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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 […]

A fast, beautiful, and native FTP/SFTP client for macOS Discussion | Link

There’s no better time to get a Kindle than during Amazon's own sale event.

Move over, spring cleaning. These vacuum deals will give your home the cleanest summer yet thanks to Amazon Prime Day.

From MacBooks to gaming laptops, these are the very best deals on some of my very favorite laptops for Amazon Prime Day.

AI community manager that hypes up your Discord server Discussion | Link

TL;DR Welcome back to Dev Opportunity Radar. This is a weekly series where I share opportunities,...

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!