONE WAS EVER TAUGHT WHICH PARTS ARE SAFE An hour from Douglas Crockford, the man who invented JSON, on the good parts of JavaScript buried under a pile of blunders nobody warned you about. -> The moment it lands, every weird bug makes sense. The language never had time to be polished. It went global in months, bad parts and all, and you inherited every one of them. Global variables. Silent semicolon insertion. eval. Coercion that turns a simple comparison into a coin flip. Most people never learned to avoid them -- they just lose hours and blame themselves. Writing JavaScript that runs was never the skill -> knowing which half of it to never touch is. And when an AI agent happily generates the bad parts at scale, the person who knows the safe subset is the one who catches it before it ships. Everyone writes JavaScript. Almost no one was shown the line between the parts that save you and the parts that quietly burn you. Bookmark and Watch it ↓

slash1s

13,073 просмотров • 16 дней назад

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.
0:27

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.

Dustin

315,019 просмотров • 3 месяцев назад

A DEVELOPER PROVED THE REGEX YOU'VE WRITTEN A THOUSAND TIMES IS SECRETLY A COMPILER AND THAT ALMOST NO ONE WHO USES THEM HAS ANY IDEA WHAT ACTUALLY RUNS 36 minutes from Paul Wankadia, the engineer behind a regex engine that compiles your pattern straight down to raw machine code -- walking through what really happens between the slashes. -> The moment it clicks, regex stops being magic punctuation you paste from Stack Overflow and becomes what it actually is: a tiny machine. Your pattern gets turned into a state machine, and that machine is what runs against every character of your text. That one idea explains everything you never understood. Why one regex returns instantly and a nearly identical one hangs your whole server. Why some patterns are safe and others are a denial-of-service waiting to happen. It was never random -- it's whether the machine underneath is built well or badly. Writing a regex was never the skill -> reading one is. And now that an AI agent hands you dense, clever patterns you'd never write yourself, the person who can see the machine underneath is the one who catches the one that takes down production at 3am. Everyone copies regex and prays. This is the talk that ends the praying. Save it. The next time a pattern "Just works," you'll actually know why ↓
36:09

A DEVELOPER PROVED THE REGEX YOU'VE WRITTEN A THOUSAND TIMES IS SECRETLY A COMPILER AND THAT ALMOST NO ONE WHO USES THEM HAS ANY IDEA WHAT ACTUALLY RUNS 36 minutes from Paul Wankadia, the engineer behind a regex engine that compiles your pattern straight down to raw machine code -- walking through what really happens between the slashes. -> The moment it clicks, regex stops being magic punctuation you paste from Stack Overflow and becomes what it actually is: a tiny machine. Your pattern gets turned into a state machine, and that machine is what runs against every character of your text. That one idea explains everything you never understood. Why one regex returns instantly and a nearly identical one hangs your whole server. Why some patterns are safe and others are a denial-of-service waiting to happen. It was never random -- it's whether the machine underneath is built well or badly. Writing a regex was never the skill -> reading one is. And now that an AI agent hands you dense, clever patterns you'd never write yourself, the person who can see the machine underneath is the one who catches the one that takes down production at 3am. Everyone copies regex and prays. This is the talk that ends the praying. Save it. The next time a pattern "Just works," you'll actually know why ↓

slash1s

191,386 просмотров • 24 дней назад

A LINUX KERNEL DEVELOPER PROVED THE THING YOU PUSH CODE TO IS SECRETLY A DATABASE THAT CAN VERSION ALMOST ANYTHING AND THAT MOST DEVS HAVE ONLY EVER TOUCHED A TENTH OF IT 42 minutes from Josh Triplett -- a longtime Linux kernel and Debian developer -- showing that Git is a general-purpose, tamper-evident versioning engine that just happens to be famous for code. -> The moment it clicks, Git stops being "Where my code lives" and becomes what it really is underneath: a content-addressable store that can version almost anything -- your configs, your notes, your servers' state, entire datasets. People run whole wikis on it. They version their entire machine's configuration with it. They ship websites by pushing to it. They track data too big to email. None of it is a hack -- it's the same handful of objects you already use for code, pointed somewhere new. Treating Git as a code-only tool was never the ceiling -> it's a versioning engine for anything, and the people who see that automate what the rest of the team still does by hand. And as AI agents start spitting out not just code but configs, docs and data, the one system that can version and audit all of it at once is already sitting on your machine. You learned five commands to survive. This is the talk that shows you were standing on top of a database the whole time. It changes what you think the tool is even for. Bookmark & Watch it today ↓
42:24

