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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... show more

Santiago

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16,299 views • 7 months ago •via X (Twitter)

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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

64,438 views • 8 months ago

AI is changing the software engineering craft. Anders Hejlsberg (Anders Hejlsberg) - creator of C#, TypeScript and industry legend - on why code review needs to get more enjoyable in response: #1 - AI is shifting the craft from writing code, to reviewing code: "In a sense, we're all turning into project managers. We can have an army of junior programmers, called agents, that will just spit out reams of code but someone's got to have the big picture and review all of that. And so, increasingly, our craft is going from one of writing the code, to one of reviewing the code and building the architecture of the code and overseeing the work. It's a different kind of craft. It's a different kind of enjoyment. I've always liked writing the code. To me that was the fulfilling part, seeing it work. In a way, AI robs a little bit of that, because I am less interested in reviewing code." #2 - The code review experience should be improved: "I think we could also make the process of reviewing code much more interesting than it is today. I mean, today, you see a list of diffs in alphabetical order and now it's up to you to make heads or tails of it. There are more pedagogical ways of presenting that. And you could have commentary generated by the AI that tells you what the changes are and whatever, and then tries to guide you along. So that symbiotic relationship, I think we need to work on that more and to keep the enjoyment in there."

AI is changing the software engineering craft. Anders Hejlsberg (Anders Hejlsberg) - creator of C#, TypeScript and industry legend - on why code review needs to get more enjoyable in response: #1 - AI is shifting the craft from writing code, to reviewing code: "In a sense, we're all turning into project managers. We can have an army of junior programmers, called agents, that will just spit out reams of code but someone's got to have the big picture and review all of that. And so, increasingly, our craft is going from one of writing the code, to one of reviewing the code and building the architecture of the code and overseeing the work. It's a different kind of craft. It's a different kind of enjoyment. I've always liked writing the code. To me that was the fulfilling part, seeing it work. In a way, AI robs a little bit of that, because I am less interested in reviewing code." #2 - The code review experience should be improved: "I think we could also make the process of reviewing code much more interesting than it is today. I mean, today, you see a list of diffs in alphabetical order and now it's up to you to make heads or tails of it. There are more pedagogical ways of presenting that. And you could have commentary generated by the AI that tells you what the changes are and whatever, and then tries to guide you along. So that symbiotic relationship, I think we need to work on that more and to keep the enjoyment in there."

The Pragmatic Engineer

39,073 views • 3 months ago

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

296,637 views • 10 months ago

The bottleneck in coding is now the time it takes a human to review agent-generated code. But existing review UIs don't work well for agents. So we built a new one into Amp.

The bottleneck in coding is now the time it takes a human to review agent-generated code. But existing review UIs don't work well for agents. So we built a new one into Amp.

Beyang

63,082 views • 10 months ago

Insane: 90-95% of Claude Code is now written by Claude Code. I asked Mike Krieger (Anthropic's CPO) what changes when so much of your code is written by AI? His answer: The bottleneck moves from coding/design to: 1. Upstream: aligning the team around what to build. 2. Downstream: the PR merge queue, reviewing and merging all of the new code into production. Anthropic is where other product teams will be in a year or two, so it's important we pay attention. "I would expect that a year from now, the way that we are conceiving of building and shipping software changes a lot. Because it's gonna be very painful to do it the current way."

Insane: 90-95% of Claude Code is now written by Claude Code. I asked Mike Krieger (Anthropic's CPO) what changes when so much of your code is written by AI? His answer: The bottleneck moves from coding/design to: 1. Upstream: aligning the team around what to build. 2. Downstream: the PR merge queue, reviewing and merging all of the new code into production. Anthropic is where other product teams will be in a year or two, so it's important we pay attention. "I would expect that a year from now, the way that we are conceiving of building and shipping software changes a lot. Because it's gonna be very painful to do it the current way."

Lenny Rachitsky

369,920 views • 1 year ago

30% of code at top tech companies is now AI-generated. Most engineering leaders have no idea what that means for speed, quality, or ROI. Nivara ( gives them visibility into how humans and AI build together. The future of engineering is hybrid.

30% of code at top tech companies is now AI-generated. Most engineering leaders have no idea what that means for speed, quality, or ROI. Nivara ( gives them visibility into how humans and AI build together. The future of engineering is hybrid.

