Why Linus Torvalds, Bjarne Stroustrup, and Other Veteran Programmers Are Skeptical of AI‑Written Code
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation. Critics such as Bjarne Stroustrup, Linus Torvalds, and Vlad Mihalcea say AI output can be low qual...
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation.
Critics such as Bjarne Stroustrup, Linus Torvalds, and Vlad Mihalcea say AI output can be low quality or “almost right,” shifting work from writing code to reviewing and fixing it.
Their skepticism contrasts with tech executives predicting that AI could soon write most software or replace mid‑level developers.
How are veteran programmers like Bjarne Stroustrup, Linus Torvalds, and Java author Vlad Mihalcea criticizing AI-generated code, and why doAI coding assistants can generate code quickly, but experienced developers say the real work often lies in reviewing and correcting the output.
AI Prompt
Create a landscape editorial hero image for this Studio Global article: How are veteran programmers like Bjarne Stroustrup, Linus Torvalds, and Java author Vlad Mihalcea criticizing AI-generated code, and why do. Article summary: They are criticizing AI code mainly as low-quality, overhyped, and costly to supervise. In the reported remarks, Bjarne Stroustrup says AI often produces “rubbish code,” Linus Torvalds says he gets angry at claims that A. Topic tags: general, general web, user generated. Reference image context from search candidates: Reference image 1: visual subject "Title: Linus Torvalds Calls AI-Generated Code 'Slop' in Linux Kernel Debate # Linus Torvalds Calls AI-Generated Code ‘Slop’ in Linux Kernel Debate. Linus Torvalds bluntly dismissed" source context "Linus Torvalds Calls AI-Generated Code 'Slop' in Linux Kernel Debate" Reference image 2: visual subject "Title: Linus
openai.com
Artificial intelligence is rapidly becoming part of the modern software development workflow. Large technology companies increasingly promote AI coding assistants as tools that can dramatically accelerate programming or even automate large portions of software engineering.
But many veteran programmers are far more cautious. Experienced developers including C++ creator Bjarne Stroustrup, Linux creator Linus Torvalds, and Java author Vlad Mihalcea have publicly questioned both the quality of AI‑generated code and the size of its real productivity gains. Their criticism highlights a growing gap between corporate messaging about AI automation and how senior engineers see the technology in practice.
“Rubbish code”: Concerns about output quality
One of the most common criticisms from veteran programmers is that AI systems can produce code quickly but not reliably.
Bjarne Stroustrup has warned that AI tools often generate poor‑quality output that still requires experienced engineers to inspect and correct it. In reported remarks, he described much AI‑generated output as "rubbish code," arguing that it shifts work to senior developers who must review, repair, and maintain the results.
The core issue is not speed. AI systems can generate large volumes of code rapidly. The concern is that the resulting code may not follow good architecture, safety practices, or long‑term maintainability standards—areas where experienced engineers still need to intervene.
Linus Torvalds: AI is a tool, not the engineer
Linux creator Linus Torvalds has pushed back strongly against claims that AI can already write most production software.
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What is the short answer to "Why Linus Torvalds, Bjarne Stroustrup, and Other Veteran Programmers Are Skeptical of AI‑Written Code"?
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation.
What are the key points to validate first?
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation. Critics such as Bjarne Stroustrup, Linus Torvalds, and Vlad Mihalcea say AI output can be low quality or “almost right,” shifting work from writing code to reviewing and fixing it.
What should I do next in practice?
Their skepticism contrasts with tech executives predicting that AI could soon write most software or replace mid‑level developers.
Why Linus Torvalds, Bjarne Stroustrup, and Other Veteran Programmers Are Skeptical of AI‑Written Code
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation. Critics such as Bjarne Stroustrup, Linus Torvalds, and Vlad Mihalcea say AI output can be low qual...
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation.
Critics such as Bjarne Stroustrup, Linus Torvalds, and Vlad Mihalcea say AI output can be low quality or “almost right,” shifting work from writing code to reviewing and fixing it.
Their skepticism contrasts with tech executives predicting that AI could soon write most software or replace mid‑level developers.
How are veteran programmers like Bjarne Stroustrup, Linus Torvalds, and Java author Vlad Mihalcea criticizing AI-generated code, and why doAI coding assistants can generate code quickly, but experienced developers say the real work often lies in reviewing and correcting the output.
