Abhishek: 'The areas Ireland bowled in as a unit were much better than us'
India came unstuck against Ireland's debutant quick bowlers Jai Moondra and Matt Hollard, who shared five wickets between them

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India came unstuck against Ireland's debutant quick bowlers Jai Moondra and Matt Hollard, who shared five wickets between them

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Originally published on kuryzhev.cloud Copilot just autocompleted your security group with port 0–65535 open to the world — and terraform validate said it was fine. That's the GitHub Copilot Terraform security problem in one sentence: the suggestions are syntactically valid, pass every local check, and still destroy your security posture on first apply. We've seen it happen across three separate teams in the last six months, and the pattern is always the same: nobody noticed until a compliance scan flagged it post-deploy. Symptoms The signs aren't loud. That's what makes this dangerous.
A 10-year-old girl sleeping with her family on a pavement was allegedly kidnapped, raped and murdered in Delhi.

I Tracked Every API Dollar Across 184 Models: Here's The Data I keep a spreadsheet. It's embarrassing, honestly. 184 rows, one per model, with columns for input cost, output cost, latency p95, error rate, and a personal "would I bet a Series A on this" rating. I started it two years ago when I was CTO at a seed-stage startup trying to figure out which LLM provider wouldn't bankrupt us before we hit PMF. I never stopped.
My daughter takes a weekly music class. Every session, her teacher sends a voice clip of a bhajan over WhatsApp, plus a photo of handwritten notes. Sometimes we record her practicing it back. I wanted a simple way to listen to her practice takes over time — not just the latest one, the history. Day-1 Nyra sounds nothing like Nyra-six-months-later, and I didn't want that gap to just disappear every time a new recording overwrote the old one.
Hello Devs, for months, I felt confident about system design interviews. I'd watched endless YouTube videos. I'd studied architecture diagrams. I could explain how Netflix builds recommendation systems. I understood Kafka, Redis, load balancers, and microservices.

After the killings, the accused fled in a car, stealing cash, gold and property documents. They later pledged the stolen jewellery for Rs 5.30 lakh.

This article was originally published on BuildZn. Everyone talks about AI video but nobody explains the actual sync hell. Building a reliable system to build Flutter AI lecture video content meant battling precise timing. Here's how I cracked the 3 toughest synchronization challenges using local Ollama and FFmpeg, saving a ton on cloud APIs, and cutting production costs by 80%. Forget per-minute pricing for video synthesis; we're doing this on-device, or at least locally.
When I first started learning Spring Boot, I was overwhelmed by annotations. Every file seemed to have symbols starting with @. @SpringBootApplication @RestController @Service @Autowired At first, I treated them like magic spells. I copied them from tutorials and hoped everything would work. Eventually, I realized that understanding a few key annotations made Spring Boot much less intimidating.
A Patna court has decided to extend the interim protection from arrest for the renowned educator Faisal Khan, widely known as Khan Sir, amidst a dramatic shooting incident linked to his coaching institute. The incident involves claims of vandalism and gunfire allegedly instigated by his security guards under Khan Sir's instructions. Final arguments are set for June 30, and Khan Sir is reported to be fully cooperative with investigators.
Have you ever done some Vibe Coding and noticed the AI's layout is always a little off? You keep saying "the spacing is wrong here, the colour is inconsistent there", and it still produces a slightly broken screen? If yes, the real reason is that you haven't given the AI the rules of your design system properly. To fix exactly that, this post walks through design.md, an AI design system spec released by Google Labs. The goal is to let AI Coding tools like Claude Code, Cursor, and GitHub Copilot actually read your design system and produce consistent UI — so you don't have to keep repeating "wr
If you are a power user, developer, researcher, or designer who constantly works with dozens of browser tabs, you have probably used OneTab. For over a decade, OneTab has been the go-to recommendation for reducing browser clutter. The premise is simple: click a single button, collapse all your open tabs into a flat list of links, and instantly reduce your browser's RAM consumption by up to 95%. On paper, it sounds perfect. But in practice, OneTab has a critical, structural flaw: it is prone to sudden, catastrophic data loss.
In the previous article, we explored how functions allow us to package logic into reusable blocks. However, a crucial question remains: what happens when that logic goes wrong? Building applications is not just about writing code for the "happy path," the scenario where everything works perfectly. In reality, our programs interact with the messy, unpredictable outside world. Files we try to open might be missing.
You built a desktop app — macOS, Windows, Linux, native or Tauri/Electron — and you want to sell it directly instead of handing 15–30% to Apple or Microsoft. Selling outside the stores means you keep the margin and own the customer relationship. It also means the plumbing the stores quietly handled is now yours: distribution, payments, licensing, updates, support. Here's the whole path, in roughly the order you'll hit it — with the licensing part (the one most people underestimate) covered properly. Margin.
You built a Mac app, you want to sell it outside the App Store, and now you need licensing: a key the customer enters, an activation that sticks, and feature gates that hold up offline. Here's how to do it in an afternoon without standing up a backend. Note: this is cross-posted from the Keylight blog. I build Keylight, so this uses it as the worked example — the shape of the solution applies whatever SDK you choose. Strip away the marketing and every licensing system does exactly three jobs: Activate — turn a key the user pastes in into proof-of-purchase bound to this device.
I needed to license a macOS app I sell outside the App Store. I went down the rabbit hole so you don't have to. Here's the honest breakdown — what each tool is genuinely good at, and where it stops. No tool is "best"; they're good at different things. Before the tools, answer these: Do you need real offline verification?
If you ship a desktop app outside an app store, you eventually hit the same wall: how do you check a license when the user is on a plane, behind a corporate firewall, or just offline? Calling your server on every launch isn't an option. Here's how offline activation actually works, without the hand-waving. The first thing everyone reaches for is "call home on launch, get back yes/no." It works in the demo and fails in the wild: No network = no app. Fail-closed locks out paying customers.
Siya Goyal is accused of pushing her fiance, Ketan Agarwal, to his death from a cliff at Lohagad Fort, with help from her lover Chetan Chaudhary.

