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Marc Andreessen explains why AI coding won't replace programmers, but fundamentally change what they do. He argues that AI coding is just the latest abstraction layer, and the job of a programmer has always evolved with each one. Andreessen's key reframe of what's actually happening: "AI coding actually abstracts... away the process of actually writing the scripting code... This is the next layer of the task redefinition under the job of programmer." He's clear that the best programmers aren't being replaced. They're already adapting, even if their day-to-day looks radically different now. Their job has shifted from writing code line by line to managing dozens of AI agents working in parallel. "The world's best programmers today will tell you, 'My job is I'm sitting there and I'm orchestrating 10 code bots running in parallel.' Their day job now is kind of arguing with the AI bots to try to get them to write the right code." But Marc Andreessen 🇺🇸 is adamant this doesn't make foundational knowledge obsolete — it makes it more important. "You need to still fully understand and learn how to write and understand code, because if it doesn't work or it's not doing what you expect, you need to be able to understand the results of what the AI is giving you." He draws a direct parallel: Just as someone writing scripting languages still needs to understand how a microprocessor works, someone orchestrating AI bots needs to understand the code those bots produce. "It's this upleveling of capability where you actually want the depth to go down and understand what the thing is actually doing, even if you're not spending your day doing that by hand." The result, in his view, is transformative: "Now programmers are going to be 10 times or 100 times or a thousand times more productive. And that is overwhelmingly a good thing." The pattern: New abstraction layer emerges → tasks change → the job gets redefined upward → productivity explodes It raises a question every programmer should be sitting with... Are you building the depth to evaluate what AI gives you, or just accepting the output?show more

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Marc Andreessen: "The job is not actually the atomic unit of what happens in the workplace. The atomic unit of what happens in the workplace is the task." "A job is a bundle of tasks." “Everybody wants to talk about job loss, but really what you want to look at is task loss.” "As the tasks change enough, then that’s when the jobs change." "Ten years from now, is your job title coder, or coder-designer-product manager, or is it just, ‘I build products,’ or is it just, ‘I tell the AI how to build products.’ Whatever that job is called, it’s going to be incredibly important, because the people doing that job are going to be orchestrating the AI." Marc Andreessen 🇺🇸 on Lenny's Podcast with Lenny Rachitsky

Marc Andreessen: "The job is not actually the atomic unit of what happens in the workplace. The atomic unit of what happens in the workplace is the task." "A job is a bundle of tasks." “Everybody wants to talk about job loss, but really what you want to look at is task loss.” "As the tasks change enough, then that’s when the jobs change." "Ten years from now, is your job title coder, or coder-designer-product manager, or is it just, ‘I build products,’ or is it just, ‘I tell the AI how to build products.’ Whatever that job is called, it’s going to be incredibly important, because the people doing that job are going to be orchestrating the AI." Marc Andreessen 🇺🇸 on Lenny's Podcast with Lenny Rachitsky

a16z

292,601 просмотров • 4 месяцев назад

Marc Andreessen: "The job is not actually the atomic unit of what happens in the workplace. The atomic unit of what happens in the workplace is the task." "A job is a bundle of tasks." “Everybody wants to talk about job loss, but really what you want to look at is task loss.” "As the tasks change enough, then that’s when the jobs change." "Ten years from now, is your job title coder, or coder-designer-product manager, or is it just, ‘I build products,’ or is it just, ‘I tell the AI how to build products.’ Whatever that job is called, it’s going to be incredibly important, because the people doing that job are going to be orchestrating the AI."

Marc Andreessen: "The job is not actually the atomic unit of what happens in the workplace. The atomic unit of what happens in the workplace is the task." "A job is a bundle of tasks." “Everybody wants to talk about job loss, but really what you want to look at is task loss.” "As the tasks change enough, then that’s when the jobs change." "Ten years from now, is your job title coder, or coder-designer-product manager, or is it just, ‘I build products,’ or is it just, ‘I tell the AI how to build products.’ Whatever that job is called, it’s going to be incredibly important, because the people doing that job are going to be orchestrating the AI."

Lenny Rachitsky

46,682 просмотров • 4 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.

