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

When I first started using Cursor AI , I thought it was just an AI-powered code editor. After spending more time with it, I realized it's much more than that. Cursor isn't just about generating code—it's a development assistant that can understand your project, automate repetitive tasks, connect with external tools, and help you build software much faster. If you're new to Cursor, this guide will explain the most important concepts in simple language with real-world examples. 1. What are Rules? Think of Rules as permanent instructions for Cursor. Instead of telling the AI the same things every time, you define them once and Cursor follows them throughout your project. Example Instead of writing this every time: Use TypeScript Use Tailwind CSS Create reusable components Write clean code You can create a rule like: Always use TypeScript. Always use Tailwind CSS. Never use inline CSS. Create reusable components. Write meaningful comments. Now every prompt automatically follows these instructions. Real-world example Imagine you're working in a company where every developer follows coding standards. Rules are those standards—but for your AI assistant. Benefits Consistent code Less repetitive prompting Faster development Better code quality 2. What are Skills? Skills are reusable instructions for specific types of work. Instead of explaining how to build an API every time, you create one reusable skill. Example: Create Express APIs using MVC architecture. Validate all inputs. Handle errors properly. Use async/await. Now whenever you ask Cursor to create an API, it follows that workflow. Real-world example A plumber has plumbing skills. An electrician has electrical skills. Similarly, Cursor can have reusable development skills. Benefits Reusable workflows Consistent architecture Faster feature development 3. What are Hooks? Hooks are automatic actions triggered by an event. For example: You save a file. ↓ Cursor automatically runs: Formatter Linter Tests You don't have to

Mitigating Hallucinations in Theology AI: Implementing Groundedness Evaluation Pipelines For software developers and indie hackers, the era of building generic wrapper APIs is over. The real value now lies in highly specialized, niche vertical applications. One of the most fascinating, complex, and underserved niches is the intersection of artificial intelligence and religious doctrine. Building a catholic ai tool presents unique software engineering challenges. Unlike general-purpose chatbots, a theology ai application cannot afford to "hallucinate" or generate creative interpretations of established doctrines. In this space, an inaccurate answer is not just a software bug; it is a theological error. To build a high-quality, trustworthy catholic ai app , developers must move past basic prompt engineering. We must implement robust groundedness evaluation pipelines. This article explores the technical journey of building a specialized catholic ai chatbot , the catholic church stance on ai , our choice of tech stack, and how to build a production-grade groundedness pipeline to keep your AI aligned with official church teachings. The Catholic Church Stance on AI: Designing for Ethics and Trust Before writing a single line of Dart, Swift, or Python, we must understand the ethical landscape of ai and theology . The Vatican has taken an surprisingly proactive approach to artificial intelligence. Pope Francis has frequently spoken on the topic, advocating for "algor-ethics"—the ethical development of algorithms. The catholic church stance on ai emphasizes that technology must serve human dignity and remain aligned with truth. ┌─────────────────────────────────┐ │ The Vatican's Algor-ethics │ └────────────────┬────────────────┘ │ ┌─────────────────────────┴─────────────────────────┐ ▼ ▼ ┌──────────────────┐ ┌──────────────────┐ │ Human Agency │ │ Doctrinal Truth │ │ AI must assist, │ │ AI must not alter│ │ never replace │ │ established dogma│ └──────────────────┘ └─────────

It was the middle of a Friday afternoon, and I was sitting in the front row of a local mosque. The room was deathly quiet, the kind of silence that amplifies every heartbeat. Suddenly, three rows behind me, a phone erupted with a loud, brassy ringtone that seemed to go on for an eternity. The man scrambled to silence it, his face turning bright red as he fumbled with his screen. I felt his humiliation deeply. In that moment, I realized that modern smartphones—despite their intelligence—are remarkably stupid when it comes to context-aware social etiquette. We live in a world of smart devices, yet we are still manually toggling our volume settings like it is 2005. I have spent years forgetting to silence my phone before a meeting, a lecture, or a quiet space, only to have it buzz loudly at the worst possible time. It is a friction point that feels trivial until it happens to you, at which point it becomes incredibly disruptive. Existing solutions often fall into two camps: over-engineered automation tools that require a computer science degree to configure, or basic calendar-sync apps that lack the nuance needed for things like location-based triggers or recurring religious observances. I wanted something that just worked, quietly, in the background, without requiring me to constantly open an app to double-check if my rules were still active. When I started building Muffle, I quickly realized that the greatest obstacle wasn't the logic of detecting a location or a prayer time—it was the operating system itself. Android, in its quest to squeeze every millisecond of battery life out of a device, has turned into a minefield for developers trying to keep background tasks alive. If you rely on a standard Service , the system will kill it within minutes as soon as the user turns the screen off. I needed a way to ensure that my background monitoring, especially for geofencing and prayer time calculations, stayed alive even when the phone was sitting in a pocket for hours. I

