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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... a class has two methods and one is init, you meant to write a function. Most people add structure to feel like real engineers. It just adds weight no one ever needed. Writing more code was never the skill -> writing less of it is. And when an AI agent happily generates ten classes for a job that needed three lines, the person who knows what to delete is the one who ships something clean. Anyone can add abstraction. Knowing when not to is the whole job. Bookmark it and Watch ↓show more

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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 ↓

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 views • 2 months ago

MIT GAVE DEBUGGING ITS OWN FULL LECTURE -- BECAUSE MOST DEVS STILL HUNT BUGS WITH PRINT STATEMENTS LIKE IT'S 1995 54 minutes that take the thing you do every single day, badly, and show you the tools schools never bothered to teach. -> The moment it lands, you realize "add a print, run it, add another print" was never debugging. It was guessing with extra steps. Most people never learned the real toolkit. A proper debugger, breakpoints, tracing what the program actually does instead of what you assume it does. In 2026 guessing isn't good enough -> the bug is buried in code you didn't even write, and printf won't find it for you. An AI agent will generate hundreds of lines in seconds. When one of them quietly breaks, finding it runs on exactly the skills in this lecture. Anyone can add a print statement. The person who can actually trace a bug to its source is the one who ships while everyone else guesses. Bookmark & Watch it ↓

MIT GAVE DEBUGGING ITS OWN FULL LECTURE -- BECAUSE MOST DEVS STILL HUNT BUGS WITH PRINT STATEMENTS LIKE IT'S 1995 54 minutes that take the thing you do every single day, badly, and show you the tools schools never bothered to teach. -> The moment it lands, you realize "add a print, run it, add another print" was never debugging. It was guessing with extra steps. Most people never learned the real toolkit. A proper debugger, breakpoints, tracing what the program actually does instead of what you assume it does. In 2026 guessing isn't good enough -> the bug is buried in code you didn't even write, and printf won't find it for you. An AI agent will generate hundreds of lines in seconds. When one of them quietly breaks, finding it runs on exactly the skills in this lecture. Anyone can add a print statement. The person who can actually trace a bug to its source is the one who ships while everyone else guesses. Bookmark & Watch it ↓

slash1s

10,864 views • 2 months ago

A DEVELOPER WHO HELPS MAINTAIN GIT ITSELF PROVED THAT USING GIT AND CONTRIBUTING WITH GIT ARE TWO DIFFERENT SKILLS AND ALMOST NO ONE LEARNS THE SECOND 55 minutes from Johannes Schindelin, one of git's most prolific contributors, on the workflow that gets your code accepted into a project you don't own. -> The moment it lands, committing to your own repo turns out to be the easy 10%. Landing a change in someone else's codebase is the part nobody taught you. Most people can save their own work. Far fewer can revise a patch five times, keep the history clean, and merge it into a project moving under them. Saving your code was never the skill -> getting it merged into someone else's is. And when an AI agent fires off a pull request nobody asked for, the person who knows how to really contribute is the one who gets it accepted instead of closed. Anyone can commit to their own repo. The person who can land a change in a project they don't own is the one who actually ships. Bookmark & Watch it today ↓

A DEVELOPER WHO HELPS MAINTAIN GIT ITSELF PROVED THAT USING GIT AND CONTRIBUTING WITH GIT ARE TWO DIFFERENT SKILLS AND ALMOST NO ONE LEARNS THE SECOND 55 minutes from Johannes Schindelin, one of git's most prolific contributors, on the workflow that gets your code accepted into a project you don't own. -> The moment it lands, committing to your own repo turns out to be the easy 10%. Landing a change in someone else's codebase is the part nobody taught you. Most people can save their own work. Far fewer can revise a patch five times, keep the history clean, and merge it into a project moving under them. Saving your code was never the skill -> getting it merged into someone else's is. And when an AI agent fires off a pull request nobody asked for, the person who knows how to really contribute is the one who gets it accepted instead of closed. Anyone can commit to their own repo. The person who can land a change in a project they don't own is the one who actually ships. Bookmark & Watch it today ↓

slash1s

12,750 views • 2 months ago

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.

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

318,457 views • 5 months ago

IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓

slash1s

22,107 views • 1 month ago

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 ↓

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

191,595 views • 2 months ago

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 ↓

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

384,696 views • 2 months ago

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 ↓

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

37,773 views • 2 months ago

"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."

"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 views • 6 months ago

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.

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

82,757 views • 5 months ago

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 ↓

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

237,718 views • 2 months ago

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.

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 views • 2 months ago

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.

