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For most of Linux gaming's history, the story has been the same: Linux users want to play games, game companies don't care about Linux users, and the community builds its own tools to bridge the gap. Valve changed that with Proton and the Steam Deck. But the storefronts held out. Epic, GOG, and Microsoft all stayed away from native Linux support, leaving their games accessible only through community-built launchers or not at all. That's changing. Three things happened this month that point to a tipping point. Epic Games is building a native Linux launcher In a Discord AMA reported by GamingOnLinux on August 14, 2026, an Epic Games developer confirmed that a native Linux version of the Epic Games Store launcher is coming "soon." Not for the preview release of the upcoming store overhaul, but after that. The developer's exact words, screenshotted from Discord: "Soon <-- but not for the preview release. As you can imagine, we need to do more than simply have a build of the launcher that can run natively on Linux." This isn't a vague promise from a community manager. It's a developer in an AMA saying the work is happening. Epic was also recently hiring a Security Engineer to champion Linux anti-cheat, which suggests broader plans for Linux support beyond just the launcher. The context matters. Epic has been the holdout. Tim Sweeney has historically been dismissive of Linux as a gaming platform, and Epic's anti-cheat (BattlEye, Easy Anti-Cheat) has been a recurring blocker for Linux compatibility even when games would otherwise run fine through Proton. A native launcher doesn't solve the anti-cheat problem, but it signals a shift in how Epic views the platform. GOG is working on a Linux version of GOG Galaxy GOG separately confirmed to GamingOnLinux that work is in progress on a Linux version of GOG Galaxy. No timeline, no details, just confirmation that it's happening. GOG is a smaller player than Epic, but they matter for a different reason: they're the DRM-free storef

If you use GitHub Copilot, Claude, Cursor or any other AI coding assistant to write production code, the legal ownership of what you ship is less settled than your licence agreement implies. The US Copyright Office ruled in January 2025 that purely AI-generated material is not copyrightable, and that prompts alone do not provide sufficient human control to earn protection. Code you wrote with heavy AI assistance sits in an uncertain middle ground: it may be copyrightable, it may not, and no court has drawn the line for software. The answer-first version: you probably do not own copyright in the portions of your code that an AI wrote without substantial human direction, and you may not be able to prove where the boundary lies. This does not mean someone else owns it — it may be uncopyrightable altogether, like a phone book. But your employment contract, your client agreement and your open-source licence all assume you hold full copyright in your deliverables. That assumption is now an open question. The rule, plainly stated Purely AI-generated output is not copyrightable in the United States. This is not a prediction or a legal opinion; it is the stated position of the US Copyright Office, set out in its January 2025 report Copyright and Artificial Intelligence, Part 2: Copyrightability . The report received over 10,000 public comments and represents the Office’s most comprehensive statement on the subject. Its conclusions are clear: “material generated wholly by AI is not copyrightable”, and existing law is adequate to handle the question without new legislation. The nuance sits in the middle ground — which is exactly where most AI-assisted coding lives. What the Copyright Office said The report draws several lines. First, it confirms the long-standing requirement that copyright requires a human author. An AI system cannot be an author, regardless of how sophisticated its output. Second, it addresses prompts: “based on the functioning of current generally available

En el día a día del desarrollo de software y el análisis de datos, la preparación y limpieza de archivos financieros suele ser una de las tareas más repetitivas y propensas a errores. Tratar con layouts rígidos, filas desfasadas y nombres de columnas que cambian sin previo aviso genera una fricción operativa constante. Para resolver este problema de raíz—y manteniendo un enfoque estricto en la seguridad de la información—desarrollé D-MO (Data Micro-Optimizer) , una potente herramienta web de procesamiento ETL (Extract, Transform, Load) que corre completamente del lado del cliente. El Origen: Privacidad por Diseño Cuando manejamos reportes bancarios o información financiera sensible, subirlos a plataformas externas de conversión representa un riesgo crítico de seguridad. D-MO nació bajo la premisa de la privacidad absoluta: todo el procesamiento ocurre en la memoria local del navegador a través del cliente. Los datos estructurados jamás se envían a un servidor externo, eliminando latencias de red y garantizando un entorno de zero server overhead . Arquitectura del Pipeline (Flujo de Datos) El sistema procesa la información de manera secuencial a través de un flujo desacoplado, lo que permite transformar archivos complejos en datasets listos para producción en un solo clic: [ Archivo Local ] (.csv / .xlsx / .xlsb) │ ▼ ┌──────────────┐ │ DropZone │ ◄── Validación de Extensión y Tamaño └──────┬───────┘ │ (Buffer / Texto plano) ▼ ┌──────────────┐ │ File Parser │ ◄── Detección de delimitadores y headers dinámicos └──────┬───────┘ │ (JSON Normalizado) ▼ ┌──────────────┐ │ ETL Engine │ ◄── Reglas de Negocio, Mapeo de Alias y Filtros CUSTOM └──────┬───────┘ │ (Dataset Limpio) ▼ ┌──────────────┐ │ Export File │ ◄── Generación de reportes limpios listos └──────────────┘ Core Técnico y Capas del Sistema La aplicación está construida sobre Next.js 14 (App Router) y TypeScript , dividiendo su lógica interna en tres componentes principales: 1. Interfaz y Coordinación ( page.tsx )

