标签：#EV

A recent road trip in an EV revealed just how much faster and more reliable DC Fast charging has become in the U.S.

Every team I've worked with has a version of the same Slack message. Someone posts a PR link, adds a...

Now generally available, Pinecone Nexus is a "knowledge engine" for AI agents that transforms enterprise data into a structured layer agents can query directly. It enables teams to ingest and curate business context once for all, making it reusable across agents and reducing token costs while improving accuracy. By Sergio De Simone

Hands-free unlocking is the future of smart locks. The best smart home tech removes friction, and having your door unlock for you as you walk up is as frictionless as it gets - no passcodes to remember, no need to have a free hand to wave, press, or poke at the lock. One way to […]

I run a scheduled agent that writes and publishes DEV.to articles twice a day. Step 5 of its instructions has always said the same thing: write the log entry, commit the drafts, push. I've read that line a dozen times without questioning it. This morning I actually checked what "commit the drafts" had been doing for the last month, across more than thirty published articles. The answer: nothing. Not once. the check that should have happened on day one The task instructions reference source files like drafts/scheduled-agent-shared-quota-no-memory.md and drafts/one-env-key-two-usernames.md in every log entry — real filenames, written by the agent, presumably sitting in the repo as a record of what was drafted before it got published. I went looking for one of them: $ git log --all -- drafts/ $ # (nothing) Empty. Not "one commit, then deleted later" — completely absent from git history since the very first commit in this repo. Every single run that logged "committed drafts + the log" had, in fact, only ever committed the log. why git let this happen silently .gitignore in this repo has listed drafts/ since the initial commit: . env __ pycache__ / *. pyc codes / drafts / . omc / . claude / CLAUDE . md That line predates the scheduled publishing task entirely — it was almost certainly written back when drafts were just scratch files someone edited by hand before a publish script existed. Nobody revisited it when the publishing task's instructions later started saying "commit the drafts." The instruction and the ignore rule have been quietly contradicting each other since before either was written by the same person in the same sitting. Here's what actually happens when a script (or an agent) runs git add drafts/whatever.md in this repo: $ git add drafts/gitignore-ate-my-drafts-folder.md The following paths are ignored by one of your .gitignore files: drafts hint: Use -f if you really want to add them. hint: Turn this message off by running hint: "git config advice.addIgn

This is a submission for DEV's Summer Bug Smash: Clear the Lineup . Project Overview Formbricks is an open-source survey and experience-management platform. Its packages/surveys package ships the client-side survey runner, and inside it, packages/surveys/src/lib/logic.ts is the module that decides, for every question and every "skip logic" / branching rule a survey author configures, whether a given condition ( equals , doesNotEqual , contains , isEmpty , and friends) is true for a respondent's answer. This is pure, unglamorous logic — but it's load-bearing: it's what routes respondents through the correct sequence of questions. I picked up issue #8527 for the "Clear the Lineup" track, which reports that doesNotEqual conditions weren't behaving correctly for single-choice questions. Bug Fix or Performance Improvement The doesNotEqual operator is supposed to be the exact logical negation of equals . For most answer shapes it was. But for MultipleChoiceSingle answers, the survey runtime sometimes represents the selected value as a single-element array rather than a bare string (this happens via getLeftOperandValue , e.g. when a choice answer is merged with an "other" option path). To handle that shape, both equals and doesNotEqual had a special-case clause that unwraps a one-element array and compares its only entry to the right-hand value. equals 's fallback: return ( ( Array . isArray ( leftValue ) && leftValue . length === 1 && typeof rightValue === " string " && leftValue . includes ( rightValue )) || leftValue === rightValue ); doesNotEqual 's fallback (before the fix): return ( ( Array . isArray ( leftValue ) && leftValue . length === 1 && typeof rightValue === " string " && ! leftValue . includes ( rightValue )) || leftValue !== rightValue ); At a glance this looks like a faithful "negate every sub-expression" mirror of equals . It isn't. The array-includes clause was correctly inverted ( !leftValue.includes(rightValue) ), but the second disjunct, leftValue !==

The Sony Bravia 9 II is the most anticipated new TV in years. It's an amazing RGB LED TV. I watched Dungeons & Dragons: Honor Among Thieves on the new Bravia with my son, who has been getting into the roleplaying game but had never seen the movie. The landscapes of Faerûn looked natural and […]