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

535,877 views • 5 months ago

A DEVELOPER FOUND SEVEN WAYS TO TAKE DOWN A PRODUCTION DATABASE THAT ALL LOOK EXACTLY LIKE NORMAL, INNOCENT CODE AND ALMOST EVERY TEAM IS SHIPPING AT LEAST ONE OF THEM RIGHT NOW 17 minutes from Josh Berkus, one of the people who actually maintains PostgreSQL, walking through the quiet mistakes that turn a healthy database into a 3am outage. -> The moment it lands, you realize none of these are exotic attacks. They're ordinary-looking decisions -- a query that locks a table, a connection that never closes, a setting no one ever questioned -- that work perfectly until the day they don't, and then they take everything down with them. The scary part isn't that the database breaks. It's how normal the code looks right up until it does. A query that runs in 5ms on your laptop and 5 minutes on prod. A migration that silently locks the whole table. A connection pool that runs dry the moment real traffic shows up. Every one of them passed review. Writing SQL that runs was never the hard part -> writing SQL that survives production is. And now that an AI agent is generating and firing queries at your real database faster than anyone can read them, every one of those seven landmines is one autocomplete away -- and the only person who can stop it is the one who already knows where they're buried. Your database doesn't go down because someone attacked it. It goes down because something that looked completely normal finally caught up with it. Save and Watch it today. You'll see the next outage coming before it lands ↓

A DEVELOPER FOUND SEVEN WAYS TO TAKE DOWN A PRODUCTION DATABASE THAT ALL LOOK EXACTLY LIKE NORMAL, INNOCENT CODE AND ALMOST EVERY TEAM IS SHIPPING AT LEAST ONE OF THEM RIGHT NOW 17 minutes from Josh Berkus, one of the people who actually maintains PostgreSQL, walking through the quiet mistakes that turn a healthy database into a 3am outage. -> The moment it lands, you realize none of these are exotic attacks. They're ordinary-looking decisions -- a query that locks a table, a connection that never closes, a setting no one ever questioned -- that work perfectly until the day they don't, and then they take everything down with them. The scary part isn't that the database breaks. It's how normal the code looks right up until it does. A query that runs in 5ms on your laptop and 5 minutes on prod. A migration that silently locks the whole table. A connection pool that runs dry the moment real traffic shows up. Every one of them passed review. Writing SQL that runs was never the hard part -> writing SQL that survives production is. And now that an AI agent is generating and firing queries at your real database faster than anyone can read them, every one of those seven landmines is one autocomplete away -- and the only person who can stop it is the one who already knows where they're buried. Your database doesn't go down because someone attacked it. It goes down because something that looked completely normal finally caught up with it. Save and Watch it today. You'll see the next outage coming before it lands ↓

slash1s

22,268 views • 2 months ago

Elon Musk just said what every government on earth already knows and none will admit. Musk: “AI is moving 10 times faster than government, maybe more.” Not slightly faster. Ten times. And the gap compounds daily. Every institution ever built runs on the same architecture. Committees. Hearings. Drafts. Amendments. Votes. A process designed for a world that moved at the speed of human debate. That world is gone. The moment legislation is signed, the thing it was written for is already three generations obsolete. Law is becoming a monument to things that no longer exist by the time the ink is dry. Musk: “The one thing that the government can do is just issue people money.” The largest militaries ever assembled. The most sophisticated legal infrastructure in human history. The accumulated weight of ten thousand years of institutional evolution. Collapsed to a single remaining function. Printing checks. Not because they failed. Because the velocity of what is coming makes everything else they were built to do ornamental. Musk: “Nobody’s gonna starve is what I’m saying.” The floor rises. Survival becomes automatic. Nobody goes hungry. For ten thousand years, that would have been the finish line. It is not. It is the starting line of the hardest question the species has ever faced. Every civilization in history was organized around one brutal fact. The world needed your labor to function. You worked because you had to. You built because the alternative was death. Every economy, every identity, every reason to get out of bed was downstream of that single pressure. That pressure is being quietly removed. And what it leaves behind is not freedom. It is a vacuum. A check hits your account. Rent is covered. Food is handled. The base layer of existence is solved. But the thing that organized your time. Gave your effort weight. Made your life feel like it pointed somewhere. Gone. No government can legislate that back. No policy can manufacture it. Purpose is not a deposit. Identity is not a program. What you are for when the world no longer needs you to function is not a problem any institution was designed to answer. It is the first problem in history that belongs entirely to you. And while the rest of the world debates how to control what is coming, one person is doing the only thing that has ever mattered. Building what comes next.

