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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...

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Big Brain AI

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20,221 просмотров • 10 дней назад •via X (Twitter)

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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?
1:50

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?

Big Brain AI

45,187 просмотров • 3 месяцев назад

Marc Andreessen on the imperative of speed in AI adoption: "Both the AI utopians and the AI doomers are far too optimistic." "They believe that because the technology makes something possible, 8 billion people all of a sudden are going to change how they behave. It's like—no. So much of how the existing economy works is just wired in." "We're going to be lucky as a society if AI adoption happens quickly. Because if it doesn't, what we're going to have is stagnation." Marc Andreessen 🇺🇸 with Latent.Space
0:24

Marc Andreessen on the imperative of speed in AI adoption: "Both the AI utopians and the AI doomers are far too optimistic." "They believe that because the technology makes something possible, 8 billion people all of a sudden are going to change how they behave. It's like—no. So much of how the existing economy works is just wired in." "We're going to be lucky as a society if AI adoption happens quickly. Because if it doesn't, what we're going to have is stagnation." Marc Andreessen 🇺🇸 with Latent.Space

a16z

70,412 просмотров • 2 месяцев назад

📁 Marc Andreessen, co-founder of Andreessen Horowitz, says AI coding is not replacing programmers; it is turning them into “AI vampires”. Who work more, sleep less, and produce far more. The blind spot is that productivity is now outrunning comprehension. At scale, software becomes something people summon faster than they can understand or control.
2:28

📁 Marc Andreessen, co-founder of Andreessen Horowitz, says AI coding is not replacing programmers; it is turning them into “AI vampires”. Who work more, sleep less, and produce far more. The blind spot is that productivity is now outrunning comprehension. At scale, software becomes something people summon faster than they can understand or control.

Jon Hernandez

35,234 просмотров • 1 месяц 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.
2:28

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 • 29 дней назад

Marc Andreessen says AI is hyper democratizing. “Is the future of the world going to be one or a small number of companies, or for that matter, governments or super AIs that kind of own and control everything?” “Or is this a technology that's going to diffuse out and be in everybody's hands?” “This is the time in which AI is actually hyper democratizing. It has spread to more individuals, both in the country and around the world in the shortest period of time of any new technology I think in history.” “The best AIs in the world are in the consumer products.” “This technology is going to be in everybody's hands. And everybody is going to be able to use it to optimize the things that they do, have it be a thought partner, assistant for building companies.” Marc Andreessen 🇺🇸
1:34

Marc Andreessen says AI is hyper democratizing. “Is the future of the world going to be one or a small number of companies, or for that matter, governments or super AIs that kind of own and control everything?” “Or is this a technology that's going to diffuse out and be in everybody's hands?” “This is the time in which AI is actually hyper democratizing. It has spread to more individuals, both in the country and around the world in the shortest period of time of any new technology I think in history.” “The best AIs in the world are in the consumer products.” “This technology is going to be in everybody's hands. And everybody is going to be able to use it to optimize the things that they do, have it be a thought partner, assistant for building companies.” Marc Andreessen 🇺🇸

a16z

79,935 просмотров • 7 месяцев назад

Marc Andreessen on why companies are cutting headcount, and why AI is taking the blame for something it didn't cause: "Why are we seeing layoffs every year? Why is every CEO I'm meeting saying, 'Oh, we're flat headcount or we're reducing.'" His answer points straight to interest rates. "Every big company had to replan all of their financials. All their cost of capital went up five points." When rates spiked, companies were forced to rethink everything. That cracked open a deeper problem: the hiring binge of the COVID era. "What you have happening right now is you have essentially every large company that is overstaffed." So why is AI taking the heat? Marc Andreessen 🇺🇸 is blunt: "They all have the silver bullet excuse, right? Ah, it's AI." But the timeline doesn't hold up. Marc makes it clear the numbers simply don't support that story: "AI, until literally December, was not actually good enough to do any of the jobs that they're actually cutting. So it just can't have been AI." The same logic applies to new graduates struggling to land work. People are quick to point at automation, but Marc sees two more grounded explanations. First, the over-hiring hangover: companies that ballooned headcount during COVID are now pulling back hard and not bringing new hires in on top of that. Second, a harder conversation about skills. Marc puts it plainly: "Maybe the skill set of a lot of college graduates over the last decade doesn't necessarily match to the job market. That's a very uncomfortable conversation. But if you talk to any employer, they'll immediately tell you that." The real story is simpler than people think. Companies overspent when money was cheap, overhired during COVID, and now the skills coming out of universities don't match what the job market needs.
1:09

