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Creator of C++, Bjarne Stroustrup: AI-generated code isn't ready — it generates more bugs, more bloat, more security holes, and is nearly impossible to validate "senior developers are already retiring rather than deal with it" The problem is that even a small prompt change can shift the entire codebase... show more

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Microsoft CEO, Satya Nadella: "AI now generates 20–30% of Microsoft’s integrated code" the company is seeing mixed results in AI-generated code across different languages, with more progress in Python and less in C++

Microsoft CEO, Satya Nadella: "AI now generates 20–30% of Microsoft’s integrated code" the company is seeing mixed results in AI-generated code across different languages, with more progress in Python and less in C++

Haider.

141,788 просмотров • 1 год назад

Today, I'm excited to launch Entelligence AI DeepReviews, the next generation AI-powered code reviews. Vibe coded PRs are not production ready often creating more subtle bugs throughout the codebase than before. Entelligence fixes this by understanding the entire codebase and flags bugs, regressions, and breakages across files before you ship. But it goes beyond review comments: ✅ Auto-generated docs with architecture diagrams ✅ Team Insights to improve process, not just code ✅ Real time code reviews within your editor If you're building or leading a dev team, this is what smarter, context-aware reviews look like. Try it out in the link below 👇

Today, I'm excited to launch Entelligence AI DeepReviews, the next generation AI-powered code reviews. Vibe coded PRs are not production ready often creating more subtle bugs throughout the codebase than before. Entelligence fixes this by understanding the entire codebase and flags bugs, regressions, and breakages across files before you ship. But it goes beyond review comments: ✅ Auto-generated docs with architecture diagrams ✅ Team Insights to improve process, not just code ✅ Real time code reviews within your editor If you're building or leading a dev team, this is what smarter, context-aware reviews look like. Try it out in the link below 👇

Aiswarya Sankar

96,309 просмотров • 1 год назад

At the AI in America Summit, Scott Dietzen, Executive Chair of Augment Code and former CEO of Pure Storage, described how AI is reshaping software development through “meta programming”—where engineers guide and refine AI-generated code rather than writing everything line by line. He argued this shift isn’t about cutting developers, but about unlocking far greater productivity and building more ambitious software than ever before. Explore more: #TheHillTech #AIinTech #FutureOfWork

At the AI in America Summit, Scott Dietzen, Executive Chair of Augment Code and former CEO of Pure Storage, described how AI is reshaping software development through “meta programming”—where engineers guide and refine AI-generated code rather than writing everything line by line. He argued this shift isn’t about cutting developers, but about unlocking far greater productivity and building more ambitious software than ever before. Explore more: #TheHillTech #AIinTech #FutureOfWork

The Hill Events

10,971 просмотров • 8 месяцев назад

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 просмотров • 3 месяцев назад

Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.

Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.

Milk Road AI

24,356 просмотров • 3 месяцев назад

$PLTR is one of the only software platforms that plausibly becomes more important in an agentic world rather than less important. The market can argue about how expensive it is but it is much harder to argue that the problem it solves is going away.

$PLTR is one of the only software platforms that plausibly becomes more important in an agentic world rather than less important. The market can argue about how expensive it is but it is much harder to argue that the problem it solves is going away.

Shay Boloor

197,964 просмотров • 6 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

64,438 просмотров • 8 месяцев назад

Elon Musk: Hunger these days is more of a political and logistics problem than it is not having enough food There's a lot of food. In fact, in the US and many countries, the issue is more obesity than it is hunger. So I'm always looking for ways to give away money that are effective Like, what do you think I should do?"

Elon Musk: Hunger these days is more of a political and logistics problem than it is not having enough food There's a lot of food. In fact, in the US and many countries, the issue is more obesity than it is hunger. So I'm always looking for ways to give away money that are effective Like, what do you think I should do?"

X Freeze

43,729 просмотров • 8 месяцев назад

AI can now hack everything. In 3 weeks Anthropic’s new AI built more hacks than the entire global security community discovered in the past decade. Treasury is already holding emergency meetings with banks.

AI can now hack everything. In 3 weeks Anthropic’s new AI built more hacks than the entire global security community discovered in the past decade. Treasury is already holding emergency meetings with banks.

Peter St Onge, Ph.D.

167,035 просмотров • 4 месяцев назад

This is the video AI Haters tried to cancel, created by Martin Nebelong, who has just given me permission to republish it. He felt compelled to remove it due to the incredible amount of bullying he was receiving. In his words: "The amount of hate, negativity, and fear was staggering, and I didn't want to defend myself against that." Nothing outrages me more me more than the "cancel culture" and the unfair pressures on creators who are simply using AI tools and showing the world how they can learn these new creative processes. His video is amazing. It shows how Generative AI nowadays is much more than "just writing a prompt". And how it will enable artists and designers to experiment in countless new ways. Remember that it's not that artists/designers hate AI! AI Haters are just a small group of people and they don't speak for all artists. In fact, I know many more artists and designers who already use it daily. But they just don't make noise: they focus on learning and creating. Martin, you, and any other creator using AI, has all my support!

This is the video AI Haters tried to cancel, created by Martin Nebelong, who has just given me permission to republish it. He felt compelled to remove it due to the incredible amount of bullying he was receiving. In his words: "The amount of hate, negativity, and fear was staggering, and I didn't want to defend myself against that." Nothing outrages me more me more than the "cancel culture" and the unfair pressures on creators who are simply using AI tools and showing the world how they can learn these new creative processes. His video is amazing. It shows how Generative AI nowadays is much more than "just writing a prompt". And how it will enable artists and designers to experiment in countless new ways. Remember that it's not that artists/designers hate AI! AI Haters are just a small group of people and they don't speak for all artists. In fact, I know many more artists and designers who already use it daily. But they just don't make noise: they focus on learning and creating. Martin, you, and any other creator using AI, has all my support!