Y Combinator

26,681 views • 9 months ago

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

slash1s

22,107 views • 2 months ago

What people don't realize is that a short '10 minute technical talk' is easily 35 slides worth of content and months of technical work. I've often struggled to use AI to generate slides (the lack of taste!) but two unlocks recently changed that: 1. Fast code generation → fast slides iteration 2. Writing my slides in HTML instead of generating graphics (models are better at writing code) Check out how I built my boilerplate with Mistral AI's Mistral Vibe. Available through the Le Chat Pro and team plan :) Get started with Mistral Vibe:

What people don't realize is that a short '10 minute technical talk' is easily 35 slides worth of content and months of technical work. I've often struggled to use AI to generate slides (the lack of taste!) but two unlocks recently changed that: 1. Fast code generation → fast slides iteration 2. Writing my slides in HTML instead of generating graphics (models are better at writing code) Check out how I built my boilerplate with Mistral AI's Mistral Vibe. Available through the Le Chat Pro and team plan :) Get started with Mistral Vibe:

Sarah Chieng

18,300 views • 4 months ago

SHIPPED. Mistral Vibe is now the AI agent for long-horizon productivity and coding, and the home for Work mode, Code mode, the CLI, and a brand new VS Code extension. Let's go... 🧵

Vibe

239,242 views • 3 months ago

An MCP server that detects production-grade code quality issues in real-time! Even though AI is now generating code at light speed, the engineering bottleneck has just moved from writing to reviewing, and now devs spend 90% of their debugging time on AI-generated code. AI reviewers aren't that reliable either because they share the same fundamental blind spots as AI generators do: - They pattern match, not proof check. - They validate syntax, not system behavior. - They review code, not consequences. I have been using the SonarQube MCP Server (by Sonar) to solve this. It produces enterprise-grade code analysis and returns instant feedback on bugs, vulnerabilities, and code smells right where you're working (Claude Code, Cursor, etc.). Its capabilities have emerged from the 750B+ lines of code SonarQube processes daily, so it has seen every bug pattern that exists. This includes: - Security vulnerabilities (SQL injection, XSS, hardcoded secrets) - Code smells and technical debt - Test coverage gaps - Maintainability issues The setup is simple: - Install the SonarQube MCP server - Add it to your AI assistant's config Done! SonarQube is now part of your AI coding workflow. I have shared the GitHub repo in the replies! P.S. Thanks to Sonar for working with me today.

An MCP server that detects production-grade code quality issues in real-time! Even though AI is now generating code at light speed, the engineering bottleneck has just moved from writing to reviewing, and now devs spend 90% of their debugging time on AI-generated code. AI reviewers aren't that reliable either because they share the same fundamental blind spots as AI generators do: - They pattern match, not proof check. - They validate syntax, not system behavior. - They review code, not consequences. I have been using the SonarQube MCP Server (by Sonar) to solve this. It produces enterprise-grade code analysis and returns instant feedback on bugs, vulnerabilities, and code smells right where you're working (Claude Code, Cursor, etc.). Its capabilities have emerged from the 750B+ lines of code SonarQube processes daily, so it has seen every bug pattern that exists. This includes: - Security vulnerabilities (SQL injection, XSS, hardcoded secrets) - Code smells and technical debt - Test coverage gaps - Maintainability issues The setup is simple: - Install the SonarQube MCP server - Add it to your AI assistant's config Done! SonarQube is now part of your AI coding workflow. I have shared the GitHub repo in the replies! P.S. Thanks to Sonar for working with me today.