Marc Andreessen on why companies are cutting headcount, and why AI is taking the blame for something it didn't cause: "Why are we seeing layoffs every year? Why is every CEO I'm meeting saying, 'Oh, we're flat headcount or we're reducing.'" His answer points straight to interest rates. "Every big company had to replan all of their financials. All their cost of capital went up five points." When rates spiked, companies were forced to rethink everything. That cracked open a deeper problem: the hiring binge of the COVID era. "What you have happening right now is you have essentially every large company that is overstaffed." So why is AI taking the heat? Marc Andreessen 🇺🇸 is blunt: "They all have the silver bullet excuse, right? Ah, it's AI." But the timeline doesn't hold up. Marc makes it clear the numbers simply don't support that story: "AI, until literally December, was not actually good enough to do any of the jobs that they're actually cutting. So it just can't have been AI." The same logic applies to new graduates struggling to land work. People are quick to point at automation, but Marc sees two more grounded explanations. First, the over-hiring hangover: companies that ballooned headcount during COVID are now pulling back hard and not bringing new hires in on top of that. Second, a harder conversation about skills. Marc puts it plainly: "Maybe the skill set of a lot of college graduates over the last decade doesn't necessarily match to the job market. That's a very uncomfortable conversation. But if you talk to any employer, they'll immediately tell you that." The real story is simpler than people think. Companies overspent when money was cheap, overhired during COVID, and now the skills coming out of universities don't match what the job market needs.

Big Brain AI

22,681 просмотров • 1 месяц 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)
0:53

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

Jensen Huang just said the most dangerous thing about AI that no one is sitting with. Huang: “AI basically does most of our coding. And yet we’re hiring more engineers than ever. We have more challenges than ever. We have bigger dreams than ever.” Every engineer at NVIDIA uses AI. AI writes most of their code. This is the company building the infrastructure behind every major AI system on Earth. Closer to this technology than any organization alive. They’re hiring more people. Not fewer. Every conversation about AI is built around subtraction. Fewer jobs. Fewer workers. Fewer humans in the loop. Jensen just told you the opposite is true. Huang: “Suppose we infused AI into this country, and as a result of that, we are doing things faster than ever before. Our ambition is greater than ever before. Our expectations are greater than ever before. How is that a bad condition for our country?” He’s not defending AI. He’s describing what happens inside the organizations that actually use it. It doesn’t make them leaner. It makes them hungrier. More ambition. More speed. More appetite for problems no one would have touched five years ago. The car didn’t make humans travel less. The internet didn’t make humans communicate less. No tool in human history has ever made humans want less. AI will not be the exception. Huang: “Prior to that, it’s been incredible but not useful. Now it’s useful and incredible.” Six months. That’s how fast AI crossed from impressive demo to daily weapon. The companies that adopted it didn’t shrink. They expanded. Compressed timelines. Started chasing problems they never would have attempted. The companies that ignored it stayed exactly where they were. That gap compounds. Every day a company uses AI to move faster, it learns something the one standing still never will. That knowledge stacks. That speed stacks. That ambition stacks. Jensen isn’t warning about a future where machines take your job. He’s describing a present where the companies using AI are becoming so fast and so hungry that standing still is already fatal. By the time you notice, it’s over. You were never going to be replaced by AI. You were going to be erased by someone it made hungrier than you.
1:23

Jensen Huang just said the most dangerous thing about AI that no one is sitting with. Huang: “AI basically does most of our coding. And yet we’re hiring more engineers than ever. We have more challenges than ever. We have bigger dreams than ever.” Every engineer at NVIDIA uses AI. AI writes most of their code. This is the company building the infrastructure behind every major AI system on Earth. Closer to this technology than any organization alive. They’re hiring more people. Not fewer. Every conversation about AI is built around subtraction. Fewer jobs. Fewer workers. Fewer humans in the loop. Jensen just told you the opposite is true. Huang: “Suppose we infused AI into this country, and as a result of that, we are doing things faster than ever before. Our ambition is greater than ever before. Our expectations are greater than ever before. How is that a bad condition for our country?” He’s not defending AI. He’s describing what happens inside the organizations that actually use it. It doesn’t make them leaner. It makes them hungrier. More ambition. More speed. More appetite for problems no one would have touched five years ago. The car didn’t make humans travel less. The internet didn’t make humans communicate less. No tool in human history has ever made humans want less. AI will not be the exception. Huang: “Prior to that, it’s been incredible but not useful. Now it’s useful and incredible.” Six months. That’s how fast AI crossed from impressive demo to daily weapon. The companies that adopted it didn’t shrink. They expanded. Compressed timelines. Started chasing problems they never would have attempted. The companies that ignored it stayed exactly where they were. That gap compounds. Every day a company uses AI to move faster, it learns something the one standing still never will. That knowledge stacks. That speed stacks. That ambition stacks. Jensen isn’t warning about a future where machines take your job. He’s describing a present where the companies using AI are becoming so fast and so hungry that standing still is already fatal. By the time you notice, it’s over. You were never going to be replaced by AI. You were going to be erased by someone it made hungrier than you.

