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If you have ever pointed a coding agent at a multi-day goal, you know the failure mode. It is not that the model writes a bad function. It is that on turn 40, the agent no longer remembers what the objective was, which decision you already made, what is out of scope, or what the last run actually proved. The context window rolled over, and the plot went with it. LoopX is an attempt to fix that specific problem. It calls itself "loop engineering for long-running AI agents," and it is a local control plane that sits above your agent runtime rather than replacing it. The one-sentence version Your agent (Codex, Claude Code, Cursor, whatever) executes bounded loops. Something (a heartbeat, a cron job, you hitting enter) triggers the next loop. LoopX holds the state that has to survive between those loops. The project draws the separation like this: Layer Role Codex / Claude Code / Cursor Execute a bounded agent loop: read, write, run commands, respond Goal mode / automation / CLI / TUI Trigger or schedule the next loop LoopX Preserve goals, gates, todos, run history, quota, evidence, handoff state That third row is the whole product. LoopX is not an executor and not an autonomous production controller. It is a state kernel with a CLI. Why "just use a todo file" isn't enough A TODO.md plus a long system prompt gets you surprisingly far. It falls over once any of these become true: The goal changed halfway through, and nothing recorded why . A decision genuinely needs a human, and that request evaporated into a chat message nobody read. Two agents are touching the same repo and neither knows who owns what. The last run claimed success, and there is no artifact proving it. Some work is safe and read-only, some crosses into writes, production, or private data, and the distinction lives only in your head. LoopX makes those things explicit and machine-readable, which is what lets a loop run longer without becoming less accountable. The concepts, in plain English Lifetime goals

I needed a VPS to run CyberPanel. Simple enough: 1 vCPU, 1 GB RAM, 10 GB SSD, IPv6 only. CyberPanel...

JioHotstar explains the distributed architecture behind its real-time ad request workflow, covering ad decisioning, waterfall tiering, pacing algorithms, latency optimization, and service coordination required to select and deliver personalized advertisements during streaming playback at scale. By Leela Kumili

This is disturbing: …a team of security researchers at UC San Diego, who found that a model of aftermarket car alarm known as the KARR Security System, installed in more than 2 million vehicles across the US by their estimate, can let any hacker within Bluetooth range send radio commands to silently unlock the car at will, turn off its alarm, honk the car’s horn or flash its lights, or even disable its ignition and leave a driver stranded.

If you've experimented with AI-driven testing, you've probably lived this cycle: you ask an AI agent to "test the checkout flow," and it does something — clicks around, declares success, and leaves you unsure what was actually verified. The next day you ask again and it does something different. The browser automation works; the testing discipline is missing. That gap is what Snagly is for. Rather than describe it, I pointed it at softwaretestingtrends.com — my own production site, nothing fixed beforehand — and recorded the whole thing. It found eleven issues, including a critical accessibility bug on my own signup page. One of its findings turned out to be wrong, and I'll come back to that, because it matters more than the ones it got right. 📺 Watch the full walkthrough — installed from an empty folder, run against production, ~20 minutes. What it is Snagly is a free, MIT-licensed set of 30 skills for AI coding agents — GitHub Copilot , Claude Code , Cursor, Codex and 70+ others — that turn "an AI that can drive a browser" into "an AI that tests like a QA professional." A skill, if you haven't met them yet, is a reusable instruction set that teaches the agent a specific working method — when to use it, what rigor it requires, what evidence to capture, and what it must never do. Each skill in Snagly has one job, and they hand off to each other the way a real testing practice does: start-testing is the front door — say "what can you test here?" and it routes you to the right skill, checking prerequisites before handing off. Discovery & strategy : scenario-mapper explores your site and produces a prioritized list of test scenarios; test-case-writer expands any of them into a reviewable spec; test-plan sets strategy, cadence, and release exit criteria; qa-onboarding writes the guide for your next hire. Execution : flow-runner drives real user journeys step by step, asserting outcomes (not just that clicks happened) and capturing evidence the moment anything fails. cru

I’m an omnivore. Purple Carrot’s vegan meal kit offers some of the best cooking I’ve seen from any meal kit, with or without meat.

This essay originally appeared in Foreign Policy . Earlier this month, two of OpenAI’s models broke out of their containment sandbox and attacked another AI company. The story is kind of wild . OpenAI was running security tests on two of its models: GPT-5.6 Sol and an unreleased model that is almost certainly GPT-6. In particular, it was running the ExploitGym benchmark, which measures how good a model is at turning security vulnerabilities into working exploits: basically, offensive cyberattacks. Since these were internal tests, OpenAI locked those models in a secure sandbox that denied them access to the internet. But it was running the models without any safety filters that would prevent them from offensive cyber-actions. That meant that there was nothing to prevent the models from trying to ...

Whether you want an audio player that’ll grow with your kid or one that your toddler can operate independently, I have a recommendation for you.

In June 2026, Peter Steinberger reported that his system spent $1,305,088.81 over 30 days and...

Two weeks ago, I published "Why Agent Evaluation Is Harder Than Model Evaluation." The core argument:...