Build a Complete MERN Stack CRUD App with Image Upload (Step-by-Step) This is a complete step-by-step guide to building a MERN Stack CRUD application with Image Upload using Multer. Let's dive right into the structure and code! 📂 The Complete Folder Structure mern-crud-app/ │ ├── backend/ │ ├── models/ │ │ └── Employee.js │ ├── routes/ │ │ └── employeeRoutes.js │ ├── uploads/ (Make sure to create this empty folder) │ ├── .env │ └── server.js │ └── frontend/ └── src/ ├── components/ │ └── EmployeeManager.jsx ├── App.jsx └── index.css ⚙️ Part 1: Backend Code 1. backend/.env PORT=5000 MONGO_URI=mongodb://127.0.0.1:27017/mock-crud 2. backend/server.js const express = require ( ' express ' ); const mongoose = require ( ' mongoose ' ); const cors = require ( ' cors ' ); require ( ' dotenv ' ). config (); const app = express (); // Middlewares app . use ( cors ()); app . use ( express . json ()); // Setup static folder for frontend image access app . use ( ' /uploads ' , express . static ( ' uploads ' )); // Routes const employeeRoutes = require ( ' ./routes/employeeRoutes ' ); app . use ( ' /api/employees ' , employeeRoutes ); // MongoDB Connection mongoose . connect ( process . env . MONGO_URI ) . then (() => console . log ( ' MongoDB Connected Successfully! ✅ ' )) . catch (( err ) => console . log ( ' MongoDB Connection Failed ❌ ' , err )); app . get ( ' / ' , ( req , res ) => { res . send ( ' Backend Server is Running! 🚀 ' ); }); const PORT = process . env . PORT || 5000 ; app . listen ( PORT , () => { console . log ( `Server is running on port ${ PORT } ` ); }); 3. backend/models/Employee.js const mongoose = require ( ' mongoose ' ); const employeeSchema = new mongoose . Schema ({ name : { type : String , required : true }, email : { type : String , required : true , unique : true }, phone : { type : String , required : true }, designation : { type : String , required : true }, experience : { type : Number , required : true }, salary : { type : Number , required : tru

👋 Hi DEV Community! I'm the creator of Cloud Compass , a newsletter dedicated to making cloud computing easier to understand. If you've ever felt overwhelmed by the constant stream of cloud updates, new services, documentation, and buzzwords, you're definitely not alone. I originally published this as the welcome issue of my newsletter, and I'm sharing it here because I hope it helps developers, students, and anyone starting their cloud journey. ☁️ Welcome to Cloud Compass Cloud news, concepts, and insights without the overwhelm. The cloud is moving fast. Let's make sure you're not left behind. Welcome to Cloud Compass — your guide to staying current with cloud computing while building real cloud knowledge, without feeling overwhelmed. Let's be honest. Keeping up with cloud technology is exhausting. Cloud providers release new services, features, and updates almost every week. Between official documentation, blog posts, YouTube videos, LinkedIn posts, and countless tutorials, it's difficult to know: What actually matters? What should you learn first? Where do you even begin? That's exactly why I started Cloud Compass . This isn't a newsletter written by AI or filled with copied announcements. It's written by someone who genuinely enjoys learning cloud computing and wants to make it easier for everyone else—whether you're: A developer trying to stay current A student entering the cloud world for the first time A professional who wants to understand cloud technology without spending hours reading documentation The goal is simple: Show up regularly with something that's actually useful. "I want Cloud Compass to feel less like reading tech news and more like having a conversation with someone who already read everything and saved you the time." Here's what you can expect 📰 Cloud News Roundup The most important updates from across the cloud industry—not just AWS, Azure, and Google Cloud, but the wider cloud ecosystem. No endless lists of links. No unnecessary hype. Just

Browser automation with Playwright, Python, GitHub Actions, and Entire to auto-enter San Francisco Stern Grove concert lotteries each week!

