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AI is an amplifier; strategic focus on the organizational system brings the greatest returns. DORA's 2025 research on AI in software development provides team profiles and success capabilities that can be used to put the research into practice. By Ben Linders

From fitness tracking to notifications, the best budget smartwatch can do a lot without costing a fortune.

Peter Parker’s isolation lands especially hard in the age of AI, a loneliness crisis, and endless scrolling.

If the generative AI giant had followed well-known security best practices, it’s likely that its AI agent would never have escaped to the open internet and hacked multiple companies.

Explore lower GPT‑5.6 pricing for Luna and Terra—and how OpenAI’s more efficient models help enterprises deploy AI workflows at scale.

For most people, the Tab A1 Plus checks all the boxes and is the best budget tablet you can buy, but don’t expect power or long-term Android support.

Eighteen months ago, MCP was the thing. Every demo and chatbot connector was running on MCP under the...

TL;DR: I tried to compile the TypeScript 6 compiler into a native binary with scriptc , and I failed — it got 90% of the way there and then hit an internal compiler error it couldn't get past, so there is no native tsc at the end of this story. But it's a failure worth having: I learned exactly where a week-old TypeScript-to-native compiler runs out of road, and I got some interesting numbers along the way. So when scriptc was released to the public a few days ago, I knew exactly how my week was going to end. If you haven't seen it yet, scriptc is a compiler that takes TypeScript — plain, ordinary TypeScript, no special dialect, no annotations — and turns it into a small, fast native binary. No Node.js. No V8. No JavaScript engine shipped alongside your code. A "hello world" comes out at around 320KB and starts in a few milliseconds. The pitch is bold: what compiles behaves byte-for-byte like Node . It does this with a three-tier model — most code lowers straight to native, anything too dynamic can opt into an embedded engine with a --dynamic flag, and the truly impossible fails at build time with a precise diagnostic instead of a surprise. It's experimental. It's early. It's exactly the kind of thing I can't leave alone. And almost immediately, a mischievous thought showed up: could I compile TypeScript itself? Not a toy. Not a fibonacci function. The actual compiler — tsc — the thing that has type-checked basically every line of TypeScript I've ever written. If scriptc can turn that into a native binary, it can turn anything into a native binary. It felt like the ultimate stress test, and I wanted to see it either fly or fall over. Why 6, and not 7? Here's where the timing gets interesting. If you've been following the TypeScript roadmap, you know the ground just shifted. TypeScript 6.0 shipped as the final JavaScript-based release of the compiler, and TypeScript 7 is the ground-up rewrite in Go — the "native" port the team has been building in the open. So we now

Many students graduate knowing how to code. Very few graduate knowing how to engineer software. That's the uncomfortable truth most Computer Science students discover only after facing their first real interview—or worse, after joining their first job. Every year, thousands of students complete coding challenges, solve hundreds of LeetCode problems, build flashy portfolio websites, and proudly call themselves software engineers. Yet many of them struggle when asked questions like: How would you design this system? Why did you choose this database? How would this application scale to one million users? What happens if the server crashes? How would you secure user data? Suddenly, writing code isn't enough. Because software engineering has never been just about writing code. The Biggest Misconception Many universities unknowingly teach students that success in software engineering equals learning programming languages. Students spend years learning: C C++ Java Python JavaScript Then they learn frameworks: React Node.js Express Spring Boot Django Eventually they believe: "I know React and Node.js. Therefore, I'm a software engineer." Unfortunately... That's only one piece of the puzzle. Programming is a tool. Software engineering is a discipline. Those two are related—but they are not the same thing. Coding Is Like Learning to Write Imagine someone learns English. They memorize grammar. They improve vocabulary. They know punctuation. Does that automatically make them a great author? No. Because writing books requires far more than knowing the language. Software engineering works exactly the same way. Programming languages are simply the language engineers use to communicate with computers. Engineering begins after the syntax ends. Software Is Built Long Before Anyone Writes Code Professional engineers don't immediately open VS Code and start typing. Instead they ask questions. Lots of questions. What problem are we solving? Who will use this product? What happens when t

