Will some programmers become "AI babysitters"? asks long-time Slashdot readertheodp. They share some thoughts from a founding member of Code.org and former Director of Education at Google: "AI may allow anyone to generate code, but only a computer scientist can maintain a system," explained Google.org Global Head Maggie Johnson in a LinkedIn post. So "As AI-generated code becomes more accurate and ubiquitous, the role of the computer scientist shifts from author to technical auditor or expert. "While large language models can generate functional code in milliseconds, they lack the contextual judgment and specialized knowledge to ensure that the output is safe, efficient, and integrates correctly within a larger system without a person's oversight. [...] The human-in-the-loop must possess the technical depth to recognize when a piece of code is sub-optimal or dangerous in a production environment. [...] We need computer scientists to perform forensics, tracing the logic of an AI-generated module to identify logical fallacies or security loopholes. Modern CS education should prepare students to verify and secure these black-box outputs." The NY Times reports that companies are already struggling to find engineers to review the explosion of AI-written code.

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"Rust's rise shows signs of slowing," argues the CEO of TIOBE. Back in 2020 Rust first entered the top 20 of his "TIOBE Index," which ranks programming language popularity using search engine results. Rust "was widely expected to break into the top 10," he remembers today. But it never happened, and "That was nearly six years ago...." Since then, Rust has steadily improved its ranking, even reaching its highest position ever (#13) at the beginning of this year. However, just three months later, it has dropped back to position #16. This suggests that Rust's adoption rate may be plateauing. One possible explanation is that, despite its ability to produce highly efficient and safe code, Rust remains difficult to learn for non-expert programmers. While specialists in performance-critical domains are willing to invest in mastering the language, broader mainstream adoption appears more challenging. As a result, Rust's growth in popularity seems to be leveling off, and a top 10 position now appears more distant than before. Or, could Rust's sudden drop in the rankings just reflect flaws in TIOBE's ranking system? In January GitHub's senior director for developer advocacy argued AI was pushing developers toward typed languages, since types "catch the exact class of surprises that AI-generated code can sometimes introduce... A 2025 academic study found that a whopping 94% of LLM-generated compilation errors were type-check failures." And last month Forbes even described Rust as "the the safety harness for vibe coding." A year ago Rust was ranked #18 on TIOBE's index — so it still rose by two positions over the last 12 months, hitting that all-time high in January. Could the rankings just be fluctuating due to anomalous variations in each month's search engine results? Since January Java has fallen to the #4 spot, overtaken by C++ (which moved up one rank to take Java's place in the #3 position). Here's TIOBE's current estimate for the 10 most popularity programming languages: PythonCC++JavaC#JavaScriptVisual BasicSQLRDelphi/Object Pascal TIOBE estimates that the next five most popular programming languages are Scratch, Perl, Fortran, PHP, and Go.

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Grady Martin writes: A security researcher has leaked a complete repository of source code for Anthropic's flagship command-line tool. The file listing was exposed via a Node Package Manager (npm) mapping, with every target publicly accessible on a Cloudflare R2 storage bucket. There's been a number of discoveries as people continue to pore over the code. The DEV Community outlines some of the leak's most notable architectural elements and the key technical choices: Architecture Highlights The Tool System (~40 tools): Claude Code uses a plugin-like tool architecture. Each capability (file read, bash execution, web fetch, LSP integration) is a discrete, permission-gated tool. The base tool definition alone is 29,000 lines of TypeScript. The Query Engine (46K lines): This is the brain of the operation. It handles all LLM API calls, streaming, caching, and orchestration. It's by far the largest single module in the codebase. Multi-Agent Orchestration: Claude Code can spawn sub-agents (they call them "swarms") to handle complex, parallelizable tasks. Each agent runs in its own context with specific tool permissions. IDE Bridge System: A bidirectional communication layer connects IDE extensions (VS Code, JetBrains) to the CLI via JWT-authenticated channels. This is how the "Claude in your editor" experience works. Persistent Memory System: A file-based memory directory where Claude stores context about you, your project, and your preferences across sessions. Key Technical Decisions Worth Noting Bun over Node: They chose Bun as the JavaScript runtime, leveraging its dead code elimination for feature flags and its faster startup times. React for CLI: Using Ink (React for terminals) is bold. It means their terminal UI is component-based with state management, just like a web app. Zod v4 for validation: Schema validation is everywhere. Every tool input, every API response, every config file. ~50 slash commands: From /commit to /review-pr to memory management -- there's a command system as rich as any IDE. Lazy-loaded modules: Heavy dependencies like OpenTelemetry and gRPC are lazy-loaded to keep startup fast.