Looked at 30 products running Meta + TikTok ads profitably. 7 patterns every single one had: PRICE : $25-$65 Below = thin margins. Above = harder impulse. BUNDLE OPTIONS "Buy 2 save 10% / Buy 3 save 15%" — every store had this. None were single-product only. VISUAL HOOK IN 3 SECONDS Unique design, specific problem solved, or "wow factor." Generic products failed. REAL REVIEWS WITH PHOTOS Not 5-star spam. Real, mixed reviews. Even negatives build trust. SHIPPING TIME ON PDP Every store disclosed it directly. None hid it in FAQ. STICKY ADD-TO-CART ON MOBILE All 30 had it. If your Add to Cart scrolls off-screen on mobile, you're losing sales. POST-PURCHASE UPSELL "Add this for $X" / subscription / bulk refill. This is where AOV lives. WHAT THEY DIDN'T HAVE Live chat (only 4/30) Exit-intent popups (only 2/30) Countdown timers (only 3/30) Countdown timers (only 3/30 — most had REAL shipping urgency instead) Multiple payment options visible on PDP (most just had Shopify default) The "guru tactics" aren't what winning stores use. 3 QUICK WINS Pick products with visual hooks Bundle by default Fix PDP before scaling ads

Cross-posted from noflattery.com/decide — where I ran this exact question through a council of four different frontier models and let them argue it out. You're a solo founder at ~$8K MRR. You have runway for exactly one full-time hire. Which role unlocks the most growth? (A) a second engineer to ship features faster (B) a marketer to build a real acquisition channel (C) a customer-success / support hire to cut churn and free your time (D) a salesperson to chase larger deals The intuitive answer for most technical founders is A — more shipping velocity. The case below is for C , and it's stronger than it looks. (With one caveat that can flip the whole thing — stick around for it.) TL;DR: At ~$8K MRR solo, hire customer success first if churn is real or support is eating your week . If voluntary churn is under ~3% and support is light, hire a marketer instead. Engineer and sales come later. The case for customer success first 1. Churn quietly eats growth before features can add it. At $8K MRR, 5% monthly churn is ~$400/month bleeding out before you grow an inch. Across bootstrapped SaaS in the $5–15K MRR band, the strongest predictor of reaching $50K isn't feature velocity or channel — it's net revenue retention above 90% . That's a customer-success function, not an engineering one. 2. You are the bottleneck, and support is eating you. As a solo founder you're doing product, sales, billing, and support. If support takes ~15 hours a week, that's nearly 40% of your capacity — and it's the cheapest thing to hand off. A CS hire costs less than a senior engineer or an experienced salesperson, and it buys back the hours (and the headspace) you need to think strategically again. 3. It's a research department in disguise. A CS hire generates the highest volume of qualitative signal: why people leave, what they actually use, what they'd pay more for. An engineer builds what you think users want. CS tells you what they actually need — which means the engineer you hire next buil

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It’s been hot in London this week. Really hot. A dangerous heat wave has hit Western Europe. Yesterday, the UK recorded its highest ever June temperature at 36.1 °C (about 97 °F). But as the weather app on my phone confirmed, it felt like 39 °C. It’s frightening that we are seeing such temperatures in…

Where's the Trump phone? We're going to keep talking about it every week. We still don't have the phones we preordered yet, but this week the T1 hit open sale, no deposit required. Trump Mobile's T1 Phone is now available for anyone to buy directly. The phone has previously trickled out to a small number […]