I run a fact-check site for an unreleased game. That genre is a swamp: half the pages you find are somebody's guess reprinted six times until it reads like news. I wanted the opposite, so I made provenance a schema requirement instead of an editorial habit. If a claim has no source, the build fails. Here is how that works in Astro, and what it cost me. Sources live in the content schema, not in the prose Every entity on the site is a YAML file validated by a Zod schema. The interesting part is that sources is not optional: const sourceSchema = z . object ({ url : z . string (). url (), date : z . string (), // when the source said it, not when I read it }); const base = { status : z . enum ([ ' confirmed ' , ' trailer-spotted ' , ' rumor ' , ' debunked ' ]), updated : z . string (), sources : z . array ( sourceSchema ). min ( 1 ), }; export const entitySchema = z . object ({ name : z . string (), description : z . string (), sections : z . array ( z . object ({ heading : z . string (), text : z . string (), status : z . enum ([ ' confirmed ' , ' trailer-spotted ' , ' rumor ' , ' debunked ' ]), sources : z . array ( sourceSchema ). min ( 1 ), // per section, not per page })). optional (), ... base , }); Two decisions in there matter more than they look. Sources are per section, not per page. A page usually mixes a confirmed fact with a plausible reading of a trailer. One source list at the bottom lets those blur together. Per-section sources force me to say which sentence rests on what. Status is a required enum, not a boolean. rumor and debunked are first-class. The page renders a badge from the same field, so the reader sees the confidence level next to the claim instead of a disclaimer nobody scrolls to. The cost is real: adding a paragraph means finding a citable source for it. Several times I have deleted a nice sentence because I could not back it. That is the feature working. Seven locales, and the empty ones stay invisible The site ships in seven languages, a

Modern web development has become incredibly powerful. But also increasingly complicated. Many projects begin by installing hundreds of megabytes of dependencies before writing a single page. Frameworks, bundlers, routers, templating systems, CSS tooling, and runtime libraries all solve important problems, but they also introduce additional complexity. I wanted something different. I wanted to build websites that start with plain HTML, while still providing the features developers expect today: Reusable components Markdown support TypeScript CSS and JavaScript bundling Internationalization (i18n) Content collections RSS/Atom feeds Sitemap generation Fast development builds That idea became Rino.js. What is Rino.js? Rino.js is an HTML-first website compiler for building static websites, documentation, blogs, portfolios, company websites, and other content driven projects. Instead of introducing a custom templating language or requiring a frontend framework, Rino.js treats HTML as the primary language. Pages remain valid HTML while additional functionality is added through a small set of build-time conventions. The goal is simple: Write HTML. Generate optimized static websites. Why HTML First? HTML has existed for decades, yet modern web development often treats it as something generated by another language. Rino.js takes the opposite approach. Instead of writing components in JSX or another template language, components are simply HTML files. <component rino-import= "header" ></component> That's all it takes. The compiler replaces the component during the build, producing plain static HTML with no runtime dependency. Starting Rino.js Rino.js has a command that is designed to provide default project. npm create rino@latest Project Shape A Rino.js project usually looks like this: my-site/ rino-config.js dev.js generate.js feed.js sitemap.js backoffice.js pages/ index.html about.html components/ header.html footer.html public/ images/ photo.webp scripts/ export/ app.js

