Top 10 Hacker News posts, summarized
HN discussion
(1499 points, 3571 comments)
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HN comments suggest significant international skepticism and concern regarding the reported events in Venezuela. Several users interpret the situation as a potential US invasion, drawing parallels to other military interventions and questioning the justifications. There is a notable discussion about the perceived hypocrisy of Western nations in supporting or justifying such actions, particularly in light of past statements about international law. Some comments express shock and condemnation of the reported violence, while others speculate on the strategic motivations, such as oil or geopolitical influence, and the potential ramifications for regional stability and international relations.
HN discussion
(346 points, 272 comments)
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The discussion highlights a general user dissatisfaction with Microsoft's recent changes regarding Windows activation. A recurring theme is the perceived increasing hostility of Microsoft products towards users, with specific criticisms directed at the push for online accounts and AI integration. This sentiment is leading several commenters to consider or confirm a switch to Linux for future installations. Some users recall past difficulties with offline activation methods, such as the tedious telephone process. There is also speculation about the implications for air-gapped systems and whether alternative, unofficial methods will emerge or remain viable.
HN discussion
(372 points, 78 comments)
The article "The Most Popular Blogs of Hacker News in 2025" analyzes the top individual bloggers featured on Hacker News for the year. Simon Willison secured the #1 spot for the third consecutive year, primarily due to his prolific and insightful commentary on AI, presented as a power user rather than a vendor pitch. Jeff Geerling, a popular YouTuber, came in at #2 by thoughtfully adapting his video content into well-structured blog posts that cater to HN's favored topics like Raspberry Pi and self-hosted software. Sean Goedecke, a Staff Software Engineer at GitHub, debuted at #3 with a strategy of sharing clear, often contrarian opinions on tech work, and effectively explaining complex organizational politics to engineers.
The list also highlights investigative journalist Brian Krebs at #4 for his cybersecurity reporting, which occasionally touched on political topics, and Neal Agarwal at #5 for his unique interactive art and visual essay blog posts. The article also notes other popular bloggers like John Gruber and Mahad Kalam, emphasizing the diverse content that resonates with the Hacker News audience.
HN users generally agreed with the top rankings, particularly Simon Willison's #1 position, with many commenting on the value of his approach to curating and discussing information from various platforms. A recurring theme was the community aspect, with users noting that many of the top bloggers are also active and thoughtful commenters on HN, contributing to a sense of connection.
There was also discussion about the methodology and the performance of other previously popular bloggers, with some noting a decline in visibility for individuals like Ben Thompson and Julia Evans. Some users also offered alternative interpretations of "blogging," suggesting that newsletters or other content formats, like J.B. Crawford's computer.rip, should be considered. The author of the article, Simon Willison, also provided a link to the underlying data, enabling further analysis and experimentation by the community.
HN discussion
(264 points, 160 comments)
The C3 programming language is presented as an evolution of C, aiming to retain familiarity for C programmers while introducing modern features. Key aspects include full C ABI compatibility for seamless integration into existing C/C++ projects, a straightforward module system, and expressive operator overloading designed for tasks like vector and matrix math. C3 also incorporates a powerful macro system that resembles functions, programming-by-contract for runtime and compile-time constraints, and a robust error handling mechanism that blends Result types with exception-like usability.
Further enhancing its appeal, C3 offers generic modules for simplified type creation, compile-time and runtime type introspection, inline assembly support, and comprehensive runtime checks in debug builds to catch bugs early. The language also provides detailed stack traces for debug builds, aiming to eliminate cryptic segmentation fault errors.
Commenters expressed a range of opinions and observations about C3. Several noted its similarities to other modern C-like systems languages such as Zig and Odin, with some questioning what unique problems C3 solves. The full C ABI compatibility was widely praised as a significant advantage, reducing the barrier to adoption by allowing direct integration into existing C codebases. The design philosophy of gradual evolution rather than revolution was appreciated by some, making it an accessible language to learn for C programmers.
There was also discussion about the potential for LLMs to drive adoption of languages like C3, with the idea that compilers could handle more of the heavy lifting in memory management. Some technical points were raised, including questions about its compilation target (LLVM) and the absence of certain features like tagged enums. One commenter pointed out a potential "foot gun" in the switch statement design, while another discussed the naming of its Result-like error handling as "Optional." The project's clean website design was also a positive point mentioned.
HN discussion
(241 points, 140 comments)
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A significant portion of the discussion revolves around the observed decline in Stack Overflow questions. The dominant theory posits that the rise of Large Language Models (LLMs) such as ChatGPT has directly contributed to this decline, with users now turning to AI for quick answers. Some commenters suggest that LLMs are a more efficient and accessible alternative for many programming queries.
However, other factors are also cited. Several users point to the perceived toxicity and strict moderation policies of the Stack Overflow community as a long-standing issue that predates the widespread adoption of AI. These factors reportedly made it difficult and uninviting for users to ask questions, leading some to seek better responses on platforms like Reddit or to abandon asking questions altogether. The sale of Stack Overflow to Prosus in 2021 is also mentioned as a potential contributing factor, with some suggesting a decline in the site's culture or direction prior to the AI surge.