A LINUX KERNEL DEVELOPER PROVED THE THING YOU PUSH CODE TO IS SECRETLY A DATABASE THAT CAN VERSION ALMOST ANYTHING AND THAT MOST DEVS HAVE ONLY EVER TOUCHED A TENTH OF IT 42 minutes from Josh Triplett -- a longtime Linux kernel and Debian developer -- showing that Git is a general-purpose, tamper-evident versioning engine that just happens to be famous for code. -> The moment it clicks, Git stops being "Where my code lives" and becomes what it really is underneath: a content-addressable store that can version almost anything -- your configs, your notes, your servers' state, entire datasets. People run whole wikis on it. They version their entire machine's configuration with it. They ship websites by pushing to it. They track data too big to email. None of it is a hack -- it's the same handful of objects you already use for code, pointed somewhere new. Treating Git as a code-only tool was never the ceiling -> it's a versioning engine for anything, and the people who see that automate what the rest of the team still does by hand. And as AI agents start spitting out not just code but configs, docs and data, the one system that can version and audit all of it at once is already sitting on your machine. You learned five commands to survive. This is the talk that shows you were standing on top of a database the whole time. It changes what you think the tool is even for. Bookmark & Watch it today ↓

slash1s

382,285 просмотров • 26 дней назад

"The one thing that's going to be truly future proof is judgment. What is the biggest challenge when you have a thousand AI engineers writing code? AI slop. In an era when you can do everything, the question is which of these things matter. On the engineer side, it is evaluating the code. Which of this code is even valuable? You can have AI engineers writing beautiful code that could be wrong, that could have bugs in it, that could be vulnerable. Someone needs to review it. Make sure to have a human review at some point, especially critical code that is in the core of your system. On the product side is judgment around what needs to be built and evaluating. And similarly in design, you have to have judgment around, does it make sense in the broader design system. I think this judgment is the number one thing that humans are going to bring in an era of infinite productivity."
1:12

"The one thing that's going to be truly future proof is judgment. What is the biggest challenge when you have a thousand AI engineers writing code? AI slop. In an era when you can do everything, the question is which of these things matter. On the engineer side, it is evaluating the code. Which of this code is even valuable? You can have AI engineers writing beautiful code that could be wrong, that could have bugs in it, that could be vulnerable. Someone needs to review it. Make sure to have a human review at some point, especially critical code that is in the core of your system. On the product side is judgment around what needs to be built and evaluating. And similarly in design, you have to have judgment around, does it make sense in the broader design system. I think this judgment is the number one thing that humans are going to bring in an era of infinite productivity."

Patrick OShaughnessy

24,818 просмотров • 5 месяцев назад

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.
0:35

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.

Dustin

82,714 просмотров • 3 месяцев назад

A DEVELOPER PROVED YOU CAN FIND THE EXACT COMMIT THAT BROKE YOUR CODE IN A HISTORY OF 10,000 -- IN ABOUT 13 STEPS, AUTOMATICALLY.. 33 minutes from a Google engineer on git bisect: the built-in command that binary-searches your entire history to hunt down the one commit that introduced a bug. -> The moment it lands, "When did this break?" stops being an afternoon of guessing. You hand git a good commit, a bad one, and a test and it finds the culprit while you watch. Most people debug a regression by reading diffs by hand, blaming the obvious file, and hoping. Bisect doesn't hope. It cuts the search in half, then in half again, until only the guilty commit is left standing. Reading history by hand was never the skill -> letting git do the binary search for you is. And when an AI agent dumps hundreds of commits into your repo and one quietly breaks production, bisect is what finds the needle without you reading a single line. The bug isn't hiding. It's sitting in one exact commit. Most people just never learned to make git point at it. Bookmark & Watch it today ↓
32:07

A DEVELOPER PROVED YOU CAN FIND THE EXACT COMMIT THAT BROKE YOUR CODE IN A HISTORY OF 10,000 -- IN ABOUT 13 STEPS, AUTOMATICALLY.. 33 minutes from a Google engineer on git bisect: the built-in command that binary-searches your entire history to hunt down the one commit that introduced a bug. -> The moment it lands, "When did this break?" stops being an afternoon of guessing. You hand git a good commit, a bad one, and a test and it finds the culprit while you watch. Most people debug a regression by reading diffs by hand, blaming the obvious file, and hoping. Bisect doesn't hope. It cuts the search in half, then in half again, until only the guilty commit is left standing. Reading history by hand was never the skill -> letting git do the binary search for you is. And when an AI agent dumps hundreds of commits into your repo and one quietly breaks production, bisect is what finds the needle without you reading a single line. The bug isn't hiding. It's sitting in one exact commit. Most people just never learned to make git point at it. Bookmark & Watch it today ↓

