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Article URL: https://www.apply-tracker.com/en Comments URL: https://news.ycombinator.com/item?id=49206942 Points: 1 # Comments: 0

GitHub going down is part of engineering now, I made a skill that lets your agent check GitHub's status on failure instead of retry-looping. Comments URL: https://news.ycombinator.com/item?id=49206945 Points: 1 # Comments: 0

Article URL: https://www.nature.com/articles/s41586-026-10953-2 Comments URL: https://news.ycombinator.com/item?id=49207170 Points: 1 # Comments: 0

Article URL: https://deepmind.google/blog/weathernext-ai-model-achieves-breakthrough-in-forecasting-cyclones/ Comments URL: https://news.ycombinator.com/item?id=49207172 Points: 1 # Comments: 0

Security researchers say that Kimi K3, an open-weight model from China, wandered off to the internet in an attempt to cheat on a test it was given.

https://www.bbc.com/news/articles/c36d4376nd2o , https://archive.is/YDn6S Comments URL: https://news.ycombinator.com/item?id=49184355 Points: 213 # Comments: 43

https://www.githubstatus.com/uptime/br0l2tvcx85d Comments URL: https://news.ycombinator.com/item?id=49198302 Points: 383 # Comments: 309

Article URL: https://slayersclub.bethesda.net/en-US/news/quake-30th-anniversary-update Comments URL: https://news.ycombinator.com/item?id=49201930 Points: 285 # Comments: 145

https://ir.amd.com/news-events/press-releases/detail/1296/am... https://chatjimmy.ai/ Comments URL: https://news.ycombinator.com/item?id=49201970 Points: 609 # Comments: 453

Article URL: https://roge.onwrite.app/what-is-a-product Comments URL: https://news.ycombinator.com/item?id=49202690 Points: 26 # Comments: 10

Article URL: https://www.sciencedaily.com/releases/2026/08/260803080917.htm Comments URL: https://news.ycombinator.com/item?id=49202716 Points: 113 # Comments: 28

Article URL: https://www.aleksagordic.com/blog/vllm Comments URL: https://news.ycombinator.com/item?id=49202852 Points: 93 # Comments: 5

Article URL: https://www.troyhunt.com/welcoming-the-nepalese-government-to-have-i-been-pwned/ Comments URL: https://news.ycombinator.com/item?id=49203105 Points: 142 # Comments: 21

Author here. Background, for anyone who hasn't followed this fight: IBM's iron–sulfur SQD results (Sci. Adv. 2025) are one of the flagship "quantum computers are useful for chemistry now" claims, and a published critique (arXiv:2501.07231) argues the quantum samples never beat classical selected-CI at matched cost. That argument is still live. Both sides have been arguing about energies. Neither measured which electronic state these calculations actually converge to. So I measured it. ⟨S²⟩ comes...

https://www.reuters.com/world/new-mexico-court-orders-meta-p... https://www.theguardian.com/technology/2026/aug/06/new-mexic... https://www.kob.com/new-mexico/nm-court-orders-meta-to-pay-5... https://www.bbc.com/news/articles/cd7lz3wr2rlo https://www.wsj.com/tech/meta-ordered-to-pay-942-million-to-... Comments URL: https://news.ycombinator.com/item?id=49204352 Points: 188 # Comments: 116

Article URL: https://community.frame.work/t/framework-data-breach-discussion/83939 Comments URL: https://news.ycombinator.com/item?id=49206130 Points: 59 # Comments: 14

I got tired of doomscrolling 7 different AI news sources every morning, so I built an agent that does it for me for exactly $0/month. The pipeline: - 7 RSS feeds (Hacker News, Google AI blog, Hugging Face, Lobsters, The Hacker News, Open Source blog) → a Python script on a free-tier server - Dedup the same story hits 5 feeds; it picks the best source and drops the rest - An LLM writes 2-3 sentence summaries of the stories that actually matter - A cron job publishes a clean daily digest to ...

I made this project that lets you in your web browser help an AI think. It uses WASM or pure JS depending on your device to do some of the matrix multiplication for an AI. The more users, the better the math is shared, the faster layers get solved. The issue is that I don't have enough devices to test the server in most fronts besides "does it work." If you want to help, go to the site at https://ecthqmainserver.orfe-climb.ts.net/ . I am making this to test for weather it works on a ...