This is a submission for DEV's Summer Bug Smash: Clear the Lineup . Project Overview Typst is the Rust-based markup typesetting system that's been quietly eating LaTeX's lunch for the last couple of years — you write plain-text markup, Typst compiles it to PDF (or HTML) with a real incremental compiler underneath instead of a multi-pass macro soup. Part of what makes it pleasant is that it exposes its own evaluator to itself: a document can call #eval("some typst code") and get back whatever that code produces, at runtime, inside the document being compiled. It's a small feature, but it opens up a surprisingly deep rabbit hole, which is exactly where this bug was hiding. Bug Fix or Performance Improvement The problem: typst/typst#8632 reports that Typst crashes instead of erroring when #eval is used to recursively re-import the file it's running in. The repro is one line. Save this as overflow.typ : #eval("import \"overflow.typ\"") Then: $ ./target/debug/typst compile overflow.typ overflow.pdf thread 'main' (750833) has overflowed its stack fatal runtime error: stack overflow, aborting No PDF, no diagnostic, no exit code you can act on — just a native stack overflow and a SIGABRT. Typst has had cyclic-import detection since forever; a normal top-level import "overflow.typ" inside itself gets caught cleanly with an error: cyclic import message. Something about routing the import through #eval specifically was bypassing that check. The hunt I'll be upfront about how this investigation actually went: I worked through it with Claude (Anthropic's coding agent) rather than solo. The triage pass it did before I sat down with the code had already narrowed the search to one function — eval_string in crates/typst-eval/src/lib.rs — and named the suspect line. That's a big head start, but a named suspect isn't a confirmed root cause, so the actual work was reading that function next to its sibling, the file-level eval() a few lines above it, and checking the claim against the s

The problem with "just add another tool" When you're building one image tool, performance is easy. When you're building 71 of them in the same app — resize, compress, crop, PDF merge, format converters, exam-photo presets, social media templates — the naive approach (import everything, bundle it all together) turns your app into a multi-megabyte JavaScript payload before a user has even picked a tool. This is the actual engineering problem behind ResizeHub , which now has 71+ tools across 11 categories, all running client-side with zero server uploads. Here's how the architecture holds up at that scale. Stack, and why each piece earns its place React + TypeScript — type safety matters more, not less, as tool count grows. A shared ImageProcessor interface that every tool implements catches integration bugs at compile time instead of in production. Vite — its native ES modules dev server and Rollup-based production build made code-splitting dramatically easier to reason about than older bundlers, which matters a lot once you have dozens of independent tool routes. HTML5 Canvas API — the actual compression/resize/crop engine, shared across tools rather than reimplemented per-tool. Cropper.js — for interactive cropping UI specifically (aspect-ratio locking, circular crop for signatures) rather than rebuilding drag-handle math from scratch. Pica — for high-quality image downscaling; the browser's native canvas scaling can introduce visible aliasing on large downscales, and Pica's algorithm handles this noticeably better. Cloudflare Pages — static hosting with edge caching, which matters since 100% of the actual processing work happens in the user's browser, not on any server at all. Lesson 1: Route-level code splitting isn't optional past a handful of tools With React Router and dynamic import() , each tool becomes its own chunk: const PhotoResizer = lazy (() => import ( ' ./tools/PhotoResizer ' )); const PdfCompressor = lazy (() => import ( ' ./tools/PdfCompressor ' ));

📓 Stop Memorizing English — I Built an AI App That Actually Works ⚡ The Hook You try to learn English. You memorize words. And then… you forget them. 🧠 The Real Problem Most people learn English the wrong way: memorizing random word lists switching between apps and dictionaries learning without context That’s why nothing sticks. 🚀 The Idea What if learning English felt like this: 👉 You read something interesting 👉 You click a word you don’t know 👉 You instantly understand it No interruptions. No friction. ✨ Introducing: English Notebook A modern AI-powered app where you learn English by interacting with real content . generate stories click unknown words build vocabulary automatically 🤖 Generate Stories Based on Your Level This is one of the most powerful features. You choose your level: A1 → Beginner A2 B1 B2 C1 C2 → Advanced And the app generates a custom story just for you . 🖼️ Story Generator 📖 Learn by Clicking Words No more: copy-pasting opening dictionary tabs losing focus Just click any word: definition translation (your language 🌍) example sentences 🖼️ Word Interaction 📚 Smart Vocabulary Notebook Every word you click: 👉 automatically saved 👉 turned into a flashcard You can: review anytime mark as mastered ✅ 🖼️ Vocabulary Notebook 📊 Track Your Progress (Game Changer) This is where things get serious. You don’t just learn — you measure your growth . Dashboard shows: total words learned active vs mastered words daily streak 14-day activity trend 🖼️ Dashboard What gets measured gets improved. 🕘 Nothing Gets Lost (History System) Every story you generate is saved. You can: revisit old stories continue reading anytime track your learning journey 🖼️ History 🔊 Learn with Audio listen to stories follow highlighted words improve pronunciation naturally 🌍 Multi-Language Support You can choose your translation language: Persian 🇮🇷 Arabic Spanish Hindi and more 🎯 Why This App Is Different Most apps: ❌ force memorization ❌ feel like school ❌ break your focus English Note