slash1s

37,059 просмотров • 17 дней назад

A DEVELOPER MADE A REAL COMMIT WITHOUT EVER TYPING GIT ADD OR GIT COMMIT -- JUST TO PROVE THE COMMANDS YOU LIVE BY ARE A THIN SHELL OVER A DATABASE YOU'VE NEVER ONCE OPENED 55 minutes from Tim Berglund, a longtime Git teacher and GitHub evangelist, taking the tool apart down to the raw objects almost nobody who uses it every day has ever touched. -> The moment it clicks, Git stops being a pile of memorized commands and becomes what it actually is underneath: a tiny content-addressed database of blobs, trees and commits. git add and git commit are just polite wrappers around writing objects into it by hand. Every commit you've ever made was Git hashing a snapshot and filing it by fingerprint. Branches are just labels pointing at one of those objects. The work you thought you destroyed with a bad reset is still sitting in the reflog. Once you can see that graph, the commands that used to terrify you stop being scary at all. Memorizing commands was never the skill -> reading the object graph in your head is. And with an AI agent now committing and rebasing on your machine faster than you can follow, the one person who can untangle the mess it leaves is the one who knows what's really stored down there. There's a person on every team everyone runs to when Git breaks. This is the talk that quietly turns you into them. You'll reach for it the next time a rebase goes sideways. Bookmark & Watch it today ↓
55:19

A DEVELOPER MADE A REAL COMMIT WITHOUT EVER TYPING GIT ADD OR GIT COMMIT -- JUST TO PROVE THE COMMANDS YOU LIVE BY ARE A THIN SHELL OVER A DATABASE YOU'VE NEVER ONCE OPENED 55 minutes from Tim Berglund, a longtime Git teacher and GitHub evangelist, taking the tool apart down to the raw objects almost nobody who uses it every day has ever touched. -> The moment it clicks, Git stops being a pile of memorized commands and becomes what it actually is underneath: a tiny content-addressed database of blobs, trees and commits. git add and git commit are just polite wrappers around writing objects into it by hand. Every commit you've ever made was Git hashing a snapshot and filing it by fingerprint. Branches are just labels pointing at one of those objects. The work you thought you destroyed with a bad reset is still sitting in the reflog. Once you can see that graph, the commands that used to terrify you stop being scary at all. Memorizing commands was never the skill -> reading the object graph in your head is. And with an AI agent now committing and rebasing on your machine faster than you can follow, the one person who can untangle the mess it leaves is the one who knows what's really stored down there. There's a person on every team everyone runs to when Git breaks. This is the talk that quietly turns you into them. You'll reach for it the next time a rebase goes sideways. Bookmark & Watch it today ↓

slash1s

236,000 просмотров • 25 дней назад

Maria Popova on the soul, the self, and what AI will never have: "AI will never have feeling. AI will have the simulacrum of feeling. AI will never write the great American poem, the great French poem, because it hasn't suffered. AI doesn't have the capacity to suffer. Even if you try to make it suffer, meaning write a command that is to execute failure, it'll already be succeeding at executing failure. AI can only ever succeed. And without suffering, what kind of true art can there be? All writing that is truly moving is born of feeling and time. AI has neither; it's an instantaneous, unfeeling delivery of pure information. The function of what we call the soul is real. Whatever it's made of, where it is. And the part that I worry about is that today, most people live on the level of the self and not the level of the soul. Just the costume of personality over the soul." The value of persons does not rest on our "costume of personality," but on the soul beneath it.
2:05

Maria Popova on the soul, the self, and what AI will never have: "AI will never have feeling. AI will have the simulacrum of feeling. AI will never write the great American poem, the great French poem, because it hasn't suffered. AI doesn't have the capacity to suffer. Even if you try to make it suffer, meaning write a command that is to execute failure, it'll already be succeeding at executing failure. AI can only ever succeed. And without suffering, what kind of true art can there be? All writing that is truly moving is born of feeling and time. AI has neither; it's an instantaneous, unfeeling delivery of pure information. The function of what we call the soul is real. Whatever it's made of, where it is. And the part that I worry about is that today, most people live on the level of the self and not the level of the soul. Just the costume of personality over the soul." The value of persons does not rest on our "costume of personality," but on the soul beneath it.

David Perell Clips

12,220 просмотров • 1 месяц назад

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: “The code that Oracle is writing, Oracle isn’t writing. Our AI models are writing.” This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: “We don’t write the procedure. We declare our intent.” That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: “We just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.” You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.
0:31

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: “The code that Oracle is writing, Oracle isn’t writing. Our AI models are writing.” This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: “We don’t write the procedure. We declare our intent.” That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: “We just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.” You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.