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

82,663 просмотров • 2 месяцев назад

Programmers, PMs, and designers are in a three-way Mexican standoff. .Marc Andreessen 🇺🇸 says the new job title is "builder." "The programmers think that they don't need the product managers and the designers anymore because they can have AI do that." "Each of the other two doesn't think they need the other two either." "What I've been predicting is they're all correct." "The product manager can generate code and design now, and each of them can do the job of all three." "Now the job is builder." "It's entirely possible that we're sitting here in 10 years... the job of coder is gone, but you have this extraordinary number of builders running around."

Programmers, PMs, and designers are in a three-way Mexican standoff. .Marc Andreessen 🇺🇸 says the new job title is "builder." "The programmers think that they don't need the product managers and the designers anymore because they can have AI do that." "Each of the other two doesn't think they need the other two either." "What I've been predicting is they're all correct." "The product manager can generate code and design now, and each of them can do the job of all three." "Now the job is builder." "It's entirely possible that we're sitting here in 10 years... the job of coder is gone, but you have this extraordinary number of builders running around."

MTS

73,199 просмотров • 24 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."

"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 • 4 месяцев назад

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Santiago

64,392 просмотров • 6 месяцев назад

How will AI change writing? For clues, look at the current state of software development. Marc Andreessen says: "The new coding interface is you've got your code and a chatbot. The Copilot is reading your code and giving you real-time comments. Or the chatbot is actually writing the code for you, and then you're giving it feedback. We had this old concept in the old days called pair programming, where you'd put two coders together in front of the same keyboard, and they could talk to each other and write code together. But now you're just going to have pair programming happening much more broadly, which is human plus machine. And by the way, this hasn't happened yet, but I think the same thing will happen for every other form of writing. So I think prose writing and fiction writing and all kinds of professional authors will be working in this format where you'll have this continuous dialogue going with an AI while you're in charge of the overall product." — Marc Andreessen 🇺🇸 (Recorded in 2024)

How will AI change writing? For clues, look at the current state of software development. Marc Andreessen says: "The new coding interface is you've got your code and a chatbot. The Copilot is reading your code and giving you real-time comments. Or the chatbot is actually writing the code for you, and then you're giving it feedback. We had this old concept in the old days called pair programming, where you'd put two coders together in front of the same keyboard, and they could talk to each other and write code together. But now you're just going to have pair programming happening much more broadly, which is human plus machine. And by the way, this hasn't happened yet, but I think the same thing will happen for every other form of writing. So I think prose writing and fiction writing and all kinds of professional authors will be working in this format where you'll have this continuous dialogue going with an AI while you're in charge of the overall product." — Marc Andreessen 🇺🇸 (Recorded in 2024)

David Perell Clips

13,101 просмотров • 2 месяцев назад

We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.

We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.

Santiago

16,299 просмотров • 4 месяцев 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.

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

533,145 просмотров • 2 месяцев назад

$Marc Andreessen explains how AI turned the valley's best programmers into sleep-deprived "vampires": Marc points out a counterintuitive twist in what AI coding has done to developers. You'd expect one of two outcomes, he says. Either coders would leave the profession entirely "because there's no point anymore," or they'd simply have better lives, working a fraction of the hours now that AI makes them so productive. Neither happened. As Marc puts it: "What's actually happened is virtually to a person, they're all working more hours than ever. To the point where there is a new term of art that's used in the valley called the AI vampire...You're up all night doing AI coding because you are so productive." The reason they can't switch off is opportunity cost: "If you go to sleep, you won't be with your 20 AI coding agents keeping them working on all the projects that you have them working on. And so people stop sleeping." Marc describes friends, some of them famous, who look visibly worse than they did six months ago. Sleep-deprived, bags under their eyes, clearly not taking care of themselves. And yet "they are absolutely ecstatic because they are able to produce five times, 10 times, 20 times more code per hour than they could in the past." He shares one example, a Wall Street friend with a 35-year-old computer science degree from MIT who had long stopped coding: "He's picked up coding with AI. He's completely reanimated his entire house." AI jukebox, security cameras, robot pet dogs, smart fridges, every project he'd ever imagined. In his spare time, the friend has "generated 500,000 lines of code just by working with AI." The same thing is playing out inside companies. At leading-edge tech firms, Marc says, coders using AI are estimated to be "20 times more productive than they were before they started using AI." So what happens when code becomes that cheap to produce? Marc Andreessen 🇺🇸 points to an elasticity effect: "It turns out there's way more demand for code in the world than was ever able to be satisfied under the old economics. Every company I know has a thousand things that they've wanted to have code for that they've never been able to get to." Now they can do all of it. Companies are shipping products faster, adding features faster, moving into "turbo mode." Coding salaries have inflated to match. According to Marc, the top coders in AI now make $50 million a year, because "they've got the silver bullet. They've got the philosopher's stone." Asked whether any of this is sustainable, his answer is blunt: "Not only is this sustainable, this is going to intensify."$

