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This is a submission for the GitHub Finish-Up-A-Thon Challenge What I Built I built TradeWeave — a B2B + B2C fashion marketplace that connects small scale weavers and manufacturers directly to customers and retailers, eliminating middlemen entirely. The project started as a notebook idea at midnight: "What if factory workers and artisans could sell directly, keeping the full margin instead of losing 40% to supply chain bloat?" Demo 🔗 Live Demo — TradeWeave — Try it right now, no installation needed How to use: Hover over any dress card — it flips to reveal sizes Pick a size, adjust quantity, click "Add to cart" Click "Sign up" to see the premium registration flow Click the TradeWeave logo 5 times to unlock the hidden admin dashboard Click "Wholesale" tab to see direct manufacturer listings 💻 Source Code: github.com/Deeraj25/tradeweave The Comeback Story Before: Idea scribbled in a notebook at midnight Zero code written Zero deployment Tucked away under "someday projects" Status: Abandoned After: Full-featured marketplace in production ~550 lines of polished HTML/CSS/JavaScript Deployed live on Netlify + GitHub Pages Anyone can use it instantly Real product with real features Core fixes: Built the entire marketplace from scratch (this was a notebook idea, not existing code) Implemented hover-to-flip cards with CSS 3D transforms (perspective + rotateY) Created responsive product grid with auto-fill layout Built localStorage persistence for cart + admin state What Changed, Fixed, and Added Features added: 5 product categories with 20+ items Hover-flip interaction (no page reload needed) AI Try-On modal with upload UX Wholesale B2B portal with manufacturer data Hidden admin dashboard (5-click unlock) Aurora-style signup with animated hero and steps Real-time analytics dashboard (revenue, top categories, order table) Mobile-responsive design Keyboard + mouse support Polish & optimization: Custom animations (staggered reveals, floats, shimmers) Cormorant Garamond typograp

If you’ve been following my previous posts, you know I’m a big advocate for Trunk-Based Development and shrinking your pull requests until they almost feel too small. In a perfect world, developers merge code directly into the main branch multiple times a day, everything flows smoothly, and production remains rock solid. But let’s be honest. When you actually try to pitch this to a backend team working on a core system, you almost always hit the exact same wall of resistance. Someone in the back of the room will inevitably raise their hand and ask: “That sounds great in theory, but I’m currently refactoring our legacy checkout service. It’s going to take me four days of deep architectural changes. Are you seriously telling me I should merge half-baked, broken code into the main trunk and push it straight to production where real customers are buying our products?” It’s a completely valid objection. If your only tool for hiding uncompleted work is holding onto a massive, long-lived feature branch, then trunk-based development breaks down immediately. You end up with the exact nightmare we talked about earlier: huge code reviews, painful merge conflicts, and code that rots before it ever sees a live environment. To make continuous delivery actually work without causing catastrophic production outages every single afternoon, you need to decouple two concepts that most engineering teams mistakenly treat as the exact same thing: Deployment and Release . Last article in this category is focused on Trunk-Based Development: https://codecraftdiary.com/2026/05/18/trunk-based-development-roadmap/ The Core Concept: Shifting Left by Decoupling In traditional development setups, deploying code and releasing a feature happen simultaneously. You merge your giant feature branch, the CI/CD pipeline runs, the code hits the live servers, and boom—your users immediately see the new functionality. This model is incredibly high-stakes. If something goes wrong, your only options are rollin

