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As developers, we often need to store webhook URLs, service endpoints, configuration strings, and other values that we don't want exposed directly in frontend code. Most solutions either require setting up a backend, paying for a service, or managing API keys. API URL (Generate your endpoint here): https://dg-encoder.scriptsnsenses.workers.dev/ So I built DG Encoder . A completely free , no-API-key service powered by Cloudflare Workers that lets developers store and retrieve text-based data through simple endpoints. ✨ What is DG Encoder? DG Encoder is a lightweight API that allows you to: Store any text value Receive a unique ID Retrieve the value later through an endpoint Restrict access to specific domains Edit stored entries Delete stored entries Use the service without API keys Use the service completely free 💸 Free Forever One of the main goals of DG Encoder is simplicity. There are: ✅ No API keys ✅ No signup requirements ✅ No subscriptions ✅ No paid plans ✅ No complicated setup Just open the website, encode your value, and start using it. 🔥 Why I Built It While building web applications, I noticed that many developers need a simple way to hide values from frontend code without setting up a full backend system. Common examples include: Discord webhooks Dynamic configuration values Service endpoints Internal URLs Integration strings DG Encoder provides a quick solution by storing those values behind randomly generated IDs. Your application only needs the generated ID instead of the original value. ⚡ Key Features Encode Anything Store any string and receive a unique identifier. { "id" : "abc123xyz" } Domain Restrictions Limit which websites can access a stored value. For example: example.com myapp.pages.dev Only approved domains can successfully use the decode endpoint. Edit Existing Entries Need to replace a webhook or endpoint? Update the stored value without generating a new ID. Delete Entries Remove data whenever it is no longer needed. No API Key Required De

Atlassian details the Forge billing platform built for usage-based pricing across its cloud ecosystem. It processes large-scale usage events with correct attribution, deduplication, and aggregation using a streaming pipeline, idempotent processing, and layered storage to enable accurate billing, near real-time visibility, and reliable reconciliation across distributed services. By Leela Kumili

From its opening minutes, Moves of the Diamond Hand is upfront about what it offers: You're going to have a lot of strange conversations, and you're going to roll a lot of dice. Get on board with this proposition, and the reward is one of the most creative roleplaying games I've seen in years, even […]

Car buyers love Android Auto. Automakers? Not so much.

You can't optimize what you don't measure. Every blog post about conversion optimization, A/B testing, or paid ads assumes you have reliable tracking in place. But most developers set up analytics as an afterthought — dropping a script on the page and calling it done. The result is data that's incomplete, untrustworthy, and ultimately useless for making decisions. This guide gives you a developer-first approach to conversion tracking. We'll cover event instrumentation, attribution setup, funnel visualization, and the specific tracking architecture you need to answer real business questions. No marketing jargon. No vague advice. Just the exact setup that turns your analytics from a vanity dashboard into a decision-making tool. The Tracking Mindset Before you write any code, understand what you're trying to learn. Tracking every possible event creates noise. Tracking the wrong events leads to wrong conclusions. Start with one question: "What are the 3-5 actions a user takes between discovering my product and paying me money?" Map these actions in order. That's your funnel. Every event you track should map directly to a step in that funnel. For a typical SaaS product, the funnel looks like this: Discovery: User visits your site from a traffic source Engagement: User reads content, explores features, or uses a tool Intent: User clicks "Sign Up" or "Start Trial" Conversion: User completes signup and activates Revenue: User upgrades to a paid plan If you track these five steps reliably, you can answer 90% of the marketing questions that matter: Which traffic source brings the most valuable users? Where do users drop off? What's my true cost per acquisition? Event Instrumentation: What to Track and How Events are the atomic unit of conversion tracking. An event is any action a user takes that you want to measure. Let's build your event taxonomy from the ground up. Foundational Events (Track These First) These four events are non-negotiable. Set them up before you do anythi