Agent incidents rarely look like a movie villain. They look like a helpful assistant combining two permissions you never meant to combine: a note-reader that can summarize a folder, plus a messenger that can post to a webhook, plus one poisoned paragraph in a document that says where the notes should go. After writing about prompt changes as migrations, I started treating tool permission the same way: as a reviewed contract, not a vibe in the system prompt. The pattern I keep reaching for is ...

A malicious Ollama model is not a virus you double click, but it is untrusted input handed to a C parser, a template engine and your filesystem in one request. The realistic damage from a hostile /api/pull is disk exhaustion, VRAM starvation, blob writes under ~/.ollama/models , a poisoned chat template that silently rewrites every prompt, and memory corruption in the GGUF loader if the file is crafted for it. None of that requires a vulnerability in your app code, only an Ollama daemon that ...

This is a submission for Frontend Challenge - Comfort Food Edition, Perfect Landing Mexico is our heritage. Yet, we have no family there to visit. That sounds sadder than it is. What it actually meant, for the years before my wife and I were married and most of our time off since, is that we had to go find it ourselves. No family kitchen waiting. No grandmother's recipe with an address attached. Just the two of us and a country that is ours and that we did not know. So we did what ev...

A few weeks ago I wrote about building a reproducible test harness for comparing free AI coding models before you commit . That harness answers one question: which model should I use? It does not answer the harder follow-up: once a model generates a patch for my real codebase, when is it safe to merge? This week there was a great discussion on DEV about "understanding over origin" — the idea that it doesn't matter whether code came from a human or a model, only whether someone actuall...

When people discuss AI agents escaping their boundaries, the mental image is usually dramatic: a jailbreak, a rogue prompt, an obvious disaster. What I've actually seen in practice is duller and more dangerous. The agent finishes its task successfully, the tests pass, and only later does someone notice it edited a file three directories up, or that a "helpful cleanup" deleted something it shouldn't have. Silent drift, not explosions. Last month I wrote about building a prompt regression harne...

📑 Table of Contents Introduction Why We Created ValidX? Why Choose ValidX? 5-Minute Quick Start Multilingual Support Important: Null/Empty String Handling Thread Safety Supported Validation Annotations Quick Reference Table Basic Validation Identity Validation Financial Validation Education/Professional Qualification Network Validation China-Specific Validation Automotive Validation Book-Related Validation Mobile Device Validation More Validation ...

If you're building — or integrating — a browser-based audio trimmer, the question that eventually reaches your inbox isn't "does it cut audio?" The real question is: does it cut audio correctly across the inputs we actually receive from users? That shift, from feature presence to behavior under fuzzy conditions, is what turns a demo into a product. This article walks through the QA matrix I use when reviewing client-side trimmers before release, with an emphasis on the silent failures that don...

An AI support agent does not have to be malicious to damage trust. It only has to answer one refund question, outage complaint, security concern, or enterprise renewal ticket with polished confidence and weak evidence. That is why serious builders need an AI support escalation router before they let agents send replies on their own. The router decides when the AI can answer, when it should draft only, when it should ask a clarifying question, and when a human must take over. The goal is ...

Classic Machine Learning Through the Eyes of an SRE — Part 3 The random forest is the first ML algorithm that made me feel at home. Not because of the math — because it's an SRE idea wearing a stats costume. Many independent workers. No single point of failure. Majority vote. If one worker goes weird, the fleet absorbs it. We've been building systems this way for decades; the forest just applies it to prediction. The problem it exists to fix Last article: a single decision tree is...

The Hidden Security Gap in Multi-Tenant MCP Servers When you build a multi-tenant SaaS application or an MCP (Model Context Protocol) server that serves multiple organizations, cross-tenant data leakage is one of the most dangerous vulnerabilities you can ship. A single missing organizationId filter in a database query can expose one tenant's data to another — and traditional security scanners like Snyk, Semgrep, and CodeQL don't catch these patterns. That's why I built mcp-tenant-is...