Eight Myths on Software Engineering and GenAI
Article URL: https://queue.acm.org/detail.cfm?id=3807963 Comments URL: https://news.ycombinator.com/item?id=49176830 Points: 279 # Comments: 239
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Article URL: https://queue.acm.org/detail.cfm?id=3807963 Comments URL: https://news.ycombinator.com/item?id=49176830 Points: 279 # Comments: 239
A credential-stealing worm hidden in more than 400 compromised npm packages automatically spread across software ecosystems by republishing malicious updates. This analysis details the attack chain, affected environments, and practical guidance for detection, hunting, and remediation. The post ChainDrop supply chain compromise: Anatomy of a self-propagating worm appeared first on Microsoft Security Blog.
OpenAI and Anthropic have confirmed that their AI models were involved in separate, newly disclosed third-party cybersecurity testing incidents that resulted in a real website being breached and social engineering attacks against people outside the intended testing boundaries. [...]
Sometimes you genuinely want Docker Engine as the Kubernetes node runtime — a team standardized on the Docker CLI/API for tooling, an image-build box that doubles as a node, or a legacy playbook you can't rewrite yet. Since dockershim was removed in Kubernetes 1.24, that path now runs through cri-dockerd, an open-source CRI adapter maintained by Mirantis. Here's how to set it up on Ubuntu, and an honest note on whether you should. For most people the answer is no — use containerd (see the previo
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Hace unas semanas empecé un proyecto personal con un objetivo simple: automatizar el proceso de cotización de una vidriería que hasta entonces armaba cada presupuesto a mano. Cálculos repetidos, formato distinto cada vez, cero historial ordenado. Terminó siendo bastante más de lo que imaginé al principio: un sistema completo de gestión de presupuestos, con catálogo de productos, múltiples precios por proveedor, cálculo de márgenes, exportación a PDF con el formato real que ya usaba el negocio, y
In part 1, we built the core stack/microtask/macrotask model. In part 2, we saw how the browser and Node implement that model differently — rendering interleaved with tasks in the browser, libuv's phase-based loop in Node. Both of those posts share an unspoken assumption: your callbacks are fast. A few milliseconds, do their thing, return, let the loop move on. But what happens when that assumption breaks? What happens when you genuinely need to do slow, CPU-bound work — and there's no I/O to wa
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