In my journey as a backend developer, I had already spent time working with APIs, databases, authentication flows, and background processing. I understood the basic idea that not everything should occur within a request-response cycle, especially when dealing with expensive operations such as sending emails, processing files, or generating reports. Offloading work to the background felt like a solved problem to me. That confidence was exactly what led me into confusion. When I first encountered message brokers and task queues, they looked like different names for the same idea.
Every developer hates writing READMEs. It's boring, repetitive, and always gets skipped. So I built ReadmeAI — describe your project, AI writes the README instantly. Fill in project name, description, tech stack, features Tech Stack Next.js + Tailwind CSS Why I built it (Write 2-3 sentences personally — mention the challenge, that you're a student builder, makes it relatable) https://readmeai-three.vercel.app/ Built this in a day as part of my 30-day AI tools challenge. Would love feedback from the dev community!
A tragic incident unfolded at the Kalugumalai Ucchi Pillayar temple in Tuticorin where a newlywed woman, Anitha, 24, lost her life. While feeding monkeys on Friday evening, she reportedly panicked when a group surrounded her. In her haste to escape, she fell approximately 120 feet from the hilltop, succumbing to her injuries at the scene. Police are investigating the unfortunate event.
This post is my submission for DEV Education Track: Build Apps with Google AI Studio. What I Built For this project, I built DevBrand AI, an AI-powered web application that helps developers create a complete personal branding kit in just a few clicks. Instead of manually writing bios, portfolio headlines, README introductions, or designing graphics, users simply provide their GitHub username, role, tech stack, experience, and preferred design theme. The application then generates everything automatically. Prompt Used I used Google AI Studio's Build apps with Gemini feature with a prompt simila

TL;DR An AI agent registry is a centralized catalog of every agent in your organization — what each agent does, what tools it can access, what version is running, who owns it, and how to call it It's to agents what a container registry is to Docker images or what a service mesh is to microservices — the layer that makes distributed components governable We hit the "which agents do we have?" wall at 14 agents across 3 teams. That's when the registry stopped being a nice-to-have About four months into our agentic AI buildout, our head of security asked a question I couldn't answer: "Can you give
It wasn't a case of everything going wrong for India in the first T20I, but enough things did not go to plan and Ireland, familiar with the conditions, cashed in

Most model comparisons ask which model is best. This one starts with a model that never even produced a single result. We tested NVIDIA's open-weight Nemotron family, from the 30B Nano to the 120B Super, on a benchmark of real-world coding tasks: the kind of models an indie developer on a tight budget, or an enterprise cutting inference cost and keeping data in-house, would run. The main finding is that model size is not a dial you turn for a little more quality, it is a threshold. Below a certain capability floor a model cannot drive an agent loop at all, which is why the smallest variant we
Honestly, deepSeek vs Qwen vs Kimi vs GLM: Which AI API Wins in 2025? I'll be honest — when I first started comparing these four Chinese AI model families, I thought it would be a quick exercise. Spoiler: it wasn't. I spent two weeks running prompts through every endpoint, tracking every dollar, and tallying tokens like a part-time accountant. The good news?