Javi Lopez ⛩️

4,122,306 просмотров • 2 лет назад

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dan McAteer

174,505 просмотров • 2 месяцев назад

GPT Engineer github: Specify what you want it to build, the AI asks for clarification, and then builds it. GPT Engineer is made to be easy to adapt, extend, and make your agent learn how you want your code to look. It generates an entire codebase based on a prompt.

GPT Engineer github: Specify what you want it to build, the AI asks for clarification, and then builds it. GPT Engineer is made to be easy to adapt, extend, and make your agent learn how you want your code to look. It generates an entire codebase based on a prompt.

AK

349,154 просмотров • 3 лет 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

296,637 просмотров • 10 месяцев назад

In our $KGN earnings call today, it sounded like it's David Shafer and I presenting but it wasn't. Our voices were AI generated and read the script. We uploaded several hours of our prior talks to train our voice model and the results were pretty incredible. This saved us a few hours preparation - valuable time we could spend working on other areas of the business. This is an example of the many one percenters across our business where AI is making us more efficient and helping the team be more productive. Our marketing team uses it to improve our content and make it more enaging. Our Engineering team uses it to get more context of our entire code base quicker and produce production ready code more rapidly. Our purchasing teams are using it for data and trend analysis to bring the latest products to our customers at even better prices. The list goes on. While the productivity gains are exciting, what's even more exciting is the pace at which things are changing and the technology is getting better!

In our $KGN earnings call today, it sounded like it's David Shafer and I presenting but it wasn't. Our voices were AI generated and read the script. We uploaded several hours of our prior talks to train our voice model and the results were pretty incredible. This saved us a few hours preparation - valuable time we could spend working on other areas of the business. This is an example of the many one percenters across our business where AI is making us more efficient and helping the team be more productive. Our marketing team uses it to improve our content and make it more enaging. Our Engineering team uses it to get more context of our entire code base quicker and produce production ready code more rapidly. Our purchasing teams are using it for data and trend analysis to bring the latest products to our customers at even better prices. The list goes on. While the productivity gains are exciting, what's even more exciting is the pace at which things are changing and the technology is getting better!

Ruslan Kogan

814,106 просмотров • 1 год назад

Researchers found that D.C., Maryland, and Virginia are among the places where AI has some of the highest potential to either wipe out or transform jobs. In Maryland, researchers estimate nearly 40% of the workforce is in occupations where AI can do the job. D.C. ranks even higher, with more than 55% of workers in jobs threatened by AI. MORE:

Researchers found that D.C., Maryland, and Virginia are among the places where AI has some of the highest potential to either wipe out or transform jobs. In Maryland, researchers estimate nearly 40% of the workforce is in occupations where AI can do the job. D.C. ranks even higher, with more than 55% of workers in jobs threatened by AI. MORE:

7News DC

37,834 просмотров • 3 месяцев назад

Elon Musk predicts that AI will bypass coding entirely by the end of 2026 - just creates the binary directly AI can create a much more efficient binary than can be done by any compiler So just say, "Create optimized binary for this particular outcome," and you actually bypass even traditional coding Current: Code → Compiler → Binary → Execute Future: Prompt → AI-generated Binary → Execute Grok Code is going to be state-of-the-art in 2–3 months Software development is about to fundamentally change

Elon Musk predicts that AI will bypass coding entirely by the end of 2026 - just creates the binary directly AI can create a much more efficient binary than can be done by any compiler So just say, "Create optimized binary for this particular outcome," and you actually bypass even traditional coding Current: Code → Compiler → Binary → Execute Future: Prompt → AI-generated Binary → Execute Grok Code is going to be state-of-the-art in 2–3 months Software development is about to fundamentally change

X Freeze

1,441,375 просмотров • 6 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 • 7 месяцев назад

introducing knowledge bases. greptile maintains detailed docs about how your codebase works, and uses them during review. for each part of the codebase, it maintains a running list of past bugs. this way, the next time it reviews that part of the code, it knows what to look for. greptile catches 12.2% more bugs with knowledge bases enabled! now available to all users :)

introducing knowledge bases. greptile maintains detailed docs about how your codebase works, and uses them during review. for each part of the codebase, it maintains a running list of past bugs. this way, the next time it reviews that part of the code, it knows what to look for. greptile catches 12.2% more bugs with knowledge bases enabled! now available to all users :)

Daksh Gupta

14,102 просмотров • 14 часов назад

AI is increasing the speed, density and complexity of work rather than reducing it, a new analysis shows. Read more:

AI is increasing the speed, density and complexity of work rather than reducing it, a new analysis shows. Read more:

The Wall Street Journal

47,801 просмотров • 5 месяцев назад

Bjarne Stroustrup (Creator of C++) on the costs of abstraction: "It's compiled away. This is why I talk about zero overhead abstraction. And people are beginning to take me to task for that because that's underestimating the ability of the C++ compiler. We can do negative overhead abstraction." Ryan: "What if you're really good at writing assembly and had all the time in the world to write it?" Bjarne: "If you are very smart and you have infinite time, you can do better. By and large, we are not as smart as the optimizers anymore, and we don't have infinite time."

Bjarne Stroustrup (Creator of C++) on the costs of abstraction: "It's compiled away. This is why I talk about zero overhead abstraction. And people are beginning to take me to task for that because that's underestimating the ability of the C++ compiler. We can do negative overhead abstraction." Ryan: "What if you're really good at writing assembly and had all the time in the world to write it?" Bjarne: "If you are very smart and you have infinite time, you can do better. By and large, we are not as smart as the optimizers anymore, and we don't have infinite time."

Ryan Peterman

145,117 просмотров • 3 месяцев назад