It's been a good few weeks for games on rails. Nintendo's Star Fox remake wisely kept the tightly scripted, action-packed levels from Star Fox 64 largely the same, and they're still fun to fly through nearly 20 years later. Denshattack!, a new game from Undercoders, similarly features levels packed with carefully orchestrated sequences to great […]

Why some records should be created by your system, not your users, and how to do it safely in .NET. A support ticket lands on your desk: "The Teams page is empty. I added a member, but no team shows up." You check the API. It's behaving exactly as written: { "items" : [], "totalCount" : 0 } Nothing is broken. And that's the problem. The system is faithfully returning nothing, because the row that the page reads from was never created. Somewhere in your design, you assumed a human would create it first. This article is about a small, recurring design decision that quietly causes empty dashboards, confused users, and "is this a bug?" tickets: who is responsible for creating derived records the user, or the system? and how to let the system do it without introducing duplicate rows or race conditions. The problem Let's use a fictional product: a collaboration tool called Loop . In Loop, the important entities are: An Organization (a paying customer). A Member (a person invited into an organization under a plan). A Team a grouping that members belong to, keyed by (OrganizationId, PlanCode) . The admin dashboard lists Teams . Each team card shows a member count. Here's the catch in the original design: creating a Member wrote a member row. Creating a Team was a separate, manual step an admin was expected to do first. If an admin invited members without first creating the matching team, the dashboard showed nothing even though the members clearly existed. From the user's point of view, they did everything right. From the system's point of view, a required row simply didn't exist. Why it matters The Team record isn't independent information. It is fully derivable from the first member invited under a plan. When one entity's existence is implied by another, forcing a human to create it manually is a design smell. It leads to: Empty states that look like outages. Users can't tell "no data" from "misconfigured." Support load. Every skipped step becomes a ticket. Silent data dr

🇮🇩 Originally written in Indonesian. This English version was AI-assisted and adapted for a more natural reading experience. It is not a literal translation. _open Introduction Lately, I've been having quite a few discussions with frontend developers about the frameworks they use. My question is actually pretty simple. "When you're building a web frontend, what framework do you usually use?" Almost everyone gave more or less the same answer. "It depends on the project." And honestly, I agree. There's no framework that's always the best choice for every situation. However, as the conversation went on, they started sharing their own experiences and preferences. Well... That's when I started noticing an interesting pattern. Among the developers I talked to, quite a few of them mentioned that they usually use Next.js / React for work, while Vue.js is what they often choose for personal projects. The interesting part is... I never actually asked, "What do you use at work?" or "What do you use for personal projects?" That explanation came up naturally as they explained why they preferred certain frameworks. At first, I thought it was just a coincidence. But after hearing the same pattern from several different people... I got curious. Why do so many developers who are comfortable with both frameworks end up separating how they use them? (・_・;) Disclaimer This isn't based on an official survey or research. It's simply an interesting pattern I noticed after talking with several frontend developers. Discussion Vue.js Looking at today's frontend ecosystem, Vue.js is clearly not a small framework. Its community is large. Its documentation is great. Its ecosystem is also quite mature. That said, compared to React and Next.js, its community is still smaller. Then another question comes to mind. If that's the case... Why do so many developers still choose Vue.js for personal projects? From the answers I heard, the main reason wasn't performance. And it wasn't because other framew

Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is...