Marc Andreessen explains how AI turned the valley's best programmers into sleep-deprived "vampires": Marc points out a counterintuitive twist in what AI coding has done to developers. You'd expect one of two outcomes, he says. Either coders would leave the profession entirely "because there's no point anymore," or they'd simply have better lives, working a fraction of the hours now that AI makes them so productive. Neither happened. As Marc puts it: "What's actually happened is virtually to a person, they're all working more hours than ever. To the point where there is a new term of art that's used in the valley called the AI vampire...You're up all night doing AI coding because you are so productive." The reason they can't switch off is opportunity cost: "If you go to sleep, you won't be with your 20 AI coding agents keeping them working on all the projects that you have them working on. And so people stop sleeping." Marc describes friends, some of them famous, who look visibly worse than they did six months ago. Sleep-deprived, bags under their eyes, clearly not taking care of themselves. And yet "they are absolutely ecstatic because they are able to produce five times, 10 times, 20 times more code per hour than they could in the past." He shares one example, a Wall Street friend with a 35-year-old computer science degree from MIT who had long stopped coding: "He's picked up coding with AI. He's completely reanimated his entire house." AI jukebox, security cameras, robot pet dogs, smart fridges, every project he'd ever imagined. In his spare time, the friend has "generated 500,000 lines of code just by working with AI." The same thing is playing out inside companies. At leading-edge tech firms, Marc says, coders using AI are estimated to be "20 times more productive than they were before they started using AI." So what happens when code becomes that cheap to produce? Marc Andreessen 🇺🇸 points to an elasticity effect: "It turns out there's way more demand for code in the world than was ever able to be satisfied under the old economics. Every company I know has a thousand things that they've wanted to have code for that they've never been able to get to." Now they can do all of it. Companies are shipping products faster, adding features faster, moving into "turbo mode." Coding salaries have inflated to match. According to Marc, the top coders in AI now make $50 million a year, because "they've got the silver bullet. They've got the philosopher's stone." Asked whether any of this is sustainable, his answer is blunt: "Not only is this sustainable, this is going to intensify."

Big Brain AI

19,192 просмотров • 3 дней назад

.Scott Wu to Joe Lonsdale on why Cognition uses AI in job interviews: "One or two years ago, people had this mentality of 'How do we make sure people aren't using AI while we're interviewing them?' And I think that has totally flipped. Honestly, I think that was wrong... If you're asking the question of like, how do we evaluate people on exactly the thing that AI can already do, that seems kind of the wrong. Our interview process has always been... you can use as much AI as you want to use. We're going to give you a few hours. Just build your whole own product surface. A lot of these are projects that, frankly, is like, if you were trying to do this by hand, you would not be able to get done in a few hours. So you kind of have to use AI for this. But in reality, what we actually want to test is, in addition to how familiar you are with these tools, what we actually want to test is, what do you think is the right thing to build? Or how do you make these product decisions? How do you make these trade-offs? How do you decide or collect information about what you should be doing?"

.Scott Wu to Joe Lonsdale on why Cognition uses AI in job interviews: "One or two years ago, people had this mentality of 'How do we make sure people aren't using AI while we're interviewing them?' And I think that has totally flipped. Honestly, I think that was wrong... If you're asking the question of like, how do we evaluate people on exactly the thing that AI can already do, that seems kind of the wrong. Our interview process has always been... you can use as much AI as you want to use. We're going to give you a few hours. Just build your whole own product surface. A lot of these are projects that, frankly, is like, if you were trying to do this by hand, you would not be able to get done in a few hours. So you kind of have to use AI for this. But in reality, what we actually want to test is, in addition to how familiar you are with these tools, what we actually want to test is, what do you think is the right thing to build? Or how do you make these product decisions? How do you make these trade-offs? How do you decide or collect information about what you should be doing?"