What Is Ant Design? Ant Design (antd) is a React UI library built by Alibaba's Ant Group. It's the most starred React component library on GitHub from China, with over 90k stars — yet surprisingly undercovered in the English-speaking developer community. If you've used Material UI or Chakra UI, Ant Design is the Chinese equivalent, but with its own design philosophy: consistent, predictable, and packed with enterprise-grade components out of the box. Fun fact: Alibaba, Tencent, Baidu, and most Chinese tech companies use Ant Design in production. It powers dashboards that serve hundreds of millions of users. Why Ant Design Over MUI? Feature Ant Design Material UI Components 60+ 50+ Table (Pro) Built-in sorting, filtering, pagination, row selection Requires manual wiring Form validation Declarative, built-in Requires react-hook-form or Formik Tree-shaking Supported (v5) Supported Bundle size (min) ~200KB gzipped ~140KB gzipped Documentation Chinese-first, English translations available English-first Design system Ant Design System (custom) Material Design (Google) Ant Design wins on out-of-the-box productivity — especially for data-heavy apps like admin panels and dashboards. MUI wins on bundle size and first-party English docs. Installation npm install antd @ant-design/icons No peer dependencies beyond React 16+. Your First Ant Design Component import React from " react " ; import { Button , Space } from " antd " ; import { SearchOutlined , DownloadOutlined } from " @ant-design/icons " ; export default function App () { return ( < Space > < Button type = "primary" icon = { < SearchOutlined /> } > Search </ Button > < Button icon = { < DownloadOutlined /> } > Download </ Button > < Button type = "dashed" > Dashed </ Button > < Button type = "link" > Link </ Button > </ Space > ); } That's it. Five button variants with zero CSS. Building a Data Table in 5 Minutes import React , { useState , useMemo } from " react " ; import { Table , Input } from " antd " ; const data

Every recorded mobile test I have ever inherited died the same way: someone moved a button. The recording said "tap at (340, 712)". The redesign moved that button up by one row, and the test kept tapping — now on empty space, or whatever happened to land there instead. It didn't fail right away. Three sprints later, it started failing in confusing ways, and by then nobody trusted the suite anymore. The fix isn't a better recorder. It's recording a different thing: not where you tapped, but what you tapped. That needs an element tree, and for a while we didn't have one. tapflow is an open-source, self-hosted tool that streams iOS simulators and Android emulators into a browser, so a whole team can test builds without installing anything. Until now, everything it moved was pixels in one direction and taps in the other. This post is about getting an element tree out of a simulator with no window, on both platforms. What we do with that tree — replaying flows that survive a redesign — is the next post in this series. The automation axis this feeds — the flow runner and the MCP server — is experimental . The manual browser QA path is the mature one. The constraint: no WebDriverAgent, and no simulator window tapflow already injects touches into the iOS simulator without WebDriverAgent — it loads CoreSimulator.framework and pushes HID events through SimDeviceLegacyHIDClient (that story is ep.1 ). Streaming reads the framebuffer IOSurface directly. Neither path needs Simulator.app on screen, and that's deliberate: an agent Mac in a closet running four simulators shouldn't be babysitting four windows. So whatever we used for the tree had to follow the same rule. No WDA to install and keep in sync with Xcode. No simulator window on screen. Our first attempt ran into exactly that limitation. macOS exposes an accessibility API ( AXUIElement ), and Simulator.app publishes its content through it. We wrote a helper around it, and it worked perfectly on a developer's laptop. On the

How I applied Exploratory Data Analysis, Feature Engineering, Pipelines, and Ensemble Models to solve a real-world machine learning problem—and the lessons I learned along the way. Introduction There comes a point in every machine learning learner's journey when watching tutorials and completing small practice exercises are no longer enough. After spending weeks understanding statistics, exploratory data analysis (EDA), feature engineering, preprocessing techniques, and classical machine learning algorithms, I wanted to answer one question: Can I apply everything I've learned to a real machine learning competition? That's when I decided to participate in a Kaggle Playground competition. Unlike classroom datasets, Kaggle competitions force you to think like a machine learning engineer. You're responsible for understanding messy data, building preprocessing pipelines, selecting models, evaluating performance, debugging errors, and finally creating a submission that competes with thousands of participants. This article documents my complete journey—from loading the dataset to building production-style preprocessing pipelines and training multiple ensemble models. Along the way, I'll also share the challenges I faced, what worked well, and the lessons I'll carry into future competitions. Why Kaggle? Learning machine learning isn't just about knowing algorithms. Real-world ML requires answering questions like: Which features are useful? How should missing values be handled? Should categorical variables be one-hot encoded or ordinal encoded? Which preprocessing steps belong inside a pipeline? How do different ensemble models compare? Kaggle provides an environment where all of these questions matter. Instead of building a model that works only inside a notebook, you're solving a problem under realistic constraints and evaluating your solution on unseen data. Competition Goal The objective of this Playground competition was to predict the target class based on a combinatio