This is a submission for the GitHub Finish-Up-A-Thon Challenge What I Built SpendWise AI is a free tool that audits your AI tool spending (Cursor, Copilot, Claude, ChatGPT, Gemini, Windsurf) against verified vendor pricing and tells you exactly where you're overspending and what to do about it. I originally built this as a week-long assignment for a startup. The problem it solves is simple: founders and engineering managers pay for multiple AI tools but have no idea if they're getting ripped off. SpendWise gives them that answer in under a minute, no signup needed. The interesting part is that the core audit engine has zero AI in it. It runs 6 hardcoded rules against verified pricing data, so every recommendation is reproducible and verifiable. AI (Groq's Llama 3) only kicks in to write a friendly summary paragraph on top of the structured results. I made this choice because financial recommendations need to be deterministic. Same input, same output, every time. The stack is Next.js 16, TypeScript, Tailwind + shadcn/ui, Supabase for the database, Groq for AI summaries, Resend for emails, and Vitest for testing. Deployed on Vercel. Live app: spendwise-ai-test.vercel.app Source code: github.com/Karam-999/SpendWise-AI Demo The original audit tool: The comeback (re-audit on pricing change): You can try the Round 1 version live at spendwise-ai-test.vercel.app . Pick a tool like Cursor on Teams plan at $40/mo, run the audit, and see the full savings breakdown. The Round 2 features (pricing change detection, re-audit diff view) are on a separate branch and not merged to main yet, but the demo video above walks through the complete flow. The Comeback Story Where it was: The original version was basically a calculator. You fill in your AI tools, it shows you where you can save money, and that's it. If Cursor changed its pricing the next week, your audit was already stale and you'd never know about it. It worked fine as a one-time thing. It had the form, the audit engine, AI

Most side projects start with a simple frustration. Mine started with a banking app. One of my banks had a feature I really liked. It automatically categorized transactions and showed spending breakdowns in graphs and charts. For the first time, I could easily see how much I spent on restaurants, groceries, transport, subscriptions, and other categories. The problem was that only one of my banks offered this feature. Like many people, I use multiple bank accounts, credit cards, and savings accounts. Two of my other banks provided little more than a long list of transactions. If I wanted a complete picture of my finances, I had to switch between apps and manually piece everything together. As a software engineer, my first instinct was obvious: "Why don't I just build this myself?" That idea eventually became MyVault . The Original Goal The first version of the project was surprisingly simple. I wanted users to: Upload bank statements Extract transaction data Automatically categorize spending View useful charts and reports The goal wasn't budgeting. It wasn't investment tracking. It wasn't accounting. I simply wanted a single place where I could see spending across all of my bank accounts. Once I started building, however, I realized there was a much more interesting opportunity. If all transaction data was already extracted and structured, why not allow users to ask questions about their finances? Instead of searching through transactions manually, users could simply ask: How much did I spend on restaurants last year? What subscriptions am I paying for? Which categories increased the most this month? How much did I spend while traveling? That's when MyVault started evolving from a reporting tool into an AI-powered financial assistant. Building as a Solo Developer One of the biggest challenges wasn't technology. It was building everything alone. When you're working on a side project, you don't just write code. You become responsible for everything: Product decisions B

The Problem If you've ever audited your Windows network traffic during a boot-up sequence, you know the truth: there's a "blind spot." Between the moment your network drivers initialize and your VPN/WireGuard tunnel actually establishes, your traffic is leaking. Many third-party solutions exist, but they are often bloated, use proprietary binaries, or act as black boxes. I wanted something transparent, native, and bulletproof. The Solution: WG-KillSwitch I developed a pure PowerShell-based kill switch architecture. It doesn't rely on third-party libraries—it uses native Windows system components to enforce security. Key Architectural Features: Zero-Trust Firewall Matrix: Hardens the system by blocking all outbound traffic by default, allowing only authenticated tunnel traffic. WMI Persistent Watchdog: Unlike standard scripts that can be killed via Task Manager, this project uses WMI Event Subscriptions. If the watchdog process is terminated, Windows itself immediately respawns it. Resilience: Survives hard reboots, modem resets, and Windows service cycling. Resilience & Leak Testing I've put this through a gauntlet of tests: Forced Reboots: Zero leaks detected during driver load. Process Termination: The WMI engine restores the protection in milliseconds. Dynamic Network Resets: The firewall matrix remains active regardless of adapter status. Let's Collaborate This is open source, transparent, and built for the community. I'm looking for security audits and feedback. Check out the source code, open an issue, or submit a PR: https://github.com/ryderlacin-pixel/Windows-WireGuard-KillSwitch

The original babel-plugin-transform-flow-strip-types hasn't been updated in 9 years and breaks silently in Babel 7 and 8 environments. The fix I published a maintained fork that works as a drop-in replacement: npm install --save-dev babel-plugin-transform-flow-strip-types-maintained Then update your .babelrc: { "plugins": ["transform-flow-strip-types-maintained"] } That's it. No other changes needed. What's fixed Babel 7 and 8 peer dependency conflicts Missing syntax plugin declaration Deprecated visitor patterns allowDeclareFields support Automated migration If you want to update your entire project automatically: npx flow-strip-migrate . This updates your package.json and babel config in one command. More info: https://flowstrip.netlify.app npm: https://www.npmjs.com/package/babel-plugin-transform-flow-strip-types-maintained