Elon Musk just said what every government on earth already knows and none will admit. Musk: “AI is moving 10 times faster than government, maybe more.” Not slightly faster. Ten times. And the gap compounds daily. Every institution ever built runs on the same architecture. Committees. Hearings. Drafts. Amendments. Votes. A process designed for a world that moved at the speed of human debate. That world is gone. The moment legislation is signed, the thing it was written for is already three generations obsolete. Law is becoming a monument to things that no longer exist by the time the ink is dry. Musk: “The one thing that the government can do is just issue people money.” The largest militaries ever assembled. The most sophisticated legal infrastructure in human history. The accumulated weight of ten thousand years of institutional evolution. Collapsed to a single remaining function. Printing checks. Not because they failed. Because the velocity of what is coming makes everything else they were built to do ornamental. Musk: “Nobody’s gonna starve is what I’m saying.” The floor rises. Survival becomes automatic. Nobody goes hungry. For ten thousand years, that would have been the finish line. It is not. It is the starting line of the hardest question the species has ever faced. Every civilization in history was organized around one brutal fact. The world needed your labor to function. You worked because you had to. You built because the alternative was death. Every economy, every identity, every reason to get out of bed was downstream of that single pressure. That pressure is being quietly removed. And what it leaves behind is not freedom. It is a vacuum. A check hits your account. Rent is covered. Food is handled. The base layer of existence is solved. But the thing that organized your time. Gave your effort weight. Made your life feel like it pointed somewhere. Gone. No government can legislate that back. No policy can manufacture it. Purpose is not a deposit. Identity is not a program. What you are for when the world no longer needs you to function is not a problem any institution was designed to answer. It is the first problem in history that belongs entirely to you. And while the rest of the world debates how to control what is coming, one person is doing the only thing that has ever mattered. Building what comes next.

Dustin

50,518 views • 1 month ago

THE ENGINE DIRECTOR BEHIND AAA CONSOLE GAMES WALKED ON STAGE AT A C++ CONFERENCE AND TOLD A ROOM OF EXPERTS THAT THE CLEAN, OBJECT ORIENTED CODE THEY ARE PROUD OF IS A LIE AND IT QUIETLY THROWS AWAY 90% OF THE MACHINE THEY PAID FOR 85 minutes from Mike Acton -- engine director at Insomniac Games, where wasting cycles is not an abstract debate, it is the difference between a game that ships and one that dies. -> His first principle is blunt: the only purpose of any program is to transform data. Not to model the world in pretty classes. Move data, fast. 06:33 -- The lie he calls out: "Software is the platform". No. The hardware is the platform. Ignore it and you cannot even reason about the cost of your own code. Most devs never look at what the CPU actually does. They stack abstractions until the machine spends its life waiting on memory it should never have touched. 49:38 -- He prints a value, zips it, and measures the waste directly. A brutal little trick that exposes how much of your data is pure noise. And this is the AI era's blind spot too. Agents generate more abstract code faster, on hardware nobody profiles, while the GPU bill quietly explodes. You thought clean code was the goal. This is the man shipping real engines saying the machine is the goal, and clean code is often how you lose it. Bookmark it & you'll never look at your own abstractions the same ↓

THE ENGINE DIRECTOR BEHIND AAA CONSOLE GAMES WALKED ON STAGE AT A C++ CONFERENCE AND TOLD A ROOM OF EXPERTS THAT THE CLEAN, OBJECT ORIENTED CODE THEY ARE PROUD OF IS A LIE AND IT QUIETLY THROWS AWAY 90% OF THE MACHINE THEY PAID FOR 85 minutes from Mike Acton -- engine director at Insomniac Games, where wasting cycles is not an abstract debate, it is the difference between a game that ships and one that dies. -> His first principle is blunt: the only purpose of any program is to transform data. Not to model the world in pretty classes. Move data, fast. 06:33 -- The lie he calls out: "Software is the platform". No. The hardware is the platform. Ignore it and you cannot even reason about the cost of your own code. Most devs never look at what the CPU actually does. They stack abstractions until the machine spends its life waiting on memory it should never have touched. 49:38 -- He prints a value, zips it, and measures the waste directly. A brutal little trick that exposes how much of your data is pure noise. And this is the AI era's blind spot too. Agents generate more abstract code faster, on hardware nobody profiles, while the GPU bill quietly explodes. You thought clean code was the goal. This is the man shipping real engines saying the machine is the goal, and clean code is often how you lose it. Bookmark it & you'll never look at your own abstractions the same ↓

slash1s

172,488 views • 1 month ago

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.

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

52,882 views • 4 months ago

This is the dream of anyone who has ever tested a website. Writing automated tests for a UI is one of the hardest things ever. Here is how to write and run tests for your web pages 100x faster (it also supports iOS and Android apps).

This is the dream of anyone who has ever tested a website. Writing automated tests for a UI is one of the hardest things ever. Here is how to write and run tests for your web pages 100x faster (it also supports iOS and Android apps).

Santiago

31,529 views • 22 days ago

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.

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 views • 4 months ago

"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.

"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

390,682 views • 3 years ago