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Quick, creative video subtitling with direct canvas control Discussion | Link

Fourth of July weekend is the last great grill and griddle sale of the summer, including $250 off my favorite pellet smoker.

Next spring could be a fiesta of new iPads, MacBooks and iPhones.

The company has grown rapidly by acquiring and revamping last-generation tech brands like AOL, Eventbrite, Evernote, Meetup, and Vimeo.

Apple is working on a "revamped" version of its entry-level MacBook Pro that it could launch as soon as the first half of 2027, Bloomberg reports. The company is also testing four new iPad Pros that are set to launch in the spring with a focus on "internal improvements." The updated MacBook Pro, which will […]

The co-founders of Bending Spoons, the Italian company quietly buying beloved, ailing Internet brands, learned big lessons from their own startup's failure.

Cody Spencer, the co-owner of the small games retail chain Pink Gorilla Games, put it well when I asked about the impact of Sony's recent announcement that it will stop making discs for new games starting January 2028. "It's sad to see. This decision is only a negative for gamers. We're losing the ability to […]

Meta says usernames improve privacy, but critics question whether its safeguards can prevent impersonation.

GitHub热门项目 | 🚀 A real-time monitoring dashboard for Claude Code, built with SQLite3, Node.js, Express, React, Vite, TailwindCSS, and WebSockets. It tracks sessions, agent activity, tool usage, and subagent orchestration, providing live analytics, a Kanban status board, status notifications, a cute buddy, and an interactive web UI/MacOS/Windows native app. | Stars: 734 | 162 stars this week | 语言: TypeScript

Bonjour Je travaille actuellement sur un nouveau langage de programmation appelé Klyn . Alors je sais, certains vont me dire pourquoi encore un nouveau langage. Peut-être est-ce vrai, mais d'un autre point de vu, pourquoi ne pas être audacieux et proposer une autre lecture possible. A méditer. De plus, logiquement on ne fait pas de promo de projet sur r/programming , mais pour le coup le projet porte clairement sur la programmation et je me dis que ce post est quand même à sa place (j'espère qu'on m'en tiendra pas trop rigueur ; je suis nouveau sur Reddit). Quoi qu'il en soit, mon point de départ est que Python propose une syntaxe épurée et lisible, par contre les performances en termes de temps d'exécution, c'est pas ça. Du coup, pourquoi ne pas intégrer les bonnes idées de C++ pour les perfs dans un langage "Python-like" ? Et tant qu'on y est, Java et C# propose aussi des trucs sympa. Et puis j'ai aussi quelques autres idées sympa à tester (j'ai notamment tester des choses sur les syntaxe des collections). Et donc je suis partis à proposer Kl yn , un langage "Python-like" orienté performance . Du coup, j'en suis là : une syntaxe lisible et agréable, proche de Python, un typage statique pour la fiabilité des codes, une compilation native et implicite pour les performances, des propriétés inspirées de C#, pleins d'idées perso sur la syntaxe et les lib, une API déjà assez riche autour des collections, chaînes, fichiers, terminal, interface graphique, bases de données, thread, api llm... Etant actuellement seul sur le projet, j'ai grandement fait usage de l'IA (je préfère être cash ; clan Codex), mais franchement, je ne le regrette pas. En l'état le projet n'est pas prêt a passer en production. C'est pour ça que j'ai besoin de vos impressions (afin de préparer cette future étape). De plus, si vous êtes convaincu par la démarche, qu’attendriez vous d'autre d’un tel projet ? Site du projet : https://klyn.deepcodia.fr Tutoriel : https://klyn.deepcodia.fr/docs/tutorial/in

Everyone keeps saying AI will let a solo developer take down the giants. And everyone keeps saying the giants will just absorb everything. Both takes are wrong , and I spent a while reading the actual 2025 data to figure out why. I pulled from four of the biggest developer datasets of the year: DORA 2025 State of AI-Assisted Software Development (Google Cloud, ~4,867 respondents) Stack Overflow 2025 Developer Survey (49,009 respondents) GitHub Octoverse 2025 (behavioral data across 180M+ developers) JetBrains State of the Developer Ecosystem 2025 (24,534 developers) Here's the honest synthesis. It's more useful than either hype narrative. The one-sentence thesis AI collapsed the cost of writing software to near zero. It did not collapse the cost of distribution, trust, support, or being liable when it breaks — and those are ~80% of what a software business actually is. So the effect isn't "solos beat giants." The effect is that the middle got hollowed out . The 10-person, VC-funded, me-too startup building a feature is the loser of this era — squeezed from below by a solo who ships the same thing for free, and from above by a giant who bundles it. Solos and giants both survive. The undifferentiated middle doesn't. "AI is an amplifier, not an equalizer" This is the single most important finding of 2025, and it comes straight from DORA: "AI's primary role in software development is that of an amplifier. It magnifies the strengths of high-performing organizations and the dysfunctions of struggling ones." Read quickly, that kills the "AI levels the playing field" fantasy. AI rewards whoever already has good practices — not whoever is scrappiest. But read one layer deeper and it becomes the best available argument for the small team. DORA found the key enabler is independence of action — "the ability to develop, test, and deploy value independently, with little or no coordination cost." In an Adidas pilot they cite, teams in loosely-coupled architectures saw 20–30% produ