I used to think tests were a waste of time. "Ship fast, fix later" was my motto. Until I spent three painful weeks debugging a production issue that a simple test would have caught in 30 seconds. That was the day I became a believer. The Harsh Reality Most Solo Developers Ignore If you're a freelancer or indie hacker building real products for clients, here’s what happens without good tests: You make a "small change" and something unrelated breaks Clients find bugs you should have caught Refactoring becomes terrifying You lose sleep before every deployment Your reputation slowly takes hits A solid test suite changes all of that. What a Test Suite Actually Gives You Confidence to Move Fast You can refactor, add features, or upgrade dependencies without fear. Living Documentation Your tests explain how the system should behave — better than comments ever could. Early Bug Detection Catch issues before they reach the client or production. Better Architecture Writing testable code forces you to write cleaner, more modular code. Professional Credibility When clients or senior devs review your code, a good test suite immediately signals seriousness. The Test Suite Pyramid I Actually Use Unit Tests (70%) → Test individual functions and components Integration Tests (20%) → Test how different parts work together (API + DB) End-to-End Tests (10%) → Critical user flows (login → checkout → etc.) I don't aim for 100% coverage. I aim for high-value coverage — especially around business logic and critical paths. Final Thought Writing tests feels slow at first. But it compounds. Every month you have tests, you move faster and sleep better. The developers who ship reliable software consistently aren't necessarily the smartest — they're usually the ones who learned to respect testing. Have you built a strong test suite habit yet? Or are you still in the "I'll test it manually" phase? Drop your experience below. Let's talk.

In the world of cross-border e-commerce, malicious bot scraping leading to Meta/Google Pixel pollution is a nightmare for every seller. When your store starts gaining traction, these fake traffic sources can "poison" your ad model, causing your ROAS to plummet. To combat this, I’ve developed a robust "Backend Data Isolation" architecture. The Core Defense Strategy Stop triggering ad conversion events directly from the frontend. Instead, build a "firewall" at the backend to ensure that only verified, high-quality conversion data is sent to your ad platforms. Technical Implementation By implementing server-side logic in Python, we can filter out bot requests effectively: def process_pixel_event ( request ): # Filter out bot signatures (User-Agent, IP analysis) if is_bot_signature ( request . headers [ ' User-Agent ' ]): return None # Send only high-quality data to ad platforms if is_real_customer ( request . session ): trigger_pixel_event ( request ) By leveraging this logic, we feed "private, high-quality data" to the AI. This allows the algorithm to learn only from genuine customer behaviors, creating an "immortal pixel" moat around your store. Learn More For a deep dive into full-scale anti-scraping deployments and how to leverage automated translation techniques to scale traffic in blue-ocean markets, check out my full technical guide: 👉 Read the Full Implementation & Troubleshooting Guide Here

The new Siri AI is conversational, omnipresent, and actually helpful.

Feeling overwhelmed by the constant flood of new AI features, MCP servers, and agentic platforms? In a world full of tech noise, it's easy to get exhausted trying to keep up. I just watched an incredible video by Burke Holland where he strips away the hype and shares 10 highly practical, concrete strategies to make AI coding tools actually work for your daily workflow. If you want to stop overcomplicating your setup and start getting better production results, here is the ultimate breakdown. The 10 AI Coding Tips (TL;DR Summary) Huge shoutout and credit to Burke Holland for these insights: 1) Use Visual Studio Code to maximize your environment with powerful themes, extensions, and inline terminal chats. 2) Always turn on YOLO / "allow all" mode so your AI agent can execute commands seamlessly without breaking your flow with constant permission prompts. 3) Never run agents on your own machine , choosing instead to isolate them via remote SSH or dev containers so YOLO mode is completely safe. 4) Prototype and mock everything upfront to map out UI design languages and logic before implementing code. 5) Always plan and grill by leveraging interactive planning modes to answer critical edge-case questions before generating file. 6) Rubber duck your plans across different AI model families (like combining Claude and GPT) to cross-verify solutions and expose blind spots. 7) Utilize autopilot and sub-agents to delegate parallel tasks and route smaller, faster models where appropriate. 8) Use built-in browser tools to visually review live previews and directly prompt structural or stylistic adjustments. 9) Run iterative multi-model reviews on autopilot to catch hidden bugs and refine code quality until reaching a clear point of diminishing returns. 10) Learn from your session history using tools like Chronicle to analyze your prompting habits and continually optimize how you interact with the agent. 