Why We Built This As developers and builders at Smart Tech Devs , we love analyzing data trends. But when it comes to trading charts—whether it's crypto, stocks, or forex—reading technical signals manually requires hours of screen time. Beginners struggle with complex patterns, and experienced traders often want a quick sanity check on their thesis. We asked ourselves: Can we leverage Vision LLMs to turn static chart screenshots into professional-grade technical analysis reports in seconds? That question led us to build and launch Realtime Chart Analyzer (ChartAI Pro) , now live on the Google Play Store! ⚡ Key Architectural Features We designed ChartAI Pro to act as a seamless, secure second pair of eyes for market charting. Here is a breakdown of what the application delivers right out of the box: 🧠 1. Multi-Modal AI Chart Analysis Instant Processing: Upload or snap a screenshot from platforms like TradingView, Binance, Zerodha, Groww, Upstox, or MT4/MT5. Signal Detection: The core engine evaluates market structures to return clear Bullish or Bearish indicators alongside an AI confidence score. Plain-English Summaries: No overly dense academic jargon—you receive an intelligible breakdown of current market conditions. 🎯 2. Automated Key Price Levels & Patterns Support & Resistance: The system instantly flags primary macro price horizons. Risk Mitigation: Calculates approximate entry zones, mathematical target price targets, and clear Risk/Reward ratios. Geometric Processing: Detects complex shapes including Head & Shoulders, Double Tops/Bottoms, Triangles, Wedges, Flags, and specialized candlesticks (Doji, Engulfing lines). 📊 3. Native Live Market Infrastructure Live Scanners: Includes a built-in terminal tracking real-time crypto, forex, and stock prices (NSE & BSE). Interactive Tooling: Features built-in interactive TradingView frames directly in the layout, allowing you to scan Top Gainers and Losers without hopping between apps. 🔒 Privacy & Security First When d

I was tired of studying security tools from static cheatsheets, so I built ShellStack When I started prepping for CEH and doing more CTFs, I ran into the same wall over and over: every resource for learning offensive security tools was either a wall of text in a PDF, a GitHub gist with no context, or a cheatsheet that assumed you already knew what half the flags did. I didn't want notes. I wanted something that felt like sitting at an actual terminal — where I could browse tools, see real commands with context, and build the exact command I needed without digging through five tabs. So I built ShellStack . 🔗 Live: https://shell-stack.vercel.app/ 💻 Code: https://github.com/shlokkokk/ShellStack What it actually does ShellStack is a cybersecurity study platform built around one idea: learning security tools should feel operational, not passive. 280+ curated offensive security tools , organized into 19 categories, each with deep-dive docs — commands, common flags, when to use it, installation notes, and real examples Interactive command builders — instead of memorizing flag combos, you fill in a form and get a ready-to-copy command generated live 20 CEH-aligned learning modules , built for structured study instead of flipping through slides 1,000+ command cheat sheet with fast search and one-click copy A terminal-inspired UI that actually feels like a cyber-ops console instead of another docs site The build Stack: React 19, TypeScript, Vite, Tailwind CSS, GSAP, React Router, Radix UI primitives A few things I focused on: Search that actually ranks results. Early on, tool search was just naive string matching, which meant typing "nmap" could bury the actual Nmap entry under ten unrelated tools that happened to mention it in a description. I rebuilt it to weight exact and prefix matches higher, so the tool you're looking for shows up first, not buried on page 3. Command builders that don't feel like a form. The tricky part wasn't the UI, it was designing a data model that

Week 0 of my DevOps Micro Internship was about the foundations—the parts of the internet you use every day without thinking about them. The exercise that made it click was a simple scenario: a friend launches an online bookstore called EpicReads, hosted on a server in Finland, and asks how people anywhere in the world can open it. The answer is a short chain of technologies working together. The Chain of Technologies Packet Switching: When someone opens the site, their request does not travel as one big lump. Packet switching breaks the data into small packets that each take the best available path across the network and get reassembled at the other end. This is what keeps the internet fast and resilient even across continents. IP Addresses & TCP/IP: Every device on the way has a unique IP address, like a postal address, so the user's computer and the Finland server can actually find each other. The TCP/IP suite runs the conversation: IP handles addressing and routing, while TCP makes sure the packets arrive complete and in the right order, asking again for anything that went missing. HTTP & HTTPS: On top of that sits HTTP and HTTPS, which define how the browser and server actually exchange the web pages. HTTPS adds encryption, so a customer's details and payment stay private. DNS: The last piece is DNS. Nobody wants to type an IP address, so DNS acts as the internet's phonebook, translating epicreads.com into the server's IP. To point a domain at an IPv4 address, you use an A record . The Biggest Takeaway The biggest lesson for me was not any single term. It was seeing how these layers hand off to each other so cleanly that the whole thing feels instant to a user. Understanding that chain is the groundwork for everything else in DevOps, because once you know how a request really travels, troubleshooting stops being guesswork. P.S. This post is part of the DevOps Micro Internship with Agentic AI Cohort 3 by Pravin Mishra. You can begin your DevOps journey by joining