Turn to-dos into scheduled tasks Discussion | Link

Pressing enter to accept model suggestions now takes less effort than scrolling past it. One keystroke, and the code is yours. Reading it, understanding it, deciding if it's actually right, that part hasn't gotten any faster. That gap, between how fast we can accept code and how fast we can actually understand it, is where things start to go wrong. The new shape of technical debt We used to know where technical debt came from. Tight deadline, cut corner, # TODO: comment that nobody ever revisits. Rushing was the cause, and we could at least point to it. Now you can build up the same kind of debt on a calm Tuesday afternoon, no deadline in sight, just six suggestions in a row accepted because they looked fine and the flow felt good. Nobody rushed you, and the code still ended up just as unexamined. Same debt, just a different excuse. "It works" is not the same as "I understand why it works" Everyone knows that debugging is twice as hard as writing a program in the first place. So if you're as clever as you can be when you write it, how will you ever debug it? — Brian Kernighan, 1974 Fifty years later, the gap got wider. Kernighan was talking about code you wrote. At least you understood it once. A suggestion that compiles, passes the linter, survives code review and even comes with passing tests can still be standing on a wrong assumption that nobody caught, because nobody was reading it as code. They were reading it as output, and output that makes sense tends to get approved. Compiling is a low bar. Passing tests is a slightly higher one, depending on whether you wrote the tests, or its suggestion shaped or created those too. If it's the second, it's like grading its homework with its own answers. None of it tells you the logic is sound, that the edge cases are covered, or that it does what you actually needed, something we already learned every time we trusted code we didn't write. Somehow it's easy to forget it the moment the code appears inline, in our own edito

HTTP cookies are everywhere in authentication, sessions, and tracking — but reading Set-Cookie headers manually is tedious. I built a free, browser-only HTTP Cookie Inspector that parses cookie strings and gives you a security analysis. Live Tool 👉 https://devnestio.pages.dev/cookie-inspector/ What it does Parse Set-Cookie strings — extract all attributes at a glance Attribute cards — name, value, expires/max-age, domain, path, Secure, HttpOnly, SameSite Security score (0–100) — +25 for Secure, +25 for HttpOnly, +25 for SameSite≠None, +25 for expiry XSS/CSRF risk flags — warns when HttpOnly or SameSite is missing Syntax highlighted raw header — color-coded by attribute type Presets — session, persistent, secure+httponly, SameSite=Strict, minimal 100% client-side — no data leaves your browser Cookie security flags explained Flag Missing risk Present benefit Secure Cookie sent over HTTP Only sent over HTTPS HttpOnly JS can steal it (XSS) Inaccessible via document.cookie SameSite=Strict CSRF attacks possible Never sent on cross-site requests SameSite=Lax Partial CSRF risk Sent on top-level nav only SameSite=None Always cross-site Requires Secure flag SameSite values Set-Cookie: session=abc123; SameSite=Strict; HttpOnly; Secure # Best practice for auth cookies Set-Cookie: prefs=dark; SameSite=Lax # OK for non-sensitive preferences Set-Cookie: embed=true; SameSite=None; Secure # Cross-site embeds (e.g. payment widgets) Testing 84 tests, all passing ✅ Tests cover: Parsing all standard attributes Boolean flags (Secure, HttpOnly) detection SameSite value classification Max-Age duration calculation Security score computation XSS/CSRF warning logic All preset templates HTML escaping in output UI elements and copy functionality All tools at devnestio.pages.dev — free browser-only developer utilities.