Introduction I did something stupid. I built a superhero-themed Nuxt app, connected it to an Anthropic model through Amazon Bedrock , and gave it a tool that deletes files from my computer. In fact, if I wasn't careful, it could have deleted all my files! The first time I tried it, I didn't use any sort of approval mechanism. And as you expected it just deleted things. Then I looked into how my coding agent works, and I learned about tool approvals. I learned that AI SDK 7 has a tool approval at the model-call level. It works by pausing for an approval, showing an approval window, and then deleting it. I then put Kiro CLI behind the same interface using Agent Client Protocol (ACP). Watch the full video on YouTube . Prerequisites You need: Node.js 22 or later. AI SDK 7 requires Node.js 22 and uses ECMAScript modules (ESM). npm 11 or another package manager that works with Nuxt 4. AWS credentials available through the standard provider chain. Access to an Amazon Bedrock model in your AWS Region. The AWS CLI if you want to list the inference profiles available to your account. An authenticated Kiro CLI installation for the optional ACP section. Step 1: Create the Nuxt app Create the project and install the versions used in the recorded demo: npx nuxi@latest init nuxt-agent-approval cd nuxt-agent-approval npm install \ nuxt@4.5.2 \ vue@3.5.41 \ ai@7.0.66 \ @ai-sdk/vue@4.0.66 \ @ai-sdk/amazon-bedrock@5.0.57 \ @aws-sdk/credential-providers@3.1111.0 \ @nuxt/ui@4.10.0 \ zod@4.4.3 npm install -D @iconify-json/lucide@1.2.123 Register Nuxt UI and expose the Amazon Bedrock settings through server-side runtime config: // nuxt.config.ts export default defineNuxtConfig ({ modules : [ ' @nuxt/ui ' ], css : [ ' ~/assets/css/main.css ' ], runtimeConfig : { awsRegion : process . env . AWS_REGION ?? ' us-west-2 ' , bedrockModelId : process . env . NUXT_BEDROCK_MODEL_ID } }) Add the two Nuxt UI imports: /* app/assets/css/main.css */ @import "tailwindcss" ; @import "@nuxt/ui" ; You can c

Cloudflare is introducing WriteGuard, now in private beta, to provide fine-grained security controls for MCP (Model Context Protocol) servers. It aims to make AI agents safer by controlling their access to tools that can modify data or perform actions, rather than simply read information. By Sergio De Simone

Battery materials startup Anthro Energy has broken ground on a Louisville factory to make electrolytes, including those for solid-state batteries.

Perplexity's India revenue rose about 60% after the Airtel offer ended for new users, even as downloads declined.

Secret parameter allowed hackers to steal passwords when a target clicked on a link.

Netflix open-sourced an agentic workflow for Observational Causal Inference (OCI) that reduces toil in causal analysis. Given observational data and the human user's analysis plan, the agent uses an actor-critic loop to estimate causality, write a report, and suggest next steps. By Anthony Alford

Reach Capital announced Tuesday an oversubscribed $265M Fund V.

SpaceXAI recently introduced Grok Bot, an always-on AI-agent service designed to work more like an autonomous teammate. The agents have their own cloud computer environment and can log into applications, websites and tools to perform multi-step tasks. They can also operate in parallel and coordinate with other agents. The product is entering a market that already includes competing agentic workplace products from OpenAI, Anthropic and Microsoft. Traditional chatbot: User ↓ Question ↓ LLM ↓ Answer And Now Agent: Goal ↓ LLM ↓ Plan ↓ Tool ↓ Observe ↓ Reason ↓ Tool ↓ Validate ↓ Continue ↓ Result * But there's a major problem : * Giving an AI agent access to: Email Slack GitHub CRM Cloud Browser Databases Internal documents creates a huge identity and security problem. An agent with permission to send an email or modify production infrastructure effectively becomes another privileged identity. About the Author -> I am Ashutosh Maurya , a Senior Full-Stack Developer ** with 6+ years of experience in high-performance UI development and the MERN stack. I specialize in building scalable architectures like Schooliko and **AI-integrated platforms . My goal is to bridge the gap between complex backend logic and seamless frontend experiences.

