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“the best programmers are using AI already.” here is what a senior programmer who’s been coding for decades thinks about the future of programming:

ℏεsam

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248,375 просмотров • 5 месяцев назад •via X (Twitter)

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Agreed. Vibe coding has already removed the need for most jr programmers.

Agreed. Vibe coding has already removed the need for most jr programmers.

Peter H. Diamandis, MD

12,252 просмотров • 10 месяцев назад

Jensen made the rounds recently, saying that people shouldn't need to learn how to code to program in the future. I agree: Coding is incidental to programming, which is the act of solving problems. Programmers will instead be orchestrating AIs. An excerpt from my TED AI talk.

Jensen made the rounds recently, saying that people shouldn't need to learn how to code to program in the future. I agree: Coding is incidental to programming, which is the act of solving problems. Programmers will instead be orchestrating AIs. An excerpt from my TED AI talk.

Amjad Masad

83,236 просмотров • 2 лет назад

Marc Andreessen: AI coding doesn’t eliminate programmers — it redefines them. The job is no longer typing code line by line, it’s orchestrating 10 coding bots in parallel, arguing with them, debugging their output, changing the spec, and pushing them toward the right result. But here’s the catch: if you don’t understand how to write code yourself, you can’t evaluate what the AI gives you. The next layer of programming isn’t writing scripts — it’s supervising AI that writes them. Today’s best programmers spend their day jumping between terminals, managing multiple coding bots, fixing mistakes, and refining instructions. The irony? You still need deep fundamentals, because without them, you won’t know when the AI is wrong. The job of the programmer has changed. Now it’s about arguing with coding bots, debugging AI-generated code, and understanding why something doesn’t work or isn’t fast enough. AI abstracts the work — but only people who truly understand code can tell if the abstraction is doing the right thing. Programmers aren’t going away — they’re becoming 10x, 100x, even 1,000x more productive. Tasks are changing, the job is changing, but humans are still overseeing the process, evaluating results, fixing errors, and making judgment calls. AI changes how we code, not who is responsible. The future programmer isn’t replaced by AI — they’re upgraded by it. You still need to learn how to write and understand code, because when the AI gets it wrong, humans are the ones who have to know why. That up-leveling of capability is the real revolution.

Marc Andreessen: AI coding doesn’t eliminate programmers — it redefines them. The job is no longer typing code line by line, it’s orchestrating 10 coding bots in parallel, arguing with them, debugging their output, changing the spec, and pushing them toward the right result. But here’s the catch: if you don’t understand how to write code yourself, you can’t evaluate what the AI gives you. The next layer of programming isn’t writing scripts — it’s supervising AI that writes them. Today’s best programmers spend their day jumping between terminals, managing multiple coding bots, fixing mistakes, and refining instructions. The irony? You still need deep fundamentals, because without them, you won’t know when the AI is wrong. The job of the programmer has changed. Now it’s about arguing with coding bots, debugging AI-generated code, and understanding why something doesn’t work or isn’t fast enough. AI abstracts the work — but only people who truly understand code can tell if the abstraction is doing the right thing. Programmers aren’t going away — they’re becoming 10x, 100x, even 1,000x more productive. Tasks are changing, the job is changing, but humans are still overseeing the process, evaluating results, fixing errors, and making judgment calls. AI changes how we code, not who is responsible. The future programmer isn’t replaced by AI — they’re upgraded by it. You still need to learn how to write and understand code, because when the AI gets it wrong, humans are the ones who have to know why. That up-leveling of capability is the real revolution.

Ian Miles Cheong

911,697 просмотров • 4 месяцев назад

the best programmers are the ones that can adapt and constantly learn / progress while everything is changing around them for CJ (Coding Garden) - 2026 will be the year of "just enough AI"™️, less hype, less FOMO, more building / shipping

the best programmers are the ones that can adapt and constantly learn / progress while everything is changing around them for CJ (Coding Garden) - 2026 will be the year of "just enough AI"™️, less hype, less FOMO, more building / shipping

Syntax

23,630 просмотров • 5 месяцев назад

Anthropic Boris Cherny says the role of programmers is shifting from writing code to orchestrating agents "it's more about reviewing code than writing code" complex tasks still require manual coding, but those windows are shrinking. eventually, managing agents will become the core of programming

Anthropic Boris Cherny says the role of programmers is shifting from writing code to orchestrating agents "it's more about reviewing code than writing code" complex tasks still require manual coding, but those windows are shrinking. eventually, managing agents will become the core of programming

Haider.

137,886 просмотров • 1 год назад

Many AI-savvy programmers are now coding very differently than before, by using LLMs to help with their work. You’ll learn these emerging best practices in “Pair Programming with a Large Language Model,” by Google's Laurence Moroney 🇺🇸🇮🇪 🏴󠁧󠁢󠁷󠁬󠁳󠁿. This short course covers using LLMs to simplify and improve your code, assist with debugging, and minimize technical debt by having AI document your code. The use of LLMs as a programming companion is an important shift that's well worth every developer staying on top of. Please check this out!