AI Prompt
Create a landscape editorial hero image for this Studio Global article: How are veteran programmers like Bjarne Stroustrup, Linus Torvalds, and Java author Vlad Mihalcea criticizing AI-generated code, and why do. Article summary: They are criticizing AI code mainly as low-quality, overhyped, and costly to supervise. In the reported remarks, Bjarne Stroustrup says AI often produces “rubbish code,” Linus Torvalds says he gets angry at claims that A. Topic tags: general, general web, user generated. Reference image context from search candidates: Reference image 1: visual subject "Title: Linus Torvalds Calls AI-Generated Code 'Slop' in Linux Kernel Debate # Linus Torvalds Calls AI-Generated Code ‘Slop’ in Linux Kernel Debate. Linus Torvalds bluntly dismissed" source context "Linus Torvalds Calls AI-Generated Code 'Slop' in Linux Kernel Debate" Reference image 2: visual subject "Title: Linus
openai.com
Artificial intelligence is rapidly becoming part of the modern software development workflow. Large technology companies increasingly promote AI coding assistants as tools that can dramatically accelerate programming or even automate large portions of software engineering.
But many veteran programmers are far more cautious. Experienced developers including C++ creator Bjarne Stroustrup, Linux creator Linus Torvalds, and Java author Vlad Mihalcea have publicly questioned both the quality of AI‑generated code and the size of its real productivity gains. Their criticism highlights a growing gap between corporate messaging about AI automation and how senior engineers see the technology in practice.
“Rubbish code”: Concerns about output quality
One of the most common criticisms from veteran programmers is that AI systems can produce code quickly but not reliably.
Bjarne Stroustrup has warned that AI tools often generate poor‑quality output that still requires experienced engineers to inspect and correct it. In reported remarks, he described much AI‑generated output as "rubbish code," arguing that it shifts work to senior developers who must review, repair, and maintain the results.
The core issue is not speed. AI systems can generate large volumes of code rapidly. The concern is that the resulting code may not follow good architecture, safety practices, or long‑term maintainability standards—areas where experienced engineers still need to intervene.
Linus Torvalds: AI is a tool, not the engineer
Linux creator Linus Torvalds has pushed back strongly against claims that AI can already write most production software.
Studio Global AI
Continue your research
This page includes a source-backed answer you can continue inside Studio Global.
What is the short answer to "Why Linus Torvalds, Bjarne Stroustrup, and Other Veteran Programmers Are Skeptical of AI‑Written Code"?
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation.
What are the key points to validate first?
Veteran programmers argue AI coding tools mainly produce draft code that still requires heavy human review, debugging, and integration—so real productivity gains are often marginal despite claims of massive automation. Critics such as Bjarne Stroustrup, Linus Torvalds, and Vlad Mihalcea say AI output can be low quality or “almost right,” shifting work from writing code to reviewing and fixing it.
What should I do next in practice?
Their skepticism contrasts with tech executives predicting that AI could soon write most software or replace mid‑level developers.
Torvalds has said he becomes frustrated when developers claim that "99%" of their code is written by AI. In his view, AI can be helpful but should still be treated strictly as a tool rather than a replacement for human engineers.
He argues that AI may change how programmers work, but it does not change the fundamental realities of software development—such as understanding systems, designing architecture, and making judgment calls that automated systems struggle to handle.
Why the productivity gains may be smaller than advertised
Java performance expert and author Vlad Mihalcea has emphasized a different point: even when AI generates working code, the net productivity gains may be modest once the full development process is considered.
Writing code is only one part of software engineering. Developers still must:
verify correctness
debug edge cases
integrate code into larger systems
ensure maintainability and security
If AI output is "almost right," engineers still spend time validating and fixing it. Mihalcea argues that after accounting for this extra work, the real productivity improvements may be marginal.
Industry surveys support this concern. In the 2025 Stack Overflow developer survey, 66% of developers said they spend more time fixing AI‑generated code that is nearly correct but not quite, and "almost‑right" answers were the most frequently reported frustration.
Some research has even found experienced developers completing tasks about 19% slower when using AI tools, despite believing they were working faster.
The corporate narrative: AI engineers and automation
While many veteran programmers emphasize limitations, technology executives often highlight AI’s potential to transform software development.