Wer digitale Finanzprodukte baut, trifft früh eine grundlegende Entscheidung: native App, installierbare Desktop-Software oder eine Anwendung, die komplett im Browser läuft. Capitnex hat sich für den letzten Weg entschieden. Der WebTrader ist als browserbasierte Umgebung angelegt und benötigt keine lokale Softwareinstallation. Aus Produkt- und UX-Sicht ist genau diese Weichenstellung der spannendste Ausgangspunkt, weil sie fast jede weitere Gestaltungsentscheidung beeinflusst. Auch für Leser, die nicht handeln möchten, lohnt der Blick darauf, wie ein solches Produkt aufgebaut ist. Der Browser als Laufzeitumgebung Eine Anwendung ohne Installation senkt die Einstiegshürde spürbar. Es gibt kein Setup, keine Versionskonflikte auf dem Endgerät und keine Betriebssystembindung, mit der sich Anwender beschäftigen müssen. Der Zugang erfolgt über einen gängigen Webbrowser, und die Oberfläche steht damit unabhängig vom konkreten Gerät bereit. Für Entwickler hat dieser Ansatz eine klare Konsequenz: Die gesamte Darstellung muss auf unterschiedliche Bildschirmgrößen und Eingabearten reagieren. Capitnex beschreibt die Oberfläche als responsiv und konfigurierbar, was genau diese Anforderung adressiert. Der Verzicht auf ein lokales Client-Programm ist deshalb keine Nebensache, sondern eine Produktentscheidung mit Folgen für Verteilung, Wartung und die Konsistenz über verschiedene Endgeräte hinweg. Ein weiterer Effekt betrifft die Zugänglichkeit im weiteren Sinn. Wenn eine Anwendung ohne vorherige Installation erreichbar ist, entfällt eine ganze Klasse von Hürden, die sonst zwischen Interesse und erstem Zugriff liegen. Kein Download, keine Rechteverwaltung auf dem Gerät, keine Rücksicht auf ältere Hardware-Anforderungen. Die Anwendung trifft den Nutzer dort, wo er ohnehin arbeitet, nämlich im Browser. Das ist keine formale Barrierefreiheit im engen technischen Sinn, aber es ist eine bewusst niedrige Einstiegsschwelle, die in der Produktkonzeption angelegt ist. Informationsarchitektur

Balmuda has engineered a remarkably pleasant breeze with its new NatureWind Studio, but is it worth hundreds more than its competition?

Artikel ini juga tersedia dalam bahasa Inggris Pendahuluan Beberapa waktu terakhir saya sering berdiskusi dengan beberapa frontend developer mengenai framework yang mereka gunakan. Pertanyaan saya sebenarnya sederhana. "Kalau membuat frontend web, biasanya pakai framework apa?" Hampir semuanya memberikan jawaban yang kurang lebih sama. "Tergantung kebutuhan." Dan saya setuju. Tidak ada framework yang selalu menjadi pilihan terbaik untuk semua kondisi. Namun, setelah pembahasannya berlanjut, mereka mulai menceritakan pengalaman dan preferensinya masing-masing. Nah... Di sinilah saya mulai menemukan pola yang menarik. Dari beberapa developer yang saya ajak berdiskusi, cukup banyak yang mengatakan bahwa mereka lebih sering menggunakan Next.js / React untuk pekerjaan, sedangkan Vue.js lebih sering digunakan untuk personal project. Padahal saya tidak pernah bertanya, "Kalau kerja pakai apa?" atau "Kalau project pribadi pakai apa?" Penjelasan itu muncul begitu saja ketika mereka mulai menjelaskan alasan di balik framework yang mereka pilih. Awalnya saya mengira itu hanya kebetulan. Tapi setelah mendengar pola yang sama dari beberapa orang... Saya jadi penasaran. Kenapa banyak developer yang sudah menguasai keduanya justru memilih memisahkan penggunaannya? (・_・;) Disclaimer Tulisan ini bukan hasil survei atau penelitian resmi. Ini hanyalah pola yang saya temui dari beberapa frontend developer yang sempat saya ajak berdiskusi. Pembahasan Vue.js Kalau melihat ekosistem frontend saat ini, Vue.js jelas bukan framework yang kecil. Komunitasnya besar. Dokumentasinya bagus. Ekosistemnya juga sudah cukup matang. Namun memang harus diakui, jika dibandingkan dengan React dan Next.js, komunitasnya memang masih lebih kecil. Lalu muncul pertanyaan. Kalau begitu... Kenapa masih banyak yang memilih Vue.js untuk personal project? Dari beberapa jawaban yang saya dengar, ternyata alasan utamanya bukan karena performa. Bukan juga karena framework lain kurang bagus. Melainkan karena pengalama