Ship a compliant cookie banner in Laravel and actually gate analytics and marketing scripts on the user's choice, using the wirecookies-saved event and a plain localStorage object as the consent gate. Wirecookies is a Laravel package which handles the cookies consent for you. It gives you a consent banner and a preferences modal from a single Blade tag, and, more usefully, it hands you a plain localStorage object and a browser event you can use as the gate for your analytics and marketing scripts. This article is built around that gate, not around how the banner looks. One thing to get out of the way first, because it will bite you otherwise: Wirecookies ships no JavaScript of its own and uses wiremodal's JS to open the preferences modal. If you skip the wiremodal import in the install steps, the banner still shows and Accept all / Reject all still work, but the Configure button and the floating re-open button silently do nothing, with no error in the console. Do the JS step. How to install Pull the package in with Composer. The service provider is auto-discovered, so there is nothing to register. composer require edulazaro/wirecookies Wirecookies depends on edulazaro/wiremodal , which Composer pulls in for you. Now import the stylesheet in resources/css/app.css , after a wire* base (wiremodal or wiretoast) that defines the theme tokens. /* resources/css/app.css */ @import '../../vendor/edulazaro/wiremodal/resources/css/wiremodal.css' ; @import '../../vendor/edulazaro/wirecookies/resources/css/wirecookies.css' ; Then bundle wiremodal's JS. This is the step that makes the Configure and re-open buttons work, so do not skip it. // resources/js/app.js import ' ../../vendor/edulazaro/wiremodal/resources/js/wiremodal.js ' ; How to use it Drop the single Blade component once, near the end of your layout. <x-wirecookies :policy-url="route('cookies')" /> First-time visitors get a bottom banner after a short delay. When they choose Accept all, Reject all, or save from the Con

After setting up Jenkins and creating my first Declarative Pipeline, the next step was preparing my machine to build Docker images. Since my pipeline will eventually clone code from GitHub, build a Docker image, and push it to a container registry, Jenkins needs access to Docker. Without Docker installed, the docker build stage would fail because Jenkins wouldn't be able to execute Docker commands. Installing Docker On my Ubuntu machine, I installed Docker using: sudo apt update sudo apt install docker.io -y Once the installation completed, I verified it using: docker --version This confirmed that Docker was successfully installed and ready to use. Verifying Docker Installation Installing Docker is only half the job. The next step is to check whether your current user has permission to use Docker. Run: docker ps Expected Output If everything is configured correctly, you should see something similar to: CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES Even if no containers are running, getting an empty table like the one above means Docker is working correctly. What If You Get a Permission Error? If you see an error like: permission denied while trying to connect to the Docker daemon socket it means your current user doesn't have permission to access the Docker daemon. First, check which user you're currently logged in as: whoami Example output: nishant Now add your user to the docker group: sudo usermod -aG docker $USER What does this command do? usermod modifies a user account. -aG means append the user to a supplementary group without removing existing groups. docker is the group that has permission to communicate with the Docker daemon. $USER automatically refers to your currently logged-in username. Apply the Changes The group membership won't take effect immediately. You have two options: Option 1 (Recommended): Log out of your Ubuntu session and log back in. This refreshes your user groups and is the most reliable method. Option 2: Simply restart your ter

In a world of plasticky water filter pitchers, I tested three new-generation stainless steel filter systems.

On Dreo’s summer flash sale from August 1 to 3, a great misting fan and an even better air fryer are at the lowest prices we’ve seen them.

A removable chip lets hackers inspect their badge—and keep using it after Defcon.

Usar IA no dia a dia não é nenhuma novidade, e praticamente TODO O MUNDO já sabe disso. E hoje temos diversos "sabores" de IA, inclusive para todos os gostos, e escolher um só é difícil, porque cada um tem seu molho especial em alguma tarefa específica. Eu, como não é novidade, acabei adotando como meu "favorito das últimas semanas" o Kiro...e confesso, muito no começo pelo ícone de fantasma que acho muito massa rss, mas conforme fui usando melhor, comecei a entender a sua estrutura, e principalmente o spec-driven, aí ele me conquistou de uma maneira meio que irreversível. E engraçado que hoje mais cedo quando estava dirigindo a caminho do supermercado, pensando nas minhas demandas e atividades, comecei já a estruturar meu "steering" mentalmente de uma nova task que precisaria fazer, e nisso me veio um pensamento...Caraca! Estou usando o Kiro para praticamente tudo! É isso que quero compartilhar com vocês hoje, um pouco de não só como estou usando, mas onde e para que! Trabalho nosso de todo dia Esse é meio que óbvio né? Seja um desenvolvedor, vibe-coder, arquiteto, engenheiro e tal, todo mundo está na onda de usar a IA para acelerar seu trabalho. Como comentei acima, o spec-driven do Kiro me conquistou porque eu não saio simplesmente "curando código gerado pela IA", eu realmente troco uma ideia com a IA e estruturo realmente a arquitetura daquilo que quero construir. A geração de código virou somente a consequência de toda essa sólida estrutura que conseguimos criar antes, e nesse ponto deixei de ser apenas um curador para assumir realmente a posição de arquiteto da feature que estou desenvolvendo. Conteúdo para comunidade Inclusive, esse artigo é fruto de um pouco disso! Não é sobre ser preguiçoso e deixar a IA gerar o conteúdo (o que eu acho errado também!), mas sim em "se transformar" em uma skill, onde você produz o conteúdo (VOCÊ criando o conteúdo!) e passa por essa skill para correção de gramática, compreensão, internacionalização e regionalização...uso muit