Dustin

534,277 просмотров • 3 месяцев назад

Jensen Huang just told the world something nobody wants to hear. AI is not coming for your job. It is coming for the part of your job you mistakenly believe IS your job. Huang: “The purpose of your job and the tasks that you do in your job are related but not the same.” That one sentence is the fault line between the people who thrive in the next decade and the people who vanish from it. Huang used himself as proof. Reduce the CEO of Nvidia to his raw outputs and his entire career is typing and talking. Both have been automated to superhuman levels. Huang: “Typing and talking have both been automated to a superhuman level by AI. And yet, I’m busier than ever.” The man building the infrastructure that automates human labor has never worked harder. That should stop you cold. We look at a profession and see the tasks. The motions. The mechanical friction. We never see the intent underneath. And when AI arrives, we panic. Because we confuse the task with the job. The task was never the job. It was always the bottleneck between a human and their actual purpose. Now the bottleneck is dissolving. Years ago, the experts declared radiology dead. The algorithm could read a scan better than any human. A generation of medical students listened. They walked away from the field. The result was catastrophic. Huang: “We need more radiologists than ever, and we don’t have enough.” The algorithm did not replace the doctor. It armed the doctor. Suddenly the department could see more patients. Catch more anomalies. Generate more revenue. The hospital did not fire the radiologists. It tried to hire more. And could not find them. Because we terrified an entire generation out of a career with a prediction that landed exactly backwards. Now the same hysteria is consuming software engineering. The timeline is screaming that coding is dead. Meanwhile, inside the very company building the hardware that automates code. Huang: “The software engineers that know how to use AI, know how to work with agentic systems, are the most popular and the most successful.” The tool did not replace the architect. It replaced the shovel. This is the pattern nobody wants to confront. AI does not eliminate the human. It eliminates the friction that made the human slow. And when the friction disappears, demand for the human explodes. But only if the human shows up. The ones who defined themselves by the mechanical act of writing code are fading. The ones who defined themselves by what the code was meant to build are now the most valuable people on the planet. That is not a nuance. That is the entire dividing line. The machine will write the script. Read the scan. Draft the brief. It will never possess the reason any of it needed to exist. The task was never the job. And nobody who figures that out last gets the privilege of figuring it out twice.
2:00

Jensen Huang just told the world something nobody wants to hear. AI is not coming for your job. It is coming for the part of your job you mistakenly believe IS your job. Huang: “The purpose of your job and the tasks that you do in your job are related but not the same.” That one sentence is the fault line between the people who thrive in the next decade and the people who vanish from it. Huang used himself as proof. Reduce the CEO of Nvidia to his raw outputs and his entire career is typing and talking. Both have been automated to superhuman levels. Huang: “Typing and talking have both been automated to a superhuman level by AI. And yet, I’m busier than ever.” The man building the infrastructure that automates human labor has never worked harder. That should stop you cold. We look at a profession and see the tasks. The motions. The mechanical friction. We never see the intent underneath. And when AI arrives, we panic. Because we confuse the task with the job. The task was never the job. It was always the bottleneck between a human and their actual purpose. Now the bottleneck is dissolving. Years ago, the experts declared radiology dead. The algorithm could read a scan better than any human. A generation of medical students listened. They walked away from the field. The result was catastrophic. Huang: “We need more radiologists than ever, and we don’t have enough.” The algorithm did not replace the doctor. It armed the doctor. Suddenly the department could see more patients. Catch more anomalies. Generate more revenue. The hospital did not fire the radiologists. It tried to hire more. And could not find them. Because we terrified an entire generation out of a career with a prediction that landed exactly backwards. Now the same hysteria is consuming software engineering. The timeline is screaming that coding is dead. Meanwhile, inside the very company building the hardware that automates code. Huang: “The software engineers that know how to use AI, know how to work with agentic systems, are the most popular and the most successful.” The tool did not replace the architect. It replaced the shovel. This is the pattern nobody wants to confront. AI does not eliminate the human. It eliminates the friction that made the human slow. And when the friction disappears, demand for the human explodes. But only if the human shows up. The ones who defined themselves by the mechanical act of writing code are fading. The ones who defined themselves by what the code was meant to build are now the most valuable people on the planet. That is not a nuance. That is the entire dividing line. The machine will write the script. Read the scan. Draft the brief. It will never possess the reason any of it needed to exist. The task was never the job. And nobody who figures that out last gets the privilege of figuring it out twice.

Dustin

52,763 просмотров • 2 месяцев назад

Hermes agent supports Browserbase to browse and interact the web just like a human. You can add it when you setup your agent, or add it with Watch it add deodorant to my amazon cart, something much needed for engineers around the world.
0:23

Hermes agent supports Browserbase to browse and interact the web just like a human. You can add it when you setup your agent, or add it with Watch it add deodorant to my amazon cart, something much needed for engineers around the world.

Kyle Jeong

28,034 просмотров • 2 месяцев назад

"The number one job of government is to keep people safe" Oliver Dowden NO IT IS NOT!!! and we have never needed a national emergency alert before, and all government buildings already have a siren or alarm. There is more to it.
0:45

"The number one job of government is to keep people safe" Oliver Dowden NO IT IS NOT!!! and we have never needed a national emergency alert before, and all government buildings already have a siren or alarm. There is more to it.

