Stanford University has chosen to continue its policy of giving admissions preference to children of alumni and donors, despite new California legislation prohibiting such legacy or donor preferences at private universities that receive state funds. To circumvent Assembly Bill 1780’s requirements, Stanford will exit the state-funded Cal Grant financial aid program starting with the fall 2026 admissions cycle, instead pledging to internally fund student financial aid to maintain support for affected students. This maneuver allows Stanford to sustain legacy admissions without violating the new law, which mandates annual reporting of compliance but imposes no substantive penalties for noncompliance.

The move comes amid growing scrutiny of admissions practices nationally, particularly following the Supreme Court’s 2023 decision to ban race-based affirmative action. Legacy admissions, which disproportionately benefit white and privileged applicants, are seen by critics as perpetuating inequality, with recent data showing that legacy admits at top universities like Stanford can exceed the share of admitted Black students. While California’s new law follows similar bans in other states, it lacks punitive enforcement, and Stanford’s response highlights the complicated financial relationships between private universities and public funding sources. The university asserts that alumni and donor support are vital for institutional sustainability, even as advocacy groups argue that such policies undermine inclusivity and meritocracy.

Hacker News commenters largely characterized Stanford’s decision as a defense of entrenched privilege, with the prevailing sentiment critical of the university’s willingness to forego public aid rather than abolish legacy preference. Discussion focused on the ethics of legacy admissions, the effectiveness of weak enforcement mechanisms in legislation, and the potential impact on student diversity and university finances. Some users pointed out the broader context of admissions inequities, while others debated whether heightened transparency or sharper penalties would meaningfully address perceived unfairness in the college admissions process.

Debian 13, codenamed "trixie," is a significant new stable release delivering broad architecture support—now officially including riscv64—and nearly 70,000 packages after over two years of community-driven development. This release continues the project's tradition of prioritizing stability, versatility, and security, promising five years of support across a spectrum of devices and deployments. Among notable changes, the longstanding i386 installer and armel architectures see their final regular release, reflecting the project's efforts to adapt to evolving hardware while maintaining dependable service for most users.

The update features over 14,000 new packages and key updates to core software like Linux kernel 6.12 (LTS), GNOME 48, KDE Plasma 6.3, GCC 14.2, and Python 3.13, demonstrating Debian's capacity to balance conservatism with modernity. Installation and upgrade experiences have been streamlined, with improved support for secure boot, enhanced accessibility, and live images offering a variety of desktop environments. Progress toward reproducible builds, aided by new verification tooling, reinforces trust in package integrity and build transparency—highlighting Debian’s ongoing commitment to security best practices.

Hacker News discussion reflects broad respect for the project's rigor and longevity, with particular attention to the official riscv64 support and the milestone of dropping i386. Community members acknowledge both the technical and symbolic importance of these decisions—marking the end of an era for legacy hardware while expanding into new, open-architecture territory. The overall commentary demonstrates appreciation for Debian's stability and inclusiveness, with debates centering on package management philosophy, reproducibility, and the practicalities of upgrading—underscoring Debian’s status as an anchor in the Linux ecosystem.

A recent working paper analyzing California’s mandated $20 minimum wage for fast food workers finds a statistically significant reduction in fast food employment following the law’s implementation in April 2024. The authors estimate a 2.7% decline in jobs over a year, which adjusts to about 3.2% after accounting for prior employment trends—culminating in a median loss of approximately 18,000 fast food positions when compared to what might have occurred without the wage increase. This empirical assessment utilizes detailed data from the Quarterly Census of Employment and Wages and controls for changes in industries less affected by minimum wage policy.

The study’s methodology emphasizes specificity by isolating fast food employment and benchmarking against similarly unaffected sectors to refine its findings. Notably, the decline is more pronounced when controlling for changes outside fast food, suggesting the policy’s impact is sector-targeted rather than reflective of broader economic conditions. The authors situate their results within ongoing policy debates, acknowledging nuanced arguments about wage floors: while minimum wage hikes intend to improve living standards, the evidence here supports concerns about possible negative employment effects, especially in sectors with thin profit margins and high labor cost sensitivity.

Hacker News commenters engaged vigorously with the findings, highlighting divides between those who see the results as confirmation of classic economic predictions and those questioning causality or broader relevance. Some users pointed to automation, price increases, and business adaptation as confounding factors, while others stressed the role of legislative intent—balancing better pay against job loss. One recurring perspective, marked by skepticism, challenged the generalizability of the results or cited alternative studies that found minimal or no negative employment effect from wage hikes. The discussion underscores the deeply contentious and unsettled nature of minimum wage policy debates, especially in high-cost states like California.

The featured web service delivers a real-time simulation of the sky’s color at your approximate location using only CSS gradients, updating automatically every minute without client-side JavaScript. By leveraging scientific models—atmospheric absorption and scattering coefficients—the site achieves a visually convincing depiction of current sky conditions. This minimalist yet dynamic approach underscores the potential of modern web standards to provide engaging, data-driven visuals while maintaining efficiency and privacy.

The simulation’s accuracy draws from atmospheric physics principles, notably Rayleigh scattering, to compute color gradients that mimic the natural sky under various lighting conditions. The underlying implementation uses server-side logic to determine geolocation through IP and applies established scientific formulas to model sunlight, atmospheric particles, and diffusion before returning CSS gradient parameters. The project’s open-source release on GitHub encourages examination and adaptation by web developers interested in blending scientific visualization and efficient front-end design.

Hacker News commenters express admiration for the technical rigor and simplicity of the approach, contrasting it with industry anecdotes where visually realistic sky simulations were ultimately replaced by plain blue rectangles to favor usability. The discussion highlights a recurring tension between realism and clarity in UI design, along with kudos for avoiding client-side scripting. The community also provides insight on geolocation methodology, infrastructure choices, and the creative possibilities accessible when scientific modeling is brought to lightweight web applications.

The article presents a software engineer’s unvarnished critique of conventional tech hiring processes, emphasizing that respect for candidates is the single greatest differentiator in attracting and retaining top engineering talent. The piece asserts that most interview formats—particularly live coding and take-home assignments—either waste candidates’ time, fail to model real job tasks, or can be easily gamed by AI, thus failing to distinguish truly senior engineers from those with superficial skills. The central argument is that interviews should mirror authentic job duties, differentiate senior from junior talent, gauge long-term fit, and, above all, value candidates' time as much as the company’s.

Building on this, the author highlights code review interviews as a standout method. Unlike other formats, code reviews reverse the usual time imbalance by requiring the interviewer to prepare code, while candidates critique and discuss it collaboratively, revealing their technical depth, communication style, and design intuition. The article also advocates for blending code review with structured conversations about real project work, and ensuring candidates meet prospective managers—on the premise that “people don’t quit jobs, they quit bosses.” These concrete changes are posited as offering a fairer, more predictive, and more humane approach to technical hiring, moving away from outdated gatekeeping rituals.

Hacker News commenters largely echo the author’s frustrations, with many declaring that current industry-standard coding interviews are deeply broken—failing to find the best engineers and actively driving them away. Several participants underscore the value of code review as an interview tool, suggesting it better exposes a candidate’s technical “taste,” collaboration skills, and genuine expertise. Others warn that the ongoing “arms race” with AI-driven cheating in conventional interviews is futile. A recurring thread among the comments is the call for shorter, more respectful processes, and serious reflection on what interviews are supposed to measure, with the highest praise reserved for approaches that value mutual respect and real teamwork over theatrical problem-solving.