Many AI-savvy programmers are now coding very differently than before, by using LLMs to help with their work. You’ll learn these emerging best practices in “Pair Programming with a Large Language Model,” by Google's Laurence Moroney 🇺🇸🇮🇪 🏴󠁧󠁢󠁷󠁬󠁳󠁿. This short course covers using LLMs to simplify and improve your code, assist with debugging, and minimize technical debt by having AI document your code. The use of LLMs as a programming companion is an important shift that's well worth every developer staying on top of. Please check this out!

Andrew Ng

373,418 просмотров • 2 лет назад

AI has changed software engineering more in the last 3 years than it has changed in the previous 30. What’s needed is not a debate about whether it’s going away—instead it’s a serious discussion about its future: What are the new primitives, techniques, and best practices for software engineering in the age of AI. That’s why I brought Scott Wu (Scott Wu) on AI & I. He’s the founder of Cognition, the company behind the world’s first autonomous AI coding agent, Devin. Cognition got to $73M ARR in less than 2 years—and they just acquired Windsurf to accelerate their growth. I had Scott on the show to talk about where the programming goes from here. We get into: - What the new tools and workflows are for AI engineers. In the near term, Scott sees software engineering defined by a spectrum of tools. At one end are AI features that speed up coding, like tab complete; at the other are agentic systems, like Devin, that can take on tasks independently. Until engineers can operate entirely at the higher layer of abstraction, he argues, both are essential. - Why Scott thinks AGI is already here. By the benchmarks of a decade ago—passing the Turing test, solving hard math problems, and operating agentically—AGI is already here. The line keeps moving, he argues, because humans constantly redefine work around what machines can’t yet do. - Why developers will turn into product architects. Scott sees the long-term future of software engineering as a steady climb up the ladder of abstraction. Just as programming went from assembly to languages like Python and JavaScript, he thinks the future is humans focusing on the product, while AI agents execute. - How Devin stacks up against Anthropic’s Claude Code. Scott credits Claude Code’s success to great product design and the models becoming capable enough to support autonomous workflows. But according to him, the CLI itself isn’t the breakthrough, it’s how a tool fits into a developer’s workflow. Claude Code’s paradigm is that the AI is you, taking the wheel of your computer, he says, while Devin is like the engineer sitting beside you: it runs in its own cloud environment, manages the repo, and improves over time at testing and refining code. This episode of Every 📧’s AI & I is a must-watch for anyone interested in the brass tacks of how AI changes the future of programming. Watch below! Timestamps: Introduction: 00:02:02 Why Scott thinks AGI is here: 00:02:32 Scott’s personal journey as a founder: 00:09:27 Why the fundamentals of computer science still matter: 00:16:55 How the future of programming will evolve: 00:22:30 A new workflow for the AI-first software engineer: 00:26:50 How Devin stacks up against Claude Code: 00:29:33 Reinforcement learning to build better coding agents: 00:40:05 What excites Scott about AI beyond Cognition: 00:50:05

AI has changed software engineering more in the last 3 years than it has changed in the previous 30. What’s needed is not a debate about whether it’s going away—instead it’s a serious discussion about its future: What are the new primitives, techniques, and best practices for software engineering in the age of AI. That’s why I brought Scott Wu (Scott Wu) on AI & I. He’s the founder of Cognition, the company behind the world’s first autonomous AI coding agent, Devin. Cognition got to $73M ARR in less than 2 years—and they just acquired Windsurf to accelerate their growth. I had Scott on the show to talk about where the programming goes from here. We get into: - What the new tools and workflows are for AI engineers. In the near term, Scott sees software engineering defined by a spectrum of tools. At one end are AI features that speed up coding, like tab complete; at the other are agentic systems, like Devin, that can take on tasks independently. Until engineers can operate entirely at the higher layer of abstraction, he argues, both are essential. - Why Scott thinks AGI is already here. By the benchmarks of a decade ago—passing the Turing test, solving hard math problems, and operating agentically—AGI is already here. The line keeps moving, he argues, because humans constantly redefine work around what machines can’t yet do. - Why developers will turn into product architects. Scott sees the long-term future of software engineering as a steady climb up the ladder of abstraction. Just as programming went from assembly to languages like Python and JavaScript, he thinks the future is humans focusing on the product, while AI agents execute. - How Devin stacks up against Anthropic’s Claude Code. Scott credits Claude Code’s success to great product design and the models becoming capable enough to support autonomous workflows. But according to him, the CLI itself isn’t the breakthrough, it’s how a tool fits into a developer’s workflow. Claude Code’s paradigm is that the AI is you, taking the wheel of your computer, he says, while Devin is like the engineer sitting beside you: it runs in its own cloud environment, manages the repo, and improves over time at testing and refining code. This episode of Every 📧’s AI & I is a must-watch for anyone interested in the brass tacks of how AI changes the future of programming. Watch below! Timestamps: Introduction: 00:02:02 Why Scott thinks AGI is here: 00:02:32 Scott’s personal journey as a founder: 00:09:27 Why the fundamentals of computer science still matter: 00:16:55 How the future of programming will evolve: 00:22:30 A new workflow for the AI-first software engineer: 00:26:50 How Devin stacks up against Claude Code: 00:29:33 Reinforcement learning to build better coding agents: 00:40:05 What excites Scott about AI beyond Cognition: 00:50:05

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The future of coding is agentic. With Replit AI, every frustrating aspect of programming will melt away, so that you and your team can focus on solving the complex problems that matter.

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