Darren of Plymouth

390,558 просмотров • 3 лет назад

Mark Zuckerberg said something so quietly devastating that even he does not seem to understand what he gave away. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here.” He asked it as a rhetorical question. It stopped being rhetorical the moment he finished the sentence. A company was never a mind. It was a translation layer, built so one person’s vision could survive contact with a thousand strangers who would never fully understand it. Every meeting, every manager, every layer between an idea and the person executing it was the cost of that translation. We just called that cost the company, and mistook it for the value. Meta proved it this year. Thousands of roles cut. Thousands more reassigned into the machine that no longer needs a translator. Zuckerberg asked what ten thousand people are for, if they are not smarter than one. There is a harder question underneath it. A company was never about being smarter than anyone. It was about reaching further than any one person’s hands could go alone. AI does not make you smarter than ten thousand people. It removes the only reason you ever needed ten thousand people. That does not measure what you are worth. It never did. It only ever measured how far your own mind could reach before it needed other people to carry it further. Reach used to cost a payroll. Now it costs your attention. The gate was never about intelligence. It was about who got to multiply themselves. For a hundred years, that gate opened for almost no one. Zuckerberg: “Instead of having relatively few people be able to harness the power of a 10,000-person organization… I think in the future almost everyone is going to have that.” He asked what ten thousand people are for, if they are not smarter than one. You were never the ten thousand. You were always the one.
0:59

Mark Zuckerberg said something so quietly devastating that even he does not seem to understand what he gave away. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here.” He asked it as a rhetorical question. It stopped being rhetorical the moment he finished the sentence. A company was never a mind. It was a translation layer, built so one person’s vision could survive contact with a thousand strangers who would never fully understand it. Every meeting, every manager, every layer between an idea and the person executing it was the cost of that translation. We just called that cost the company, and mistook it for the value. Meta proved it this year. Thousands of roles cut. Thousands more reassigned into the machine that no longer needs a translator. Zuckerberg asked what ten thousand people are for, if they are not smarter than one. There is a harder question underneath it. A company was never about being smarter than anyone. It was about reaching further than any one person’s hands could go alone. AI does not make you smarter than ten thousand people. It removes the only reason you ever needed ten thousand people. That does not measure what you are worth. It never did. It only ever measured how far your own mind could reach before it needed other people to carry it further. Reach used to cost a payroll. Now it costs your attention. The gate was never about intelligence. It was about who got to multiply themselves. For a hundred years, that gate opened for almost no one. Zuckerberg: “Instead of having relatively few people be able to harness the power of a 10,000-person organization… I think in the future almost everyone is going to have that.” He asked what ten thousand people are for, if they are not smarter than one. You were never the ten thousand. You were always the one.

Dustin

43,950 просмотров • 4 дней назад

Dario Amodei, CEO of Anthropic, just shortened your career timeline. His own engineers have stopped writing code. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most advanced AI on Earth are already being replaced by what they built. Not in theory. Not in a forecast. Inside the building. Right now. Amodei: “I think we might be 6 to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” Six to twelve months. Not from automating busywork. From replacing the full scope of what a software engineer does. Architecture. Logic. Debugging. Deployment. The entire chain. Software engineering is not some fading trade. It is the highest-paid, highest-demand, most protected skill the modern economy ever produced. And the man running a frontier lab just gave it a six-month shelf life. If the most technically sophisticated job in the economy falls first, nothing beneath it is safe. That is the inversion no one saw coming. The assumption was always that AI would eat from the bottom. Routine work. Data entry. Simple automation. It started at the top. Engineers first. Then analysts. Then strategists. Then the managers overseeing work that no longer needs them. The displacement doesn’t crawl upward. It cascades downward. Starting with the people closest to the technology itself. Amodei: “If I had to guess, I would guess that this goes faster than people imagine, and that that key element of code, and increasingly research, going faster than we imagine.” Not just code. Research. Hypotheses. Experiments. Interpretation. Discovery itself. If AI closes that loop, it doesn’t just write software. It improves itself. Every iteration compresses the timeline further. Amodei: “It’s very hard for me to see how it could take longer than a few years.” He is not selling optimism. He is setting a ceiling. A few years. Maximum. For AI to absorb the two most important intellectual functions in the economy. The window to position yourself is not a decade. It is already closing.
0:58

Dario Amodei, CEO of Anthropic, just shortened your career timeline. His own engineers have stopped writing code. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most advanced AI on Earth are already being replaced by what they built. Not in theory. Not in a forecast. Inside the building. Right now. Amodei: “I think we might be 6 to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” Six to twelve months. Not from automating busywork. From replacing the full scope of what a software engineer does. Architecture. Logic. Debugging. Deployment. The entire chain. Software engineering is not some fading trade. It is the highest-paid, highest-demand, most protected skill the modern economy ever produced. And the man running a frontier lab just gave it a six-month shelf life. If the most technically sophisticated job in the economy falls first, nothing beneath it is safe. That is the inversion no one saw coming. The assumption was always that AI would eat from the bottom. Routine work. Data entry. Simple automation. It started at the top. Engineers first. Then analysts. Then strategists. Then the managers overseeing work that no longer needs them. The displacement doesn’t crawl upward. It cascades downward. Starting with the people closest to the technology itself. Amodei: “If I had to guess, I would guess that this goes faster than people imagine, and that that key element of code, and increasingly research, going faster than we imagine.” Not just code. Research. Hypotheses. Experiments. Interpretation. Discovery itself. If AI closes that loop, it doesn’t just write software. It improves itself. Every iteration compresses the timeline further. Amodei: “It’s very hard for me to see how it could take longer than a few years.” He is not selling optimism. He is setting a ceiling. A few years. Maximum. For AI to absorb the two most important intellectual functions in the economy. The window to position yourself is not a decade. It is already closing.