Avi Chawla

28,628 views • 8 months ago

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

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

Patrick OShaughnessy

24,818 views • 6 months ago

$Anthropic CEO Dario Amodei just revealed the hidden bottleneck that will kill most AI companies in the next 18 months (Save this). The insight comes from a principle in computer science called Amdahl's Law. Dario's argument is simple when something starts working really well inside an organization, you have to immediately ask what isn't working well around it. Amdahl's Law states that the maximum speedup of any system is capped by the fraction you haven't improved and that applies to companies just as brutally as it applies to processors. If you can suddenly write three or four times as many pull requests as before, you don't get three or four times the output but you rather get a pile of code no one can review, verify, or trust. The data makes this impossible to ignore. Teams with heavy AI coding adoption are merging 98% more pull requests but PR review time has ballooned 91%, deployment velocity is effectively flat and 96% of developers don't fully trust AI-generated code reaching production. AI generated code produces 1.7x more issues per pull request than human written code, 0.83 issues per PR versus 6.45. Veracode's 2026 State of Software Security report found that 82% of organizations now carry security debt, up 11% year over year, with critical security debt surging 36% in a single year driven directly by AI-generated code reaching production faster than security teams can handle. What Dario is describing is a systems problem, not a software problem and coding is roughly 20% of the software delivery cycle. Even at infinite coding speed, you're still bottlenecked by review, security, verification, testing, and deployment which make up the other 80%. The enterprises that win are the ones that identify which part of their system is the new constraint after AI accelerates the old one and fix that next. This is why Anthropic's Claude Code focuses on the full development loop, not just generation, and why the verification and security layer of the AI stack is where the next wave of enterprise value gets created. This is also why Anthropic as a company is positioned differently than most people realize. Anthropic's 2026 Agentic Coding Trends Report found that organizations using full-loop agentic coding workflows where AI handles not just generation but testing, review, and deployment validation reduced their software defect rates by 43% while increasing velocity by 2.8x. Claude Code now authors 4% of all GitHub commits and is on track to hit 20%+ by year-end, with the full-loop use case growing 3x faster than pure code generation. Dario has been building Anthropic around the exact insight he's describing publicly ,the constraint isn't writing code but rather everything that has to happen after.$

Anthropic CEO Dario Amodei just revealed the hidden bottleneck that will kill most AI companies in the next 18 months (Save this). The insight comes from a principle in computer science called Amdahl's Law. Dario's argument is simple when something starts working really well inside an organization, you have to immediately ask what isn't working well around it. Amdahl's Law states that the maximum speedup of any system is capped by the fraction you haven't improved and that applies to companies just as brutally as it applies to processors. If you can suddenly write three or four times as many pull requests as before, you don't get three or four times the output but you rather get a pile of code no one can review, verify, or trust. The data makes this impossible to ignore. Teams with heavy AI coding adoption are merging 98% more pull requests but PR review time has ballooned 91%, deployment velocity is effectively flat and 96% of developers don't fully trust AI-generated code reaching production. AI generated code produces 1.7x more issues per pull request than human written code, 0.83 issues per PR versus 6.45. Veracode's 2026 State of Software Security report found that 82% of organizations now carry security debt, up 11% year over year, with critical security debt surging 36% in a single year driven directly by AI-generated code reaching production faster than security teams can handle. What Dario is describing is a systems problem, not a software problem and coding is roughly 20% of the software delivery cycle. Even at infinite coding speed, you're still bottlenecked by review, security, verification, testing, and deployment which make up the other 80%. The enterprises that win are the ones that identify which part of their system is the new constraint after AI accelerates the old one and fix that next. This is why Anthropic's Claude Code focuses on the full development loop, not just generation, and why the verification and security layer of the AI stack is where the next wave of enterprise value gets created. This is also why Anthropic as a company is positioned differently than most people realize. Anthropic's 2026 Agentic Coding Trends Report found that organizations using full-loop agentic coding workflows where AI handles not just generation but testing, review, and deployment validation reduced their software defect rates by 43% while increasing velocity by 2.8x. Claude Code now authors 4% of all GitHub commits and is on track to hit 20%+ by year-end, with the full-loop use case growing 3x faster than pure code generation. Dario has been building Anthropic around the exact insight he's describing publicly ,the constraint isn't writing code but rather everything that has to happen after.

Milk Road AI

52,190 views • 3 months ago

Anthropic CEO, Dario Amodei in the next 3 to 6 months, AI is writing 90% of the code, and in 12 months, nearly all code may be generated by AI

Anthropic CEO, Dario Amodei in the next 3 to 6 months, AI is writing 90% of the code, and in 12 months, nearly all code may be generated by AI

Haider.