I'll give the usual caveat: The horror novel Japanese Gothic is best experienced going in with as little information as possible. Content warnings for graphic gore, scenes of domestic violence, self-harm, and mental illness. If you're okay with that, then consider pausing here. While I will try to keep this relatively spoiler-free, there will be […]

The 2026 XPS 14 is the best premium laptop we've seen from Dell in a while, with incredible build quality in a thin machine and good performance thanks to Intel's Core Ultra Series 3 "Panther Lake" chips. A bonus: Dell killed its lame "Premium Plus" naming scheme. XPS is so back! I can't believe how […]

This is a submission for the GitHub Finish-Up-A-Thon Challenge. I’ll keep this short since the repo...

Every time I started a side project, I rebuilt the same five things before I wrote a single line of the actual idea: auth, a database, file uploads, a deploy pipeline, and TLS. Different domain, same plumbing. By the third project I was copy-pasting my own docker-compose.yml from a folder two repos over and renaming things until they stopped erroring. So I stopped. I froze that plumbing into one boilerplate — PocketBase + Next.js + Caddy on a single cheap VPS — and now I ship every side project on it. Same shape every time: clone, rename, write the part that's actually new, push. The thing I care about most isn't the speed, though. It's that I stopped paying for it. A handful of real projects now run on this setup for a few euros a month, total — not a stack of per-service SaaS bills that each want $25 here and $20 there before you've shipped anything. No Vercel seat, no managed Postgres, no Auth-as-a-Service, no object-storage line item. Here's the whole thing. Why this stack The trick that makes the cost collapse is PocketBase . It's a single Go binary that gives you, in one process: Auth — email/password, OAuth, the works, with a real users collection A database — SQLite, with a schema you manage from an admin UI Realtime — subscribe to collection changes over SSE File storage — uploads handled, with on-the-fly thumbnails An admin dashboard — at /_/ , for free That's four or five separate SaaS products collapsed into one binary that runs anywhere and stores everything in a folder. Compared to wiring up Supabase or Firebase, the mental model is tiny: it's one process and one data directory. Back up the directory and you've backed up the entire app — database, uploaded files, auth tokens, all of it. For the front I use Next.js (App Router, React Server Components) because that's where I'm fastest, and Caddy as the reverse proxy because it gets you automatic HTTPS with zero config — it provisions and renews Let's Encrypt certificates on its own. And it all lives on

Most organizations still think of the hypervisor as a resource abstraction layer. CPU. Memory. Storage. The platform that decides where workloads run. That mental model is increasingly incomplete. Every major virtualization platform — vSphere, AHV, Proxmox — has been steadily accumulating policy enforcement responsibilities. The hypervisor isn't just deciding where workloads run. It's increasingly deciding what they're allowed to do. The Speed of the Shift Is the Real Story Virtualization practitioners already know security controls have moved downward through the stack. What's less appreciated is how compressed the most recent phase has been. For years, hypervisors enforced resource allocation. Within a single platform generation cycle, that same layer accumulated encryption policy enforcement, workload trust validation, microsegmentation, secure boot enforcement, host attestation, and workload isolation boundaries — not as optional add-ons, but as core platform capabilities. The perimeter-to-OS transition took decades. The hypervisor accumulated a comparable policy enforcement surface in the time between one major vSphere release and the next. That compressed timeline is what creates the ownership lag — the governance model adequate for a resource scheduler has not caught up to a platform that enforces organizational policy. The Hypervisor Now Makes Binding Decisions The distinction that matters: a platform that observes policy versus a platform that enforces it. The hypervisor is no longer observing. It is enforcing. VM fails attestation → workload does not start. Encryption policy mismatch → workload cannot migrate. Segmentation policy violation → communication blocked at the platform layer. Trust validation failure → host removed from workload eligibility. Those are not scheduling decisions. Those are governance outcomes. The workload doesn't get a vote. This is what makes the hypervisor governance infrastructure : infrastructure that directly enforces organiza