Dustin

16,132 просмотров • 2 месяцев назад

Nobel Prize winner and Google DeepMind CEO Demis Hassabis just revealed the real AI skill gap: “The next generation will do things that used to take teams of 10, 20, 30, 50 people” Most people heard that and thought: “Cool, AI makes me faster” Wrong. AI does not just make people faster. It changes what one person can become. A startup used to need: > researcher > designer > developer > marketer > analyst > support team > ops manager Now one AI-native person can wire all of that into workflows. > Agents that research. > Tools that write. > Workflows that test. > Automations that publish. > Memory that compounds. This is not prompt engineering. This is leverage. The next 5 years will not belong to people who write better prompts. They will belong to people who build better workflows. Watch the full interview. Bookmark this. It is one of the most important ideas of the decade.
22:54

Nobel Prize winner and Google DeepMind CEO Demis Hassabis just revealed the real AI skill gap: “The next generation will do things that used to take teams of 10, 20, 30, 50 people” Most people heard that and thought: “Cool, AI makes me faster” Wrong. AI does not just make people faster. It changes what one person can become. A startup used to need: > researcher > designer > developer > marketer > analyst > support team > ops manager Now one AI-native person can wire all of that into workflows. > Agents that research. > Tools that write. > Workflows that test. > Automations that publish. > Memory that compounds. This is not prompt engineering. This is leverage. The next 5 years will not belong to people who write better prompts. They will belong to people who build better workflows. Watch the full interview. Bookmark this. It is one of the most important ideas of the decade.

spect

131,101 просмотров • 17 дней назад

IN 1982 GRACE HOPPER WALKED INTO THE NSA AND EXPLAINED THE NEXT 40 YEARS OF COMPUTING 48 minutes from the woman who invented the compiler -- the first person who made a machine understand human words. -> The idea that lands: stop bending humans to the machine. Bend the machine to humans. She built the first compiler when the experts swore computers could only crunch numbers. She wanted you to write in plain words and let the machine handle the translation. Forty years later you barely write code at all -- you tell the model what you want in plain English and it writes it for you. The compiler was step one. The LLM is the same idea, finished. Memorizing syntax was never the skill -- saying clearly what you actually want is. This is where that idea was born. Most people think talking to your computer in plain English started in 2023. The ones who watch this know a Navy admiral called it in 1982. Bookmark & Watch it today ↓
47:50

IN 1982 GRACE HOPPER WALKED INTO THE NSA AND EXPLAINED THE NEXT 40 YEARS OF COMPUTING 48 minutes from the woman who invented the compiler -- the first person who made a machine understand human words. -> The idea that lands: stop bending humans to the machine. Bend the machine to humans. She built the first compiler when the experts swore computers could only crunch numbers. She wanted you to write in plain words and let the machine handle the translation. Forty years later you barely write code at all -- you tell the model what you want in plain English and it writes it for you. The compiler was step one. The LLM is the same idea, finished. Memorizing syntax was never the skill -- saying clearly what you actually want is. This is where that idea was born. Most people think talking to your computer in plain English started in 2023. The ones who watch this know a Navy admiral called it in 1982. Bookmark & Watch it today ↓

slash1s

60,118 просмотров • 5 дней назад

Morgan Housel will never use AI to write. To him, it defeats the whole purpose of writing. "The process of writing is what gets the author thinking. When they write a book, they didn't have all that knowledge in their head. They started out with one brave sentence, and then that taught them something. If you're using any kind of LLM to do any of the broad structure for you, you're not actually thinking. You stripped out everything that was good about writing." He'll use it for research, as a "Google on steroids." But even then he argues that the research process is different: "When you're doing the reps of research, it's gonna hit you in a different way."
1:23

Morgan Housel will never use AI to write. To him, it defeats the whole purpose of writing. "The process of writing is what gets the author thinking. When they write a book, they didn't have all that knowledge in their head. They started out with one brave sentence, and then that taught them something. If you're using any kind of LLM to do any of the broad structure for you, you're not actually thinking. You stripped out everything that was good about writing." He'll use it for research, as a "Google on steroids." But even then he argues that the research process is different: "When you're doing the reps of research, it's gonna hit you in a different way."