Por que usar o Cloudflare em vez do DNS padrão do seu registrador Escrevi esse texto depois de um perrengue aqui na empresa onde trabalho. Precisei registrar uns subdomínios, entrei no painel da Cloudflare esperando achar os registros lá e não tinha nada, fui atrás do time para entender onde aquilo estava apontando e a resposta foi que tudo passava direto pelo provedor de domínio. Quando você registra um domínio na GoDaddy, Namecheap, Registro.br ou qualquer outro provedor de domínio, ele já vem com um par de nameservers configurados por padrão. Funciona, mas "funcionar" e "ser a melhor opção para produção" são coisas diferentes, e trocar esses nameservers pelos da Cloudflare é uma das mudanças de maior custo-benefício que dá para fazer em um projeto. O que muda ao trocar os nameservers Um provedor de domínio só precisa resolver DNS: publicar seus registros A, CNAME, MX e afins, e responder consultas. A infraestrutura por trás disso varia muito de provedor para provedor e raramente é otimizada para latência global ou resiliência a ataques, porque não é o produto principal deles. A Cloudflare constrói a rede em torno de DNS, CDN e mitigação de DDoS como núcleo do negócio, e isso aparece em números concretos: a rede anycast cobre mais de 330 cidades, então uma consulta DNS ou uma requisição HTTP é respondida pelo ponto de presença fisicamente mais próximo do usuário, não por um servidor central do outro lado do mundo. Hoje a Cloudflare responde por algo em torno de 23% de todos os sites da internet. Vantagens técnicas O anycast é a base de tudo. Não existe "o servidor DNS" que pode cair: se um ponto de presença fica indisponível, o tráfego é roteado automaticamente para o mais próximo, o que reduz latência de resolução e risco de indisponibilidade. A mesma arquitetura, combinada a TTLs baixos, também acelera a propagação de mudanças: um registro DNS alterado costuma valer em minutos, enquanto em boa parte dos provedores de domínio tradicionais não é incomum esperar ho

Last month, the story broke (alternate link ) that Madison Square Garden uses facial recognition software on everyone entering the facility, and—among other groups—flags activists that oppose using facial recognition. Turns out that the system was shut off for Taylor Swift’s wedding. Evan Greer—one of the people that MSG alerts on— comments : Ironically, Swift herself has reportedly used facial recognition at her own concerts to identify stalkers. This “privacy for me, surveillance for thee” attitude feels like a perfect encapsulation of the future we’re already living in: one where wealthy elites can afford privacy, while the rest of us are forced to live in a corporate surveillance panopticon...

Engineering posts often end with: The new design is correct, scalable, and fast. Fast compared with what? When we changed Podium so tied players rank by arrival time instead of player ID, we added: a Lua script; a per-leaderboard sequence; a public-ID mapping; a second sorted set for ascending order. That design is fairer. It is also impossible for it to be free. So we built two benchmark layers: direct Redis strategy benchmarks to isolate the data-model cost, and end-to-end HTTP benchmarks to show what users actually experience. We are publishing the results, including the regression, because performance claims are useful only when readers can inspect the workload and reproduce the measurement. TeneficGames / podium High-performance, Redis-backed leaderboards for games and competitive applications. Podium High-performance, Redis-backed leaderboards for games and competitive applications. Podium provides ready-to-run HTTP and gRPC APIs for scores, ranks, seasons, and player-relative views. It is designed for backend teams operating large fleets of independent leaderboards without provisioning each leaderboard in advance. Fair, deterministic ordering when scores are equal. Single and bulk score updates, including multi-leaderboard fan-out. Standalone Redis and real Redis Cluster integration coverage. Deploy one multi-architecture OCI image with Docker, containerd, Kubernetes or another OCI-compatible runtime. Quickstart · Performance · API · Documentation · Helm chart · Docker Hub · GHCR Quickstart Start Redis 8.2 and the latest stable Podium image: docker network create podium docker run --detach --name podium-redis --network podium redis:8.2-alpine docker run --detach --rm --name podium \ --network podium \ --publish 8880:8880 \ --publish 8881:8881 \ --env PODIUM_REDIS_HOST=podium-redis \ --env PODIUM_REDIS_PORT=6379 \ trungdlp/podium:latest start Verify the service: curl http://localhost:8880/healthcheck WORKING Submit two equal scores: curl --request … View on Gi

A memo obtained by WIRED, issued by the water utilities information sharing group WaterISAC, links dozens of cyberattacks against Minnesota water utilities to Tehran.