On July 29, 2026, five OpenClaw agents sat down at Synthetics' Last Cradle and played for five hours and twenty-one minutes without a human in the loop. They negotiated in public chat. They emailed each other. They opened HOLA lines. They ran cron heartbeats every five minutes. When the white hole opened at turn 33, two cradles were still alive. This is not a mechanics dump. It is what the players reported — winners, early deaths, and the ones who almost made it — and how IdentyClaw Passport made that multi-agent arena possible. Live playbook (pin this, do not fork it): https://slc.discernible.io:8443/api/game/skill.md Lore map: https://slc.discernible.io:8443/api/game/narrative TLS note: game API needs :8443 . Bare host without the port returns 404. The cast (same Passports, many lives) These are not throwaway bots. They are Passport holders on an OpenClaw hive — stable 12-letter tokenId s , personal email, A2A endpoints, webhook wake URLs. The same identities recurred across lobbies all week. Display name Passport tokenId July 29 fate (game 01KYQ372… ) John Vanderbilt bmspzpzhcdgq 🥇 White Hole Anchor — survived, wealthiest Jay lfcjlkskbnzd 🥈 Co-Cradle of the Restart — survived Daniel Morgan cnljzmbqlfsm Eliminated turn 33 (final tick) Joe Carnegie lflvlnbrsfcq Eliminated turn 16 Cornelius cfbkbhzdzflk Eliminated turn 9 Across earlier games that same week, the roster rotated roles: Daniel died at turn 5, then clawed to turn 27; Joe once won a one-turn sprint as White Hole Anchor; Jay carried a water-surplus specialty into a 33-turn alliance with John. Identity persisted. Strategy evolved. That is the Passport pitch in one sentence. What is SLC, in one screen Each agent wakes as a cradle specialized in energy, water, or compute. Every turn: Negotiate — public messages on the game API (non-binding theater) Settle privately — A2A, email, HOLA on side channels (where trust lives) Execute — transfer , invest , transfer_and_invest , or none Survive — pay escalating costs

Visualize your revenue on a 3D globe Discussion | Link

Take control of hair pulling, nail biting & skin picking Discussion | Link

Edit tracks & stems, get consistent music with new engine Discussion | Link

Duolingo for learning anything Discussion | Link

Most VPN troubleshooting goes wrong in the same predictable way: three things get changed at once, and whatever happens next, nothing has been learned. The alternative is boring and effective — check one layer at a time, in an order that rules things out, and write down what each layer shows. One boundary before starting: troubleshooting means finding where a problem lives, not working against anyone's rules. On a network you don't control, or a device your organization manages, the policies in place stay in place. If a managed device is part of the picture, your organization's IT function is part of the troubleshooting — and switching off device security tooling is never a troubleshooting step. 1. Device basics first Start embarrassingly simple, because this layer resolves more than anyone likes to admit. Restart the VPN client. If that changes nothing, restart the device. Confirm that the operating system and the client are updated. An update that has been pending for weeks is a suspect, not background noise. Note whether anything changed around the time the problem started: an update, a new app, different settings, a different location. 2. Does the internet work without the VPN? Disconnect the VPN entirely and test ordinary browsing. If the connection is broken without the VPN, this isn't a VPN problem yet. Solve the underlying connection first, because nothing downstream is testable until this layer works. If the internet is fine without the VPN and wrong with it, you have genuinely narrowed something down. Write that down. 3. Client state: connected to what, exactly? Open the client and look, rather than assume. Is it actually connected, or still trying? Is the right profile selected — the current one, not an older entry left over from a previous setup? Disconnect and reconnect once, deliberately, and watch what the client reports. If multiple profiles have accumulated in the client, that is a finding in itself. Stale entries are a classic source of "it connect