American Optimist

13,182 просмотров • 2 месяцев назад

Marc Andreessen just coined a term that perfectly describes what's actually happening to programmers right now and it's the opposite of what the doomers predicted (Save this). He calls them AI vampires. Andreessen's says that programmers using Codex, Claude Code and AI coding tools are not being replaced but they're working harder than ever, sleeping less than ever, with massive bags under their eyes and they are completely euphoric. What's remarkable is that the phenomenon extends far beyond professional engineers. Andreessen described an a16z partner who had never written a single line of code in his career, who built an entire AI powered work system for himself and when asked if he'd ever looked at the underlying code, the answer was simply "hell no." The data behind the anecdote is extraordinary. Andreessen says the leading-edge programmers at a16z portfolio companies are now 20x more productive than they were a year ago, the most dramatic increase in programmer productivity in the history of the industry. The METR May 2026 AI usage survey found technical workers self reporting a 1.4–2x change in work value from AI tools, with 75% of software engineers using AI for at least half their work. The software engineer hiring rate is actually increasing up to 22.77% of new hires in 2025 from 19.32% in late 2023 and companies are now bidding more aggressively for senior engineers specifically because AI empowered engineers have a higher ROI than ever before. The US economy added 115,000 jobs in April 2026 alone, beating the 62,000 consensus forecast precisely as AI adoption hit its highest level on record. This is exactly what basic economics predicts and what almost no one who writes about AI and jobs bothers to say. Classic marginal productivity theory says: when you increase the productivity of a worker, you don't diminish human work, you expand it. The worker becomes more productive, gets paid more, does more, and more jobs are created in the process. Andreessen's ATM analogy holds here because ATMs were supposed to eliminate bank tellers but instead, teller employment rose because lower operating costs let banks open more branches. The no-code AI market has exploded from $4.3 billion in 2023 to $21.2 billion in 2026 not because programmers are being replaced, but because the universe of people who can now build software has expanded by orders of magnitude. The blind spot, as Andreessen notes, is that productivity is now outrunning comprehension. The a16z partner building AI systems he's never looked at the code for represents something genuinely new, software being summoned faster than it can be understood. That's not necessarily dangerous but it does mean the verification, security, and governance layer of the AI development stack is more important now than it has ever been.

Marc Andreessen just coined a term that perfectly describes what's actually happening to programmers right now and it's the opposite of what the doomers predicted (Save this). He calls them AI vampires. Andreessen's says that programmers using Codex, Claude Code and AI coding tools are not being replaced but they're working harder than ever, sleeping less than ever, with massive bags under their eyes and they are completely euphoric. What's remarkable is that the phenomenon extends far beyond professional engineers. Andreessen described an a16z partner who had never written a single line of code in his career, who built an entire AI powered work system for himself and when asked if he'd ever looked at the underlying code, the answer was simply "hell no." The data behind the anecdote is extraordinary. Andreessen says the leading-edge programmers at a16z portfolio companies are now 20x more productive than they were a year ago, the most dramatic increase in programmer productivity in the history of the industry. The METR May 2026 AI usage survey found technical workers self reporting a 1.4–2x change in work value from AI tools, with 75% of software engineers using AI for at least half their work. The software engineer hiring rate is actually increasing up to 22.77% of new hires in 2025 from 19.32% in late 2023 and companies are now bidding more aggressively for senior engineers specifically because AI empowered engineers have a higher ROI than ever before. The US economy added 115,000 jobs in April 2026 alone, beating the 62,000 consensus forecast precisely as AI adoption hit its highest level on record. This is exactly what basic economics predicts and what almost no one who writes about AI and jobs bothers to say. Classic marginal productivity theory says: when you increase the productivity of a worker, you don't diminish human work, you expand it. The worker becomes more productive, gets paid more, does more, and more jobs are created in the process. Andreessen's ATM analogy holds here because ATMs were supposed to eliminate bank tellers but instead, teller employment rose because lower operating costs let banks open more branches. The no-code AI market has exploded from $4.3 billion in 2023 to $21.2 billion in 2026 not because programmers are being replaced, but because the universe of people who can now build software has expanded by orders of magnitude. The blind spot, as Andreessen notes, is that productivity is now outrunning comprehension. The a16z partner building AI systems he's never looked at the code for represents something genuinely new, software being summoned faster than it can be understood. That's not necessarily dangerous but it does mean the verification, security, and governance layer of the AI development stack is more important now than it has ever been.