I've been working on a different approach to giving AI coding agents context about large codebases. Instead of indexing files by embeddings or feeding hundreds of lines into the model, the idea is to statically classify code into structured semantics. For each file it produces things like: -Primary semantic role (service, repository, controller, DTO, etc.) with the evidence used to reach that conclusion. -Behavioral traits (transaction handling, business rule enforcement, orchestration, event emission, in-memory state, database interaction, etc.). -Architectural relationships and dependency direction. It also works at the function level, so individual methods get their own behavioral classification and relationship hints. The output is structured JSON rather than summaries, so an agent can query it instead of rereading source files. One thing I found interesting is that this often gives agents enough architectural context without spending tokens on large files. Instead of inferring "what is this class?", they already know something like: Domain service, performs transactional DB writes, enforces business rules, emits events, depends on persistence and event layers. Beyond agent context, the same information seems useful for architectural analysis—tracking responsibility drift, identifying layering violations, or seeing when a service gradually accumulates unrelated behaviors. I've been testing it on Medusa (TypeScript) so far, and the results have been promising, although there are still plenty of edge cases. I'm curious how others are approaching this. If you're building coding agents or working with large monorepos, what's been the hardest part of codebase understanding? Context size, architectural reasoning, stale indexes, something else? submitted by /u/Zealousideal_Ant4747 [link] [留言]

Every small task used to mean a new tab. JSON formatter on one site, GST calculator on another, PDF merger somewhere that wanted my email before it would merge two pages. Ads everywhere, slow UIs, and that low-grade worry about uploading a payslip or invoice to a server I do not control. I got tired of juggling twenty bookmarks for work that should take thirty seconds — so I started building one place for all of it. What ToolReign is ToolReign is a free online toolbox: 260+ utilities across 15 categories , all running in your browser. Developer tools (JSON formatter, JWT decoder, API client), text utilities, SEO helpers, PDF and image tools, spreadsheets, and a finance section I built with India in mind — GST with CGST/SGST/IGST splits, EMI and SIP calculators, HRA exemption, gratuity, income tax estimates, and more. The idea is straightforward: open a tool, do the work, leave. No signup wall, no file uploads to a backend, no account to manage. I am Anirudha Sonwane , a Senior Software Engineer at Giant Leap Systems in Pune. ToolReign is a side project I build around my day job — not a pitch deck, just something I wished existed. The tech stack decisions Next.js 14 App Router and static export Each tool lives at its own route under src/app/{category}/{tool-slug}/ . That maps cleanly to SEO: one URL, one search intent, one page of metadata. The site exports statically ( output: 'export' ), so production deployment is uploading an out/ folder to static hosting — no Node server to babysit. The App Router made this scale. Add a page component, register the slug in tool-registry.json , and the sitemap, category hubs, and search index pick it up automatically. At 260+ tools, hand-maintaining URLs would have broken within a month. 100% client-side — the decision that shaped everything This was the core architectural bet, and it is also the privacy story: your data never leaves the browser. Finance calculators are plain TypeScript math with useMemo . PDF merge and split use

React dialogs often start simple. You add an isOpen state, then a selected item state, then confirm/cancel callbacks, then another dialog after the first one. Eventually, a simple flow can become scattered across multiple components. For example, a user flow like this: Select a user Confirm the action Add the user often becomes multiple pieces of state: const [ isUserSearchOpen , setIsUserSearchOpen ] = useState ( false ); const [ isConfirmOpen , setIsConfirmOpen ] = useState ( false ); const [ selectedUser , setSelectedUser ] = useState < User | null > ( null ); This works, but the actual flow is harder to read. What if dialogs could be handled as async flows? I wanted the code to read closer to the user flow: const user = await openAsync ( UserSearchDialog ); if ( ! user ) return ; const confirmed = await openAsync ( ConfirmDialog , { title : `Add ${ user . name } ?` , }); if ( confirmed ) { await addUser ( user . id ); } The dialog opens, waits for a result, and the caller continues based on that result. This is about orchestration, not UI This is not meant to replace Radix, MUI, Headless UI, shadcn/ui, or custom dialog components. Those libraries solve the dialog UI problem well. The idea here is to manage the flow around dialogs: opening dialogs from anywhere under a provider resolving typed result values handling nested dialogs distinguishing completed vs dismissed supporting dismissal reasons guarding close behavior with shouldClose So the actual dialog UI can still be your own component. I packaged the pattern I turned this idea into a small open-source library called react-dialog-flow . It provides a headless dialog stack, Promise-based openAsync , typed results, nested dialogs, closeTop , closeAll , dismissal reasons, shouldClose , and optional UI primitives. GitHub: https://github.com/CHOKANGYEOL/react-dialog-flow npm: https://www.npmjs.com/package/react-dialog-flow Docs: https://dialog-flow.kangyeol.com/ It is still early, so I am mainly looking for feed