HN discussion
(106 points, 36 comments)
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The discussion primarily revolves around the "X-Clacks-Overhead" HTTP header. Many commenters express appreciation for this custom header, often viewing it as a fun or whimsical addition to web responses. The header is frequently linked to a tribute to author Terry Pratchett, with the message "GNU Terry Pratchett" or similar phrases being common implementations. Several users share their own implementations of the header on their blogs or applications and discuss methods for detecting its presence, including browser extensions and the use of Shodan to identify sites broadcasting the header. There is also a brief mention of the deprecated "Report-To:" header.
HN discussion
(105 points, 19 comments)
The paper introduces Recursive Language Models (RLMs), a novel inference strategy designed to enable Large Language Models (LLMs) to process prompts significantly exceeding their inherent context window limitations. RLMs treat long prompts as an external environment that the LLM can interact with programmatically. This involves decomposing the prompt, examining its components, and recursively invoking the LLM on smaller snippets. Experiments demonstrate that RLMs can handle inputs up to two orders of magnitude larger than the model's context window. Furthermore, even for shorter prompts, RLMs show improved quality over base LLMs and existing long-context methods, with comparable or lower computational costs per query.
Commenters on Hacker News drew parallels between RLMs and existing techniques, with several suggesting it is similar to Retrieval Augmented Generation (RAG) or sub-agent architectures. A key point of discussion was whether the LLM's programmatic interaction with the prompt as an "environment" represented a fundamental difference from RAG, or if it was primarily about the LLM implementing the retrieval mechanism itself. There was also a sentiment that the core concept of recursively calling smaller models or agents to handle parts of a larger task is not entirely novel, likening it to "LLMs all the way down" or subagents. Interest was expressed in the practical implementation details and potential for integration with existing LLM tooling.
HN discussion
(60 points, 54 comments)
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The discussion revolves around the practicality and presentation of the project. Several users question the necessity of specific tools like Andronix or proot when simpler alternatives like Termux with nginx or lightweight HTTP servers on F-Droid exist for static site hosting. The title is criticized as disingenuous, with comments suggesting the $25 Walmart phone is subsidized and that other budget-friendly devices, like Raspberry Pis, could achieve similar results. There is also a debate regarding the role of Cloudflare Tunnel, with questions about whether Cloudflare acts as a CDN serving the site rather than the phone itself. A significant portion of the conversation addresses the use of AI (Claude Code) in the project, with users expressing skepticism about the author's claim of "vibe coding" when the setup was primarily generated by an LLM. Concerns are raised about the originality and potential copyright implications of presenting LLM-generated content as personal work. Additional comments touch upon the phone's potential as a remote webcam and its surprising lack of caching for a front-page-worthy project.
HN discussion
(76 points, 13 comments)
The author argues that while professional profilers are powerful tools, the simple act of hitting Ctrl-C in a debugger to examine a program's call stack can be surprisingly effective for diagnosing "stupid problems" often encountered by "lazy people operating in unfriendly environments." This method is presented as an accessible and often sufficient alternative to complex profilers, especially when dealing with issues like slow startup times or unexpected performance regressions that might be obscured by traditional profiling tools. The author illustrates this with anecdotes involving JSON parsing delays and linker performance issues, highlighting how Ctrl-C helped pinpoint the root causes.
Despite its strengths for simpler problems, the author acknowledges that Ctrl-C profiling, essentially a low-frequency sampling method, has limitations. It is less effective for subtle performance degradations spread across many functions, for diagnosing tail latency (infrequent but significant slowdowns), and for complex multi-threaded or distributed systems. The article concludes by giving a "warmest endorsement" to Ctrl-C profiling for its ease of use and effectiveness in many practical scenarios, while still recognizing the necessity of dedicated profilers for more advanced performance analysis.
Commenters generally agreed with the article's premise that Ctrl-C profiling is a useful and often underestimated technique for diagnosing simpler performance issues. Some shared personal anecdotes of similar methods they've employed, such as using SIGALRM or Xcode's debugger pause function, demonstrating its practical application across different environments and languages. The analogy to memory sampling techniques was also drawn, highlighting the common theme of observing a system in a "leaky" or "slow" state and then analyzing a snapshot.
However, several commenters cautioned that Ctrl-C profiling is not a replacement for learning proper profiling tools. They emphasized that it is a crude sampling method with inherent limitations, particularly for pinpointing issues that consume a smaller percentage of total runtime or for understanding nuanced performance changes. The consensus was that while Ctrl-C profiling is a valuable first step or a tool for specific situations, more sophisticated profilers like `perf` or Instruments are still essential for tackling complex performance optimization challenges.
HN discussion
(41 points, 26 comments)
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The discussion highlights significant concerns regarding the potential ecological impact of deep-sea mining. Several commenters point out that deep-sea ecosystems are extremely slow to recover, forming over millions of years. The discovery of "dark oxygen" generation by nodules, a process potentially crucial for deep-sea life, adds another layer of concern about the unknown consequences of mining. There is a prevalent sentiment that these activities are driven by profit with insufficient consideration for environmental preservation, especially when compared to the known damages of terrestrial mining. Some suggest that natural geological and biological events should be studied to better understand ecosystem resilience, questioning the necessity and ethics of introducing artificial destruction.
Commenters also touch upon the governance of deep-sea mining, with skepticism about the incentives for poorer nations and the historical precedents of destructive mining practices. The technical aspects of deep-sea mining are acknowledged as impressive, but this is contrasted with the ethical question of why such activities are permitted in international waters when they would not be in domestic ones. The debate is framed by some as a difficult choice between the known harms of land-based mining and the unknown, potentially irreversible, harms of deep-sea mining.
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