If you have ever submitted an iOS application to Apple's App Store and received a cryptic rejection notice about icon specifications, you are not alone. Apple's human interface guidelines for icons are extraordinarily precise — and for good reason. The iOS ecosystem spans devices from the tiny Apple Watch to the expansive iPad Pro, each requiring icons at exact pixel dimensions to render correctly across Retina, Super Retina XDR, and ProMotion displays. Understanding iOS icon sizes is not optional. It is a prerequisite for shipping. Every pixel dimension you provide must match Apple's specifications exactly, must use lossless PNG format, must not include transparency, and must be delivered with the exact filename that Xcode expects. One missed size, one wrong filename, and your project fails to build correctly. Precision is not a suggestion — it is a hard requirement enforced by Xcode's build system. iPhone Icon Sizes For iPhone applications, the required icon sizes span multiple uses within the operating system. The App Store listing requires a 1024×1024 pixel icon. The home screen displays icons at different sizes depending on device generation and display density. Notification icons, Spotlight search results, and Settings app icons all require their own specific dimensions. Usage Scale Size (px) Filename Convention App Store 1× 1024×1024 Icon-1024.png Home Screen 2× 120×120 Icon-60@2x.png Home Screen 3× 180×180 Icon-60@3x.png Spotlight 2× 80×80 Icon-40@2x.png Spotlight 3× 120×120 Icon-40@3x.png Settings 2× 58×58 Icon-29@2x.png Settings 3× 87×87 Icon-29@3x.png Notification 2× 40×40 Icon-20@2x.png Notification 3× 60×60 Icon-20@3x.png iPad Icon Sizes iPad adds its own set of required sizes, particularly because of the larger screen real estate and different display densities. Xcode's asset catalog system requires each icon to be placed in the correct slot, and any missing slot will prevent archiving for App Store submission. This makes completeness not just a best p

Search engine optimization doesn't require expensive tools. Your browser's built-in developer tools can identify and diagnose most SEO problems in under 15 minutes. Here are the 11 most impactful SEO checks you can run directly from Chrome DevTools. 1. Check Meta Description Length Right-click any element, Inspect, expand <head> , find <meta name="description"> . Metric Optimal Range Meta description length 120-155 characters Title tag length 50-60 characters H1 count per page Exactly 1 const meta = document . querySelector ( ' meta[name="description"] ' ); const len = meta ? meta . content . length : 0 ; console . log ( `Meta description: ${ len } chars` ); 2. Verify Only One H1 Tag Exists const h1s = document . querySelectorAll ( ' h1 ' ); console . log ( `H1 count: ${ h1s . length } ` ); A study of 1.2 million pages found pages with one H1 ranked 12% higher on average. 3. Find Images Missing Alt Text const imgs = document . querySelectorAll ( ' img ' ); const missing = [... imgs ]. filter ( i => ! i . alt || i . alt . trim () === '' ); console . log ( ` ${ missing . length } of ${ imgs . length } images missing alt text` ); Pages with complete alt text see 3.7% higher image search visibility. 4. Detect Render-Blocking Resources Open DevTools, Network tab, reload, click "Blocking" filter. Resources in red block first contentful paint. Total blocking time under 200ms More than 20 render-blocking resources signals a problem Each render-blocking CSS file adds 50-300ms to page load 5. Check Canonical Tag Consistency const canonical = document . querySelector ( ' link[rel="canonical"] ' ); console . log ( canonical ? `Canonical: ${ canonical . href } ` : ' No canonical tag ' ); 6. Audit Internal Links const links = [... document . querySelectorAll ( ' a[href] ' )]; const internal = links . filter ( l => { try { return new URL ( l . href ). hostname === window . location . hostname ; } catch ( e ) { return false ; } }); console . log ( `Internal links: ${ internal . len

Sigma’s new entry is both a bold design experiment and a pretty decent camera.