9,321,644 views • 1 year ago

$OpenAI Greg Brockman says the fraction of code not written by AI is vanishing With the right context and structure, the actual coding is already better handled by AI than by humans "what's left for human experts is the architecture" But the actual writing of code is essentially all AI now$

OpenAI Greg Brockman says the fraction of code not written by AI is vanishing With the right context and structure, the actual coding is already better handled by AI than by humans "what's left for human experts is the architecture" But the actual writing of code is essentially all AI now

Haider.

11,078 views • 4 months ago

Windsurf Founder: AI Will 10x Every Part of Coding - Faster Than You Think "It's gonna get crazy." "Every part of the software development life cycle, whether it be writing code, reviewing code, testing code, debugging code, designing code, AI is gonna be adding 10X the amount of leverage very shortly. It's gonna happen much more quickly than people imagine." Varun Mohan on Y Combinator's Lightcone Podcast

Windsurf Founder: AI Will 10x Every Part of Coding - Faster Than You Think "It's gonna get crazy." "Every part of the software development life cycle, whether it be writing code, reviewing code, testing code, debugging code, designing code, AI is gonna be adding 10X the amount of leverage very shortly. It's gonna happen much more quickly than people imagine." Varun Mohan on Y Combinator's Lightcone Podcast

Overlap: Business & Tech

47,969 views • 1 year ago

Creator and head of Claude Code, Anthropic: "I don't prompt Claude anymore. I have loops running that prompt Claude and decide what to do. My job is to write loops." He hasn't hand-written a line of code since November. 100% is Claude Code now. Still ships 10 to 30 pull requests a day. He breaks down his actual workflow in the 1h28m podcast. Loops writing 100% of the code. Engineer leveling up, or automated out?

Creator and head of Claude Code, Anthropic: "I don't prompt Claude anymore. I have loops running that prompt Claude and decide what to do. My job is to write loops." He hasn't hand-written a line of code since November. 100% is Claude Code now. Still ships 10 to 30 pull requests a day. He breaks down his actual workflow in the 1h28m podcast. Loops writing 100% of the code. Engineer leveling up, or automated out?

shmidt

521,927 views • 2 months ago

Boris Cherny (Creator of Claude Code): "The one technical book I would recommend to everyone that has had the greatest impact on me as an engineer is functional programming in Scala. You're probably never going to use Scala day today, but the way it teaches you to think about coding problems is just such a change from the way that most people were in coding, either practically or in school. It's just. It's incredible. It's going to completely change the way that you code now. I think in types, when I code, the thing that matters in your code the most is the type signatures. This is more important than the code itself." Boris Cherny

Boris Cherny (Creator of Claude Code): "The one technical book I would recommend to everyone that has had the greatest impact on me as an engineer is functional programming in Scala. You're probably never going to use Scala day today, but the way it teaches you to think about coding problems is just such a change from the way that most people were in coding, either practically or in school. It's just. It's incredible. It's going to completely change the way that you code now. I think in types, when I code, the thing that matters in your code the most is the type signatures. This is more important than the code itself." Boris Cherny

Ryan Peterman

365,032 views • 4 months ago

LeetCode is dead. Developers don't write code line-by-line anymore. They orchestrate AI agents working in parallel, review AI-generated code, and make architectural decisions. That's the job now. But most interview processes haven't caught up. They still test algorithm memorization instead of AI fluency, code review, and judgment. We're building assessments for next-gen hiring that mirror how developers actually work. Here's how we think about it:

LeetCode is dead. Developers don't write code line-by-line anymore. They orchestrate AI agents working in parallel, review AI-generated code, and make architectural decisions. That's the job now. But most interview processes haven't caught up. They still test algorithm memorization instead of AI fluency, code review, and judgment. We're building assessments for next-gen hiring that mirror how developers actually work. Here's how we think about it:

HackerRank

344,255 views • 4 months ago

Today we're launching REVIEW.FAST, speeding up human review of AI generated code 3X. AI changed the world, sped up writing code, but shifted the bottleneck to review. If you can speed up code review, you can ship more. It's as simple as that.

Today we're launching REVIEW.FAST, speeding up human review of AI generated code 3X. AI changed the world, sped up writing code, but shifted the bottleneck to review. If you can speed up code review, you can ship more. It's as simple as that.

Louis Knight-Webb

46,339 views • 8 months ago