Several companies are heavily investing in AI coding tools and automation systems. Meta CEO Mark Zuckerberg has suggested that AI could soon perform work comparable to a mid‑level software engineer, potentially writing significant portions of code inside the company.
More broadly, leaders across the industry have predicted that AI might eventually generate most software. Some executives have suggested AI could write the majority of code within a few years, fueling speculation about automation of junior developer roles.
Amazon is also investing heavily in AI development and infrastructure, with CEO Andy Jassy arguing that artificial intelligence will reinvent many digital experiences and reshape how companies build technology products.
The real disagreement: what “productivity” means
The debate is less about whether AI helps developers and more about how its impact should be measured.
Technology companies often focus on output speed: how quickly tools can generate code or help small teams ship features.
Veteran engineers, however, evaluate productivity across the full lifecycle of software:
system design
correctness and reliability
security
debugging and testing
long‑term maintenance
When these factors are included, rapid code generation alone may not translate into equally large productivity gains.
The likely middle ground
Most experienced developers do not argue that AI is useless. Instead, they see it as a powerful assistant—especially for boilerplate code, prototypes, and documentation.
But they caution that software engineering remains far more than typing code. Architecture, judgment, debugging, and system understanding remain deeply human tasks.
For now, the emerging consensus among veteran programmers is that AI is changing how developers work—but not eliminating the need for experienced engineers anytime soon.
stackoverflow.blog
Developers remain willing but reluctant to use AI - StackOverflow Blog
Torvalds has said he becomes frustrated when developers claim that "99%" of their code is written by AI. In his view, AI can be helpful but should still be treated strictly as a tool rather than a replacement for human engineers.
He argues that AI may change how programmers work, but it does not change the fundamental realities of software development—such as understanding systems, designing architecture, and making judgment calls that automated systems struggle to handle.
Why the productivity gains may be smaller than advertised
Java performance expert and author Vlad Mihalcea has emphasized a different point: even when AI generates working code, the net productivity gains may be modest once the full development process is considered.
Writing code is only one part of software engineering. Developers still must:
verify correctness
debug edge cases
integrate code into larger systems
ensure maintainability and security
If AI output is "almost right," engineers still spend time validating and fixing it. Mihalcea argues that after accounting for this extra work, the real productivity improvements may be marginal.
Industry surveys support this concern. In the 2025 Stack Overflow developer survey, 66% of developers said they spend more time fixing AI‑generated code that is nearly correct but not quite, and "almost‑right" answers were the most frequently reported frustration.
Some research has even found experienced developers completing tasks about 19% slower when using AI tools, despite believing they were working faster.
The corporate narrative: AI engineers and automation
While many veteran programmers emphasize limitations, technology executives often highlight AI’s potential to transform software development.
Several companies are heavily investing in AI coding tools and automation systems. Meta CEO Mark Zuckerberg has suggested that AI could soon perform work comparable to a mid‑level software engineer, potentially writing significant portions of code inside the company.
More broadly, leaders across the industry have predicted that AI might eventually generate most software. Some executives have suggested AI could write the majority of code within a few years, fueling speculation about automation of junior developer roles.
Amazon is also investing heavily in AI development and infrastructure, with CEO Andy Jassy arguing that artificial intelligence will reinvent many digital experiences and reshape how companies build technology products.
The real disagreement: what “productivity” means
The debate is less about whether AI helps developers and more about how its impact should be measured.
Technology companies often focus on output speed: how quickly tools can generate code or help small teams ship features.
Veteran engineers, however, evaluate productivity across the full lifecycle of software:
system design
correctness and reliability
security
debugging and testing
long‑term maintenance
When these factors are included, rapid code generation alone may not translate into equally large productivity gains.
The likely middle ground
Most experienced developers do not argue that AI is useless. Instead, they see it as a powerful assistant—especially for boilerplate code, prototypes, and documentation.
But they caution that software engineering remains far more than typing code. Architecture, judgment, debugging, and system understanding remain deeply human tasks.
For now, the emerging consensus among veteran programmers is that AI is changing how developers work—but not eliminating the need for experienced engineers anytime soon.
stackoverflow.blog
Developers remain willing but reluctant to use AI - StackOverflow Blog