David Perell Clips

13,714 просмотров • 20 дней назад

Kevin Kelly is one of the most influential tech writers of the last half-century. He's published 14 books, founded Wired magazine, and maybe even traveled to more places in Asia than anybody in human history. Here are 28 of his best maxims for writing: 1. Don't aim to be the best. Be the only. 2. Don’t create things to make money; make money so you can create things. 3. The main thing is to keep the main thing the main thing. 4. Always demand a deadline. Doing so weeds out the superfluous and prevents you from insisting on perfection (which will limit you as a writer). 5. To write about something hard to explain, write a detailed letter to a friend about why it is so hard to explain, and then remove the initial “Dear Friend” part and you’ll have a great first draft. 6. The work on any worthy piece of writing is endless and infinite. Since you cannot limit the work, you must limit your hours. 7. Books are never finished, only abandoned. 8. When you are stuck, sleep on it. Give your subconscious an assignment while you sleep. You’ll have an answer in the morning or by the next time you sit down to write. 9. A multitude of bad ideas is necessary for one good idea. 10. The greatest teacher is called “doing.” 11. Efficiency is highly overrated; goofing off is highly underrated. 12. If you have a good idea, write it down. Don't assume you'll remember it. 13. Writing is not selfish; it's for the rest of us. If you don't do your thing and share your writing, you are cheating us. 14. Most articles and stories are improved significantly if you delete the first page of the manuscript. Start with the action. 15. The best way to learn anything is to teach what you know (and you can do it at scale by writing). 16. Productivity is often a distraction. Don't aim for better ways to get through your tasks as quickly as possible. Instead, look for writing projects that you never want to stop doing. 17. Occasionally your first idea is best, but usually it’s the fifth idea. You need to get all the obvious ideas out of the way. Try to surprise yourself. 18. Pay attention to what you pay attention to. 19. To be interesting just tell your own story with uncommon honesty. 20. Ironically, the best time to write a book is once you're done with the speaking tour for the book. 21. Read the books that your favorite authors once read. 22. When you find something you really enjoy, do it slowly. 23. The main reason to write something every day is that you must throw away a lot of good work to reach the great stuff. To let it all go easily you need to be convinced that there is “more where that came from.” You get that in steady production, which comes from a steady writing habit. 24. Habits are far more dependable than inspiration. Make progress by making habits. Don't focus on becoming a better writer. Focus on becoming the kind of person who never misses a writing session. 25. The quality of a piece of writing hinges on its structure. Nail the structure and the ideas will fall into place. You'll know the structure is good when the reader doesn't even notice it. 26. To write something good, just do it. To write something great, just redo it, redo it, redo it. The secret to publishing great writing is to spend a lot of time rewriting. 27. When in doubt, retreat to honesty. Say more of what you really think and feel instead of trying to sound smart. 28. Principles like what you see here are not laws. They're like a hat. If one doesn't fit, try another. Many of these maxims are directly from Kevin Kelly's book: Excellent Advice for Living, while others are from the interview I just published with him about his approach to writing. I've linked to our full conversation in the tweet below.
0:34

Kevin Kelly is one of the most influential tech writers of the last half-century. He's published 14 books, founded Wired magazine, and maybe even traveled to more places in Asia than anybody in human history. Here are 28 of his best maxims for writing: 1. Don't aim to be the best. Be the only. 2. Don’t create things to make money; make money so you can create things. 3. The main thing is to keep the main thing the main thing. 4. Always demand a deadline. Doing so weeds out the superfluous and prevents you from insisting on perfection (which will limit you as a writer). 5. To write about something hard to explain, write a detailed letter to a friend about why it is so hard to explain, and then remove the initial “Dear Friend” part and you’ll have a great first draft. 6. The work on any worthy piece of writing is endless and infinite. Since you cannot limit the work, you must limit your hours. 7. Books are never finished, only abandoned. 8. When you are stuck, sleep on it. Give your subconscious an assignment while you sleep. You’ll have an answer in the morning or by the next time you sit down to write. 9. A multitude of bad ideas is necessary for one good idea. 10. The greatest teacher is called “doing.” 11. Efficiency is highly overrated; goofing off is highly underrated. 12. If you have a good idea, write it down. Don't assume you'll remember it. 13. Writing is not selfish; it's for the rest of us. If you don't do your thing and share your writing, you are cheating us. 14. Most articles and stories are improved significantly if you delete the first page of the manuscript. Start with the action. 15. The best way to learn anything is to teach what you know (and you can do it at scale by writing). 16. Productivity is often a distraction. Don't aim for better ways to get through your tasks as quickly as possible. Instead, look for writing projects that you never want to stop doing. 17. Occasionally your first idea is best, but usually it’s the fifth idea. You need to get all the obvious ideas out of the way. Try to surprise yourself. 18. Pay attention to what you pay attention to. 19. To be interesting just tell your own story with uncommon honesty. 20. Ironically, the best time to write a book is once you're done with the speaking tour for the book. 21. Read the books that your favorite authors once read. 22. When you find something you really enjoy, do it slowly. 23. The main reason to write something every day is that you must throw away a lot of good work to reach the great stuff. To let it all go easily you need to be convinced that there is “more where that came from.” You get that in steady production, which comes from a steady writing habit. 24. Habits are far more dependable than inspiration. Make progress by making habits. Don't focus on becoming a better writer. Focus on becoming the kind of person who never misses a writing session. 25. The quality of a piece of writing hinges on its structure. Nail the structure and the ideas will fall into place. You'll know the structure is good when the reader doesn't even notice it. 26. To write something good, just do it. To write something great, just redo it, redo it, redo it. The secret to publishing great writing is to spend a lot of time rewriting. 27. When in doubt, retreat to honesty. Say more of what you really think and feel instead of trying to sound smart. 28. Principles like what you see here are not laws. They're like a hat. If one doesn't fit, try another. Many of these maxims are directly from Kevin Kelly's book: Excellent Advice for Living, while others are from the interview I just published with him about his approach to writing. I've linked to our full conversation in the tweet below.