Dustin

12,200 просмотров • 1 месяц 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!
3:40

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

1,223,527 просмотров • 1 год назад

“The Zoomers are so much better than the Millennials” Marc Andreessen 🇺🇸 on the AI-native Zoomers who learned tech from YouTube and have a burning desire to build something great: “2015 to 2024... was a very, very strange period. And a lot of just things got really weird. And the Zoomers are the generation that basically was on the receiving end of that.” “And they're not walking around feeling guilty about everything all the time. They're not feeling like they have to deny that they want to be successful.” “They've seen a thousand hours of YouTube videos from all the great people in tech talking about how to do everything. They just know so much more than previous generations of founders did.” “They're all AI native. They all basically learn AI from scratch and in college. They're coming out, and they totally understand it.” “They wear their heart on their sleeve. They're gonna build something great. And they're completely unapologetic about it.”
1:33

“The Zoomers are so much better than the Millennials” Marc Andreessen 🇺🇸 on the AI-native Zoomers who learned tech from YouTube and have a burning desire to build something great: “2015 to 2024... was a very, very strange period. And a lot of just things got really weird. And the Zoomers are the generation that basically was on the receiving end of that.” “And they're not walking around feeling guilty about everything all the time. They're not feeling like they have to deny that they want to be successful.” “They've seen a thousand hours of YouTube videos from all the great people in tech talking about how to do everything. They just know so much more than previous generations of founders did.” “They're all AI native. They all basically learn AI from scratch and in college. They're coming out, and they totally understand it.” “They wear their heart on their sleeve. They're gonna build something great. And they're completely unapologetic about it.”

a16z

132,855 просмотров • 4 месяцев 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."
1:54

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

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.
0:31

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

Akshay 🚀

30,789 просмотров • 1 год назад

Marc Andreessen (Marc Andreessen 🇺🇸) says he attended “absolutely horrifying” meetings where Biden’s government vowed to take “complete control” over AI technology: “They basically said AI is going to be a game of 2 or 3 big companies working closely with the government… We’re going to protect them from competition, control them, and dictate what they do.” When Marc countered that this would be impossible—the math behind AI is taught everywhere—they responded, “During the Cold War, we classified entire areas of physics and took them out of the research community—entire branches of physics went dark and didn’t proceed. If we decide we need to, we’re going to do the same thing to the math underneath AI.” Listen to his full interview with Bari Weiss:
3:34

Marc Andreessen (Marc Andreessen 🇺🇸) says he attended “absolutely horrifying” meetings where Biden’s government vowed to take “complete control” over AI technology: “They basically said AI is going to be a game of 2 or 3 big companies working closely with the government… We’re going to protect them from competition, control them, and dictate what they do.” When Marc countered that this would be impossible—the math behind AI is taught everywhere—they responded, “During the Cold War, we classified entire areas of physics and took them out of the research community—entire branches of physics went dark and didn’t proceed. If we decide we need to, we’re going to do the same thing to the math underneath AI.” Listen to his full interview with Bari Weiss:

Honestly with Bari Weiss

2,519,378 просмотров • 1 год назад

Marc Andreessen says 99.9999% of the value of AI will accrue to the users of AI, not the companies who create it: "If you look at the total amount of economic value creation downstream of the internet—something like 99% of that accrued to the users of the internet, not the companies that built the internet." "Same thing with a smartphone. Who gets the economic value of the smartphone? Everybody in the world who uses a smartphone to become more productive in their life or in their business gets 99% of the value from the smartphone. Apple and Google get 1% of the value from the smartphone." "I think AI is going to be exactly the same way. It might even be greater than that—it might be 99.9999% of the value of AI is gonna accrue to the users, not to the companies that make the AI." Marc Andreessen 🇺🇸 with Harry Stebbings
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Marc Andreessen says 99.9999% of the value of AI will accrue to the users of AI, not the companies who create it: "If you look at the total amount of economic value creation downstream of the internet—something like 99% of that accrued to the users of the internet, not the companies that built the internet." "Same thing with a smartphone. Who gets the economic value of the smartphone? Everybody in the world who uses a smartphone to become more productive in their life or in their business gets 99% of the value from the smartphone. Apple and Google get 1% of the value from the smartphone." "I think AI is going to be exactly the same way. It might even be greater than that—it might be 99.9999% of the value of AI is gonna accrue to the users, not to the companies that make the AI." Marc Andreessen 🇺🇸 with Harry Stebbings