Most designers don't lose time in the design phase; they lose it in the tool-switching phase. You...

This year’s El Niño is shaping up to be the strongest on record. This is what impacts to expect and how bad it could get.

Many variables affect the value of retro game consoles today. Which ones are worth keeping, and which ones are destined for the trash?

Sonic Fire Protection raised its new funding to help get its sound-powered fire protection system into everything from commercial kitchens to apartment buildings.

How Linux file permissions actually work under the hood, why symbolic mode is your best friend, and how to stop blindly typing chmod 777. Every Linux engineer has been there. You write a brand-new bash script, try to run it from your terminal, and hit an immediate roadblock: $ ./backup.sh bash: ./backup.sh: Permission denied You open your search engine or ask a chat assistant for help. Within seconds, you find an answer that tells you to run: chmod 777 backup.sh You run the command, hit enter, and the script runs. Problem solved, right? Not quite. In fact, you just opened the digital front door of that file to every single user and background service on the entire operating system. When I started managing Linux servers years ago, permissions felt like a strange puzzle of three-digit math problems. People kept throwing numbers around: 755 for scripts, 644 for web pages, 600 for SSH keys, and 777 whenever something broke and nobody knew why. I memorized those numbers like cheat codes in a video game. But whenever I had to handle a real permission problem, like giving a development team write access to a shared log folder without letting them delete each other's files, memorized numbers fell apart. Here is the secret: you do not need to do binary math or memorize three-digit codes to master Linux permissions. Linux has a built-in, human-readable permission syntax called symbolic mode . Once you understand how Linux looks at files, who owns them, and what actions each permission controls, chmod becomes one of the most intuitive tools in your terminal. Let's break down how it all works step by step. 1. What chmod Actually Does The name chmod stands for change mode . In Unix and Linux systems, every single file and directory has a "mode". That mode determines who is allowed to read it, write to it, or run it. When you run chmod , you are simply updating those access bits inside the Linux filesystem inode. To see the current mode of your files, open any terminal and run ls

When I first got interested in cybersecurity, I thought it was all about tools. Nmap, Metasploit, Wireshark, Burp Suite. I downloaded them all, watched tutorials, and felt like a hacker. But the first time I tried to customize a scan or parse a weird log file, I hit a wall. I didn't know how to code. And in cybersecurity, that's like trying to be a chef without knowing how to use a knife. This article is for people who want to move beyond clicking buttons. Whether you're a beginner deciding where to start or a security analyst who wants to automate boring tasks, programming will change how you work. I'll cover why programming matters, what languages to learn, the concepts you'll actually use, projects to build, and how to think like both an attacker and a defender. Why programming isn't optional anymore Cybersecurity used to be more forgiving. You could run a vulnerability scanner, read the report, and call it a day. But threats have gotten more complex, and so have the defenses. Today, you need to: · Write scripts to analyze thousands of log lines in seconds. · Automate repetitive tasks like phishing email analysis or IP reputation checks. · Understand the code behind vulnerabilities so you can explain them to developers. · Build custom tools when existing ones don't fit your environment. · Test your own code for flaws before attackers find them. If you can't read or write code, you're limited to what someone else built. That's not a career; that's a hobby. Programming gives you the ability to solve problems no tool can solve out of the box. What "programming for cybersecurity" actually means It's not software engineering. You don't need to build a full web application or master design patterns. Instead, you use code as a tool for investigation, automation, and exploitation (ethically, of course). Different roles need different levels of programming: · SOC analysts might write Python scripts to correlate logs or query APIs. · Penetration testers write proof-of-conc

Filing comes after Elon Musk announced exclusive arrangement to kit out its data centers.

Lea's pushing back on light/dark mode implementations that display three state options for visitors: light, dark, and system. Dark mode toggles: two states are enough originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.

Grafana Labs has announced general availability for two tools that let AI coding agents query live observability data during development: the gcx CLI and the Grafana MCP server. Both allow agents to pull metrics, logs, traces, SLOs, and Synthetic Monitoring results from Grafana Cloud or a self-hosted stack By Claudio Masolo