David Perell

370,466 просмотров • 2 лет назад

Mark Zuckerberg just described the obsolescence of every institution on Earth and delivered it like a product update. Zuckerberg: “I just think in the future almost everyone is gonna have the power of a 10,000-person organization.” He did not say better tools. He did not say smarter apps. He said the full cognitive output of ten thousand human beings. Packaged into a product. Handed to one person. That is not an upgrade. That is the end of the reason human beings organize at all. Companies exist because one brain is not enough. Governments exist because coordination requires hierarchy. Universities exist because knowledge demands infrastructure. Every institution ever built was a workaround for the same limitation. No single person could do it alone. Zuckerberg is telling you that limitation is about to disappear. The 500-person startup becomes one founder and an AI stack. The law firm becomes one attorney and a system that never sleeps. The hospital becomes one doctor carrying every specialist in their pocket. That is not speculation. That is a deployment schedule. And the man writing it runs a 70,000-person company. He employs 70,000 people and just told the world one person will soon need none of them. That is not a prediction. That is a confession from the man who will be first to act on it. But the part nobody is discussing matters more. This technology does not land on everyone equally. It lands first on the people who already command 10,000-person organizations. Zuckerberg does not get the power of 10,000 people. He already has that. He gets the power of 10,000 organizations. Every revolution in history was sold as liberation. The printing press was supposed to democratize knowledge. It built media empires. The internet was supposed to democratize commerce. It built trillion-dollar platforms. The tool always arrives as liberation. It always settles as leverage. And leverage always consolidates upward. Zuckerberg is not wrong about the capability. One person will do what ten thousand once did. But the question nobody is asking is the only one that matters. If everyone wields the output of 10,000 people, what is a single person actually worth? And then Zuckerberg answered his own question without realizing it. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here?” He meant it as a case for AI. That is the most brutal thing a CEO has ever said about the people who work for him.
0:59

Mark Zuckerberg just described the obsolescence of every institution on Earth and delivered it like a product update. Zuckerberg: “I just think in the future almost everyone is gonna have the power of a 10,000-person organization.” He did not say better tools. He did not say smarter apps. He said the full cognitive output of ten thousand human beings. Packaged into a product. Handed to one person. That is not an upgrade. That is the end of the reason human beings organize at all. Companies exist because one brain is not enough. Governments exist because coordination requires hierarchy. Universities exist because knowledge demands infrastructure. Every institution ever built was a workaround for the same limitation. No single person could do it alone. Zuckerberg is telling you that limitation is about to disappear. The 500-person startup becomes one founder and an AI stack. The law firm becomes one attorney and a system that never sleeps. The hospital becomes one doctor carrying every specialist in their pocket. That is not speculation. That is a deployment schedule. And the man writing it runs a 70,000-person company. He employs 70,000 people and just told the world one person will soon need none of them. That is not a prediction. That is a confession from the man who will be first to act on it. But the part nobody is discussing matters more. This technology does not land on everyone equally. It lands first on the people who already command 10,000-person organizations. Zuckerberg does not get the power of 10,000 people. He already has that. He gets the power of 10,000 organizations. Every revolution in history was sold as liberation. The printing press was supposed to democratize knowledge. It built media empires. The internet was supposed to democratize commerce. It built trillion-dollar platforms. The tool always arrives as liberation. It always settles as leverage. And leverage always consolidates upward. Zuckerberg is not wrong about the capability. One person will do what ten thousand once did. But the question nobody is asking is the only one that matters. If everyone wields the output of 10,000 people, what is a single person actually worth? And then Zuckerberg answered his own question without realizing it. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here?” He meant it as a case for AI. That is the most brutal thing a CEO has ever said about the people who work for him.

Dustin

54,014 просмотров • 1 месяц назад