a16z

39,093 просмотров • 2 месяцев назад

CYBER SLEUTH: Can AI crack the Nancy Guthrie case? A former White House Chief Information Officer says the new tech could lead to a major breakthrough: "They can start using AI to match up the eyes, so we have the eyes, the eyebrows, you can use AI to ask questions about what are the probabilities that these faces actually could be a good match, what are the probabilities that this person is wearing layers of clothing and they are not this bulky, what are the probabilities that they are taller than they seem to be and what do they weigh." "There's a lot of things that AI can be doing to aid this investigation."
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CYBER SLEUTH: Can AI crack the Nancy Guthrie case? A former White House Chief Information Officer says the new tech could lead to a major breakthrough: "They can start using AI to match up the eyes, so we have the eyes, the eyebrows, you can use AI to ask questions about what are the probabilities that these faces actually could be a good match, what are the probabilities that this person is wearing layers of clothing and they are not this bulky, what are the probabilities that they are taller than they seem to be and what do they weigh." "There's a lot of things that AI can be doing to aid this investigation."

Fox News

56,138 просмотров • 4 месяцев назад

.Marc Andreessen 🇺🇸 on the economic experiment playing out in real time as AI is put in the hands of programmers: "If you believe in the Luddite zero-sum argument, you would expect that they would be working less and less... getting paid less and less, and rapidly becoming unemployed." "The observed behavior of what's happening is very clear, which is the opposite." "They're working harder than ever. They're working more hours than ever." "They stop sleeping... they're bleary-eyed, they've got these huge bags under their eyes. They're completely exhausted, but they're euphoric." "If you increase marginal productivity of the worker, you don't have a diminishment of human work, you have an expansion of human work."
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.Marc Andreessen 🇺🇸 on the economic experiment playing out in real time as AI is put in the hands of programmers: "If you believe in the Luddite zero-sum argument, you would expect that they would be working less and less... getting paid less and less, and rapidly becoming unemployed." "The observed behavior of what's happening is very clear, which is the opposite." "They're working harder than ever. They're working more hours than ever." "They stop sleeping... they're bleary-eyed, they've got these huge bags under their eyes. They're completely exhausted, but they're euphoric." "If you increase marginal productivity of the worker, you don't have a diminishment of human work, you have an expansion of human work."

a16z

36,885 просмотров • 1 месяц назад

Chamath on how AI agents are making the "10x engineer" distinction disappear because the most efficient "code paths" are now obvious to everyone. Just as AI solved chess and removed the mystery of the best move, AI is doing the same for coding, making the process reductive and removing technical differentiation. "I'm going to say something controversial: I don't think developers anymore have good judgment. Developers get to the answer, or they don't get to the answer, and that's what agents have done. The 10x engineer used to have better judgment than the 1x engineer, but by making everybody a 10x engineer, you're taking judgment away. You're taking code paths that are now obvious and making them available to everybody. It's effectively like what happened in chess: an AI created a solver so everybody understood the most efficient path in every single spot to do the most EV-positive (expected value positive) thing. Coding is very similar in that way; you can reduce it and view it very reductively, so there is no differentiation in code." --- From The All-In Podcast YT channel (link in comment)
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Chamath on how AI agents are making the "10x engineer" distinction disappear because the most efficient "code paths" are now obvious to everyone. Just as AI solved chess and removed the mystery of the best move, AI is doing the same for coding, making the process reductive and removing technical differentiation. "I'm going to say something controversial: I don't think developers anymore have good judgment. Developers get to the answer, or they don't get to the answer, and that's what agents have done. The 10x engineer used to have better judgment than the 1x engineer, but by making everybody a 10x engineer, you're taking judgment away. You're taking code paths that are now obvious and making them available to everybody. It's effectively like what happened in chess: an AI created a solver so everybody understood the most efficient path in every single spot to do the most EV-positive (expected value positive) thing. Coding is very similar in that way; you can reduce it and view it very reductively, so there is no differentiation in code." --- From The All-In Podcast YT channel (link in comment)

Rohan Paul

831,802 просмотров • 2 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.
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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

82,690 просмотров • 2 месяцев назад