Milk Road AI

136,646 просмотров • 23 дней назад

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

Andrew Ng

1,223,336 просмотров • 1 год назад

Zapier CEO Wade Foster says individuals have become more productive with AI tools, but that it's not clear if companies as a whole are also becoming more productive: "Across Zapier, 100% of our employees are using AI daily. People are individually more productive. But if you were to ask me, 'Is the company more productive, institutionally are we more productive?' It's a lot harder to say yes to that." "This feels like the next thing that everybody's working on: How do we actually accelerate the institution? This gets harder because you actually have to rethink how the company works." "To give you an example, we've gone from a world where code was expensive to now code is cheap. In the world where code was expensive, you had all these processes upfront to talk to customers, to align on roadmaps, to figure out what the right thing to build was, because if you chose the wrong thing, that was a really expensive mistake." "But when code is cheap, you can get rid of all that stuff. And that takes redesigning jobs or rethinking the human where the human actually exists in the first place."

Zapier CEO Wade Foster says individuals have become more productive with AI tools, but that it's not clear if companies as a whole are also becoming more productive: "Across Zapier, 100% of our employees are using AI daily. People are individually more productive. But if you were to ask me, 'Is the company more productive, institutionally are we more productive?' It's a lot harder to say yes to that." "This feels like the next thing that everybody's working on: How do we actually accelerate the institution? This gets harder because you actually have to rethink how the company works." "To give you an example, we've gone from a world where code was expensive to now code is cheap. In the world where code was expensive, you had all these processes upfront to talk to customers, to align on roadmaps, to figure out what the right thing to build was, because if you chose the wrong thing, that was a really expensive mistake." "But when code is cheap, you can get rid of all that stuff. And that takes redesigning jobs or rethinking the human where the human actually exists in the first place."

TBPN

15,294 просмотров • 1 месяц назад

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

Santiago

296,299 просмотров • 8 месяцев назад

Naval on how to get a job in 2025: Learn how to use AI Naval on E215: "The fastest way to help somebody get a job right now: the best thing you can do is say, 'Hey, go download the AI tools and just start talking to them. Just start using them in any way.'" "And then you can walk into any employer in almost any field and say, 'Hey, I understand AI.' And they'll hire you on the spot." "AI is a productivity tool. It increases the productivity of a worker. It allows them to do more creative work and less repetitive work. As such, it makes them more valuable." "Yes, there is some retraining involved, but not a lot. These are natural language computers. You can talk to them in plain English, and they talk back to you in plain English." "I think we will see job creation by AI that will be as fast or faster than job destruction." "You saw this even with the internet. Like, YouTube came along. Look at all these YouTube streamers and influencers. That didn't used to be a job." "Go brush up on your AI. Learn a little bit. Watch a few videos. Use the AI." "Tinker with it and then go reapply for that job that rejected you, and watch how they pull you in."

Naval on how to get a job in 2025: Learn how to use AI Naval on E215: "The fastest way to help somebody get a job right now: the best thing you can do is say, 'Hey, go download the AI tools and just start talking to them. Just start using them in any way.'" "And then you can walk into any employer in almost any field and say, 'Hey, I understand AI.' And they'll hire you on the spot." "AI is a productivity tool. It increases the productivity of a worker. It allows them to do more creative work and less repetitive work. As such, it makes them more valuable." "Yes, there is some retraining involved, but not a lot. These are natural language computers. You can talk to them in plain English, and they talk back to you in plain English." "I think we will see job creation by AI that will be as fast or faster than job destruction." "You saw this even with the internet. Like, YouTube came along. Look at all these YouTube streamers and influencers. That didn't used to be a job." "Go brush up on your AI. Learn a little bit. Watch a few videos. Use the AI." "Tinker with it and then go reapply for that job that rejected you, and watch how they pull you in."

The All-In Podcast

164,011 просмотров • 1 год назад

"To build a great company, you need to write code and talk to users." - Florian Juengermann (co-founder of Listen Labs) "AI agents can now write code, so what becomes important is building the right thing and having the right feedback." "That's what we are building: telling the AI what to do, what to build, and being the tastemaker."

"To build a great company, you need to write code and talk to users." - Florian Juengermann (co-founder of Listen Labs) "AI agents can now write code, so what becomes important is building the right thing and having the right feedback." "That's what we are building: telling the AI what to do, what to build, and being the tastemaker."