You already understand tokens. Extensions are just middleware for your money. If you have ever worked with Stripe, you know the pattern. You start with a simple charge: send money from point A to point B. Then you add features — subscriptions, transfer fees, metadata on invoices, compliance checks. Each feature is a separate Stripe product or API call, and wiring them together is your job. Solana's Token Extensions Program is the same idea, but at the blockchain protocol level. Instead of bolting features on top of a basic token after creation (which Solana does not allow), you declare every capability upfront, and the runtime enforces it automatically. No smart contract to write. No backend service to maintain. Just configuration flags at creation time. What is a token extension? A token extension is an optional feature you enable when you create a token mint. Under the hood, each extension reserves extra bytes in the mint's on-chain account. Those bytes store configuration — an interest rate, a fee percentage, a metadata URI — and the Solana runtime reads them during every transaction. The original SPL Token Program is simple. It stores supply, decimals, and authorities. The Token Extensions Program ( TokenzQdBNbLqP5VEhdkAS6EPFLC1PHnBqCXEpPxuEb ) is a superset. It stores everything the original does, plus additional data for each extension you enable. Extensions map directly to Web2 concepts Extension Web2 Analogy What It Does Transfer Fees Payment processor fee Deducts a % on every transfer Interest-Bearing Savings account APY Displays time-adjusted balance Metadata Product catalog entry Stores name, symbol, URI on-chain Default Account State KYC gating All accounts start frozen; you thaw approved users Non-Transferable Professional license Tokens cannot be sold or transferred Permanent Delegate Admin revoke power Issuer can burn tokens from any holder A concrete example Here is the exact command I ran to create a token with transfer fees, interest-bearing, and m

I spent 3 months building a tool that solves the most annoying part of working on a dev team. You know the drill: → New dev joins → "hey check your DMs" → Someone pastes the .env in Slack → That message sits there forever → 6 months later someone screenshots it by accident or worse — → git add . → git commit -m "added env" → git push → you just leaked your prod database URL to the internet I got tired of it. So I built DotSync. ─────────────────────────────────── Here's what it looks like in practice: $ dotsync push 🔒 Encrypting 10 secrets for team access... 📤 Uploading... ✅ Version : v7 Secrets : 10 keys encrypted Teammates can now run: dotsync pull That's it. New dev joins? They run dotsync pull. Secrets updated? dotsync push. Moving between your laptop and work machine? dotsync pull. ─────────────────────────────────── The part I actually care about — security: Everything is encrypted ON your machine before it hits the network. The server stores a blob it literally cannot read. I'm not asking you to trust my infrastructure. You don't have to. Stack if you're curious: • Argon2id key derivation (64MB memory cost — brute force isn't happening) • AES-256-GCM encryption • Zero-knowledge server (stores ciphertext only) • Single Go binary, no runtime deps ─────────────────────────────────── Other things it does that I use daily: dotsync diff → shows exactly which keys changed vs remote (never shows values) dotsync history → full version history, who pushed what and when dotsync rollback → restore any previous version in one command dotsync run -- node server.js → injects secrets as env vars, nothing written to disk dotsync scan → scans your codebase for accidentally committed secrets ─────────────────────────────────── Free tier covers: • 1 project • 3 team members • 7 days history That handles most small teams completely free. ─────────────────────────────────── Now the part where I need your help: I'm looking for 100 engineers to actually stress test this. Not "give i

Hi folks! I’m the architect behind WLOADCTL, a commercial workload scheduling system for enterprise automated task orchestration and RPA docking. A quick share of my daily work focus: Distributed task scheduling core development with Java & C Cross-system automation scripts built by Python & Shell Backend frontend based on SpringBoot + Vue3 Edge traffic protection & access optimization using Cloudflare Enterprise RPA integration to automate repetitive backend operations I’ve been tackling a lot of real-world pain points like cross-Linux distro compatibility, high-frequency API access security and mass task concurrency control recently. If you’re working on workload scheduling, backend automation or Cloudflare security tuning, feel free to leave a comment to chat!