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An anonymous reader quotes a report from Ars Technica: Since Andrej Karpathy coined the term "vibe coding" just over a year ago, we've seen a rapid increase in both the capabilities and popularity of using AI models to throw together quick programming projects with less human time and effort than ever before. One such vibe-coded project, Gaming Alexandria Researcher, launched over the weekend as what coder Dustin Hubbard called an effort to help organize the hundreds of scanned Japanese gaming magazines he's helped maintain at clearinghouse Gaming Alexandria over the years, alongside machine translations of their OCR text. A day after that project went public, though, Hubbard was issuing an apology to many members of the Gaming Alexandria community who loudly objected to the use of Patreon funds for an error-prone AI-powered translation effort. The hubbub highlights just how controversial AI tools remain for many online communities, even as many see them as ways to maximize limited funds and man-hours. "I sincerely apologize," Hubbard wrote in his apology post. "My entire preservation philosophy has been to get people access to things we've never had access to before. I felt this project was a good step towards that, but I should have taken more into consideration the issues with AI." "I'm very, very disappointed to see [Gaming Alexandria], one of the foremost organizations for preserving game history, promoting the use of AI translation and using Patreon funds to pay for AI licenses," game designer and Legend of Zelda historian Max Nichols wrote in a post on Bluesky over the weekend. "I have cancelled my Patreon membership and will no longer promote the organization." Nichols later deleted his original message (archived here), saying he was "uncomfortable with the scale of reposts and anger" it had generated in the community. However, he maintained his core criticism: that Gemini-generated translations inevitably introduce inaccuracies that make them unreliable for scholarly use. In a follow-up, he also objected to Patreon funds being used to pay for AI tools that produce what he called "untrustworthy" translations, arguing they distort history and are not valid sources for research. "... It's worthless and destructive: these translations are like looking at history through a clownhouse mirror," he added.

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Tony Hoare, the Turing Award-winning pioneer who created the Quicksort algorithm, developed Hoare logic, and advanced theories of concurrency and structured programming, has died at age 92. News of his passing was shared today in a blog post. The site I Programmer also commemorated Hoare in a post highlighting his contributions to computer science and the lasting impact of his work. Personal accounts have been shared on Hacker News and Reddit. Many Slashdotters may know Hoare for his aphorism regarding software design: "There are two ways of constructing a software design: One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies. The first method is far more difficult."

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OpenAI is reportedly developing a code-hosting platform that could compete with GitHub, The Information reported on Tuesday. "If OpenAI does sell the product, it would mark a bold move by the creator of ChatGPT to compete directly against Microsoft, which holds a significant stake in the firm," notes Reuters. From the report: Engineers from OpenAI encountered a rise in service disruptions that rendered GitHub unavailable in recent months, which ultimately prompted the decision to develop the new product, the report said. The OpenAI project is in its early stages and likely will not be completed for months, according to The Information. Employees working on it have considered making the code repository available for purchase to OpenAI's customer base.

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"At its peak in early 2014, Stack Overflow received more than 200,000 questions per month," notes the site DevClass.com. But in December they'd just 3,862 questions were asked — a 78 percent drop from the previous year. But Stack Overflow's blog announced a beta of "a redesigned Stack Overflow" this week, noting that at July's WeAreDevelopers conference they'd "committed to pushing ourselves to experiment and evolve..." Over the past year, on the public platform, we introduced new features, including AI Assist, support for open-ended questions, enhancements to Chat, launched Coding Challenges, created an MCP server [granted limited access to AI agents and tools], expanded access to voting and comments, and more. However, these launches are not standalone features. We have also been rethinking our look and feel, how people engage with Stack Overflow, and how content is created and shared. These new features, along with the redesign, represent how we are bringing Stack Overflow's new vision to life and delivering value that developers cannot find elsewhere. Our goal is to build the space for every technical conversation, centered on real human-to-human connection and powered by AI when it helps most. To support this, we are introducing a redesigned Stack Overflow to best reflect this direction... During the beta period, users can visit the beta site at beta.stackoverflow.com and share feedback as we build towards a new experience on Stack Overflow. They've updated their library of reusable UI components (buttons, forms, etc.), and are promising "More ways to share knowledge and ask any technical question." ("Alongside looking for the single right answer to your question, you can now find and share experience-based insights and peer recommendations...") They're launching all the planned features and functionality in April, when "More users will automatically redirect to the new site." (Starting in April users "can continue to toggle back to the classic site for a limited time.")

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An anonymous reader shares a report: Microsoft Azure CTO Mark Russinovich and VP of Developer Community Scott Hanselman have written a paper arguing that senior software engineers must mentor junior developers to prevent AI coding agents from hollowing out the profession's future skills base. The paper, Redefining the Engineering Profession for AI, is based on several assumptions, the first of which is that agentic coding assistants "give senior engineers an AI boost... while imposing an AI drag on early-in-career (EiC) developers to steer, verify and integrate AI output." In an earlier podcast on the subject, Russinovich said this basic premise -- that AI is increasing productivity only for senior developers while reducing it for juniors -- is a "hot topic in all our customer engagements... they all say they see it at their companies." [...] The logical outcome is that "if organizations focus only on short-term efficiency -- hiring those who can already direct AI -- they risk hollowing out the next generation of technical leaders," Russinovich and Hanselman state in the paper.

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