Tired of uploading your private files to sketchy ad-filled website for conversion and OCR? Meet EasyConvert, a serverless media tool that uses FFmpeg WASM to convert, compress and OCR media files 100% locally. Link: easy-convert.pages.dev Github: https://github.com/nihid7/easyconvert submitted by /u/Fun-Time9529 [link] [留言]

Hey everyone!! sharing something I've been building for the past 2 months. Leafy lets you and your team annotate any webpage. You click an element (or highlight text), leave a comment, @ mention teammates, and they get notified. Comments are anchored to specific parts of the page and sync across devices. Use cases I've seen people use it for: → Product teams reviewing features on their products → Designers leaving feedback on live prototypes → Researchers annotating sources together → QA marking bugs on staging environments → Sales teams using it on salesforce → Students using it for marking interesting things on any page, to study You can organise teams into "Gardens" (I know, quirky naming). Free tier supports up to 3 gardens with 5 members each. I'd love any feedback! especially on what feels broken or missing. Chrome Web Store: https://chromewebstore.google.com/detail/leafy-annotate-the-web-to/doohbmfpjanoimbigjbjocanpenbfkkh https://preview.redd.it/4riy4haubu5h1.png?width=908&format=png&auto=webp&s=69ecac6f3bef7a4843c58095c3d8a5972ff2ceaa Product page: https://get-leafy.com submitted by /u/maxisrichtofen [link] [留言]

Lauf’s sleek new entry feels closer to a traditional mountain bike than anything I’ve ridden before.

The idea is to make it straightforward to find any ffmpeg version and configuration you require, and to have the binaries available for production CI/CD flows without worrying they will expire. submitted by /u/pinter69 [link] [留言]

A bit of context first. I run a service that caches images from paywalled sites so users don't have to load them fresh on every visit. The overwhelming majority of what we cache is PNG - huge, bloated, uncompressed PNG. Naturally, I started looking into smarter storage and serving strategies, and JPEG XL kept coming up as the obvious answer. The compression gains on PNGs especially are remarkable: you can cut file sizes by 50–60% compared to JPEG with minimal perceptible quality loss at equivalent settings. So the plan seemed straightforward: Convert everything to JXL Detect browser support via the Accept header Serve JPEG as a fallback on the fly for unsupported browsers Here's what the numbers actually looked like: Strategy Total Size Savings Do nothing ~51 GB - WebP Q85 (universal) ~12 GB −39 GB JPEG Q92 (universal) ~21 GB −30 GB JXL d=1 + JPEG fallback ~16 GB / ~5 GB −46 GB (85% of users get 76 KB avg) The JXL route has the best savings on paper - but it means storing two versions of everything, or doing on-the-fly conversion, which adds latency. WebP Q85 just wins. Universally supported (~97–98% of browsers globally), −39 GB in savings, no fallback needed. I hate that this is the conclusion, because JXL is better across most technical dimensions that matter Chrome removed JXL support in Chrome 110 in October 2022 - and that removal was the real killer, given Chrome's ~65% global market share. The stated reasons were actually fourfold: experimental flags shouldn't remain indefinitely; insufficient ecosystem interest; insufficient incremental benefits over existing formats; and maintenance burden reduction. Critics, including engineers from Intel, Adobe, Cloudinary, Meta, and Shopify, disputed all of these claims vigorously in what became one of the most contentious threads in Chromium history. In 2026: Google has reversed course. Chrome 145 (released February 2026) ships with a JPEG XL decoder - currently behind a flag, but back in the codebase for the first tim

As the title says, creating and sharing short videos on macOS or Windows has never been a smooth flow for me. I used to screen cap with QuickTime or the NVIDIA. The result were huge .mov or .mp4 file. Then I either need to upload a 600 MB file to an online compressor, open Handbrake, or use ffmpeg from the command line. Ffmpeg is great, but for quick everyday use, but I found myself loosing the text file where I keep the most useful commands to adjust parameters, and it's anying when there are silly error because I forgot a parameter. And if I wanted to trim the video, I usually had to open a separate video editor that take time to open and are sort of overkill for a simple trimming. So I built Compress.mov . The basic flow is simple: drag and drop a video, choose whether you want to trim it, compress it, or both, and get the result automatically saved in your computer. Over time I added more features: audio removal, video rotation, codec selection, video rescaling, multiple languages (german, farsi, japanese...), and a small counter that shows how many lifetime megabytes you’ve saved by using the Compress app. The latest feature I’m testing is video recording, so I don’t have to use QuickTime anymore! This started as a side project on my spare time, and I built it without an AI assistant, so it’s fully handmade 😃 You can try it at compress.mov for FREE and if you become a fun please purchase it at the windows store or App Store to help me stay motivated. submitted by /u/tino-latino [link] [留言]