Working With Massive JSON Responses Without Losing Performance Every developer eventually encounters it. You make an API request expecting a few hundred objects, and instead receive a response that's tens—or even hundreds—of megabytes. Suddenly your browser freezes, your editor becomes sluggish, and your application consumes gigabytes of memory. Large JSON responses aren't unusual anymore. Analytics platforms, cloud providers, search engines, AI services, ecommerce catalogs, IoT systems, and data export endpoints routinely generate enormous payloads. The good news is that handling massive JSON efficiently is mostly about choosing the right techniques. This guide covers the best practices that help you inspect, process, and optimize large JSON datasets without overwhelming your tools or your users. Understand Why Large JSON Is Expensive Before optimizing, it's helpful to know where the cost comes from. When an application receives JSON, it usually goes through several stages: Download the response. Store it as a string. Parse it into objects. Allocate memory for every property. Traverse the resulting object graph. For a 100 MB JSON file, peak memory usage can easily exceed 300 MB because both the raw string and the parsed objects coexist temporarily. This explains why applications often run out of memory long before reaching the actual file size. Don't Pretty-Print Gigantic Responses Immediately Pretty-printing is useful—but formatting a huge document all at once can consume significant CPU time and memory. Instead: inspect only the sections you need collapse large objects expand nodes on demand search before formatting If you need to examine a large payload in the browser, using a dedicated formatter designed for large documents can make navigation much easier. Tools like JSON Formatter allow you to validate, format, collapse, and inspect JSON without manually editing thousands of lines. Stream Instead of Loading Everything One of the biggest mistakes is reading an

Debugging JWT authentication usually means copying tokens between tabs and tools. I built a free, browser-only JWT Creator & Signer — create, sign, and verify JWTs entirely in your browser using the Web Crypto API. Live Tool 👉 https://devnestio.pages.dev/jwt-creator/ What it does Create JWTs — edit header (alg, typ) and payload (any JSON) Sign with HMAC — HS256, HS384, or HS512 Quick claim buttons — insert sub , name , exp (+1h), iss with one click Generate random secrets — 256-bit hex secret via crypto.getRandomValues() Verify existing JWTs — paste any token and verify signature + expiry Color-coded output — header in red, payload in green, signature in blue 100% client-side — Web Crypto API, no server, your secrets stay local How signing works (Web Crypto API) const key = await crypto . subtle . importKey ( " raw " , new TextEncoder (). encode ( secret ), { name : " HMAC " , hash : " SHA-256 " }, false , [ " sign " ] ); const sig = await crypto . subtle . sign ( " HMAC " , key , new TextEncoder (). encode ( header + " . " + payload ) ); The output is base64url-encoded (replacing + → - , / → _ , stripping = padding) to form the final JWT. Why browser-only matters for a JWT tool JWT secrets are sensitive. Any tool that sends your signing secret to a server is a liability. This tool never sends anything — the Web Crypto API runs entirely inside your browser tab. Testing 77 tests, all passing ✅ Tests cover: Base64url encoding edge cases JWT structure (3-part dot-separated) HMAC algorithm mapping (HS256 → SHA-256 etc.) Expiry check (expired vs. valid tokens) Error states: invalid JSON payload, malformed JWT UI: claim insertion, secret toggle, copy, clear Web Crypto API usage verification All tools at devnestio.pages.dev — free browser-only developer utilities. Feedback welcome!

Opening hook It happened during a quiet afternoon at the mosque. The imam was mid-sentence when a rhythmic, high-pitched ringtone cut through the silence like a knife. Every head turned. It was my phone. My heart sank as I scrambled to silence it, only to realize I had forgotten to flip the physical toggle before walking in. That moment of collective, disappointed glares burned. It wasn't just an annoyance; it was a total breakdown of my focus and a social failure I had accidentally caused because my phone couldn't manage itself. The problem We live in an era where our devices are supposedly 'smart,' yet they are remarkably bad at knowing when to keep quiet. We carry computers in our pockets that can calculate the exact position of the moon or stream 4K video, but they cannot inherently tell that we are in a meeting, a lecture, or a place of worship. You could argue that setting a manual schedule works, but life isn't static. Meetings run over, prayer times shift by a minute each day based on astronomical calculations, and spontaneous plans happen. I found myself constantly juggling the physical volume buttons. If I remembered to mute it, I inevitably forgot to unmute it afterward, missing urgent calls from family. If I didn't mute it, I was the person disrupting the room. I wanted a solution that respected the context of my location and the specific time of day without requiring me to touch my screen. The core friction is that Android is designed to restrict background processes to save battery, which is exactly what a silent-automation app needs to thrive. Getting the app to reliably trigger a volume change while the phone is sitting in a pocket, deep in Doze mode, became my primary development hurdle. The technical decision / implementation When I started building Muffle, I initially tried a standard Service with a Handler loop to check conditions. It worked fine while the screen was on, but as soon as the phone entered Doze mode, the OS aggressively throttled my

A full form backend you can test before paying Discussion | Link

Fans’ euphoric reactions to the Mexican national team’s recent victory in the 2026 World Cup caused a series of unusual vibrations that were detected by seismic warning systems.

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