TBPN

15,221 просмотров • 1 год назад

Marc Andreessen says in the future, we may not have programming languages or even user interfaces: "I kind of think that in 10 years, I'm not sure there will even be a salient concept of a programming language in the way that we understand it today." "If you project forward, you have to think forward to a world in which it's just—I'm going to tell the thing what I need, and it's going to do it in whatever way is most optimal." Marc Andreessen 🇺🇸 with Latent.Space

Marc Andreessen says in the future, we may not have programming languages or even user interfaces: "I kind of think that in 10 years, I'm not sure there will even be a salient concept of a programming language in the way that we understand it today." "If you project forward, you have to think forward to a world in which it's just—I'm going to tell the thing what I need, and it's going to do it in whatever way is most optimal." Marc Andreessen 🇺🇸 with Latent.Space

a16z

65,480 просмотров • 2 месяцев назад

DAVID SACKS: “I understand that there is a lot of concern about [AI] job disruption or job loss. That's not what we're seeing in the data so far. What we're actually seeing is job creation … We have a 4% GDP growth number right now, and half of that is attributable to AI.”

DAVID SACKS: “I understand that there is a lot of concern about [AI] job disruption or job loss. That's not what we're seeing in the data so far. What we're actually seeing is job creation … We have a 4% GDP growth number right now, and half of that is attributable to AI.”

Chief Nerd

206,067 просмотров • 5 месяцев назад

.Marc Andreessen 🇺🇸 to Jack Altman: U.S.-China AI Race Mirrors Cold War with Soviet Union "There is a two-horse race. This is shaping up to be the equivalent of what the Cold War was against the Soviet Union in the last century. It is shaping up to be like that. China does have ambitions to basically imprint the world on their ideas of how society should be organized, how the world should be run, and they obviously intend to fully proliferate their technology, which they're doing in many areas. The world, 50 years from now, 20 years from now, is going to be running on Chinese AI or American AI. Those are your choices. AI is going to be the control layer for everything. My view is AI is going to be how you interface with the education system, with the healthcare system, with transportation, with employment, with the government, with law. It's going to be AI lawyers, AI doctors, AI teachers. Do you want your AI teacher, you want your kids to be taught by Chinese AI? Really, like Marx? They're really good at teaching you Marxism and Xi Jinping thought. Another way to put it is the culture in the weights, and so, like, how these things are trained and who they're trained by really, really deeply matters. By the way, this is already an issue in lots of countries because number one, they may not want Chinese AI, but number two, do they want super woke Northern California AI? There are big questions on this. If you had a choice between AI with American values versus the Chinese Communist Party values. It's just crystal clear where you'd want to go. By the way, there's also going to be a direct military, a direct military version, a national security version of this, which is, okay, do you want to live in a world of all CCP-controlled robots and drones and airplanes and cars?"

.Marc Andreessen 🇺🇸 to Jack Altman: U.S.-China AI Race Mirrors Cold War with Soviet Union "There is a two-horse race. This is shaping up to be the equivalent of what the Cold War was against the Soviet Union in the last century. It is shaping up to be like that. China does have ambitions to basically imprint the world on their ideas of how society should be organized, how the world should be run, and they obviously intend to fully proliferate their technology, which they're doing in many areas. The world, 50 years from now, 20 years from now, is going to be running on Chinese AI or American AI. Those are your choices. AI is going to be the control layer for everything. My view is AI is going to be how you interface with the education system, with the healthcare system, with transportation, with employment, with the government, with law. It's going to be AI lawyers, AI doctors, AI teachers. Do you want your AI teacher, you want your kids to be taught by Chinese AI? Really, like Marx? They're really good at teaching you Marxism and Xi Jinping thought. Another way to put it is the culture in the weights, and so, like, how these things are trained and who they're trained by really, really deeply matters. By the way, this is already an issue in lots of countries because number one, they may not want Chinese AI, but number two, do they want super woke Northern California AI? There are big questions on this. If you had a choice between AI with American values versus the Chinese Communist Party values. It's just crystal clear where you'd want to go. By the way, there's also going to be a direct military, a direct military version, a national security version of this, which is, okay, do you want to live in a world of all CCP-controlled robots and drones and airplanes and cars?"

Josh Caplan

14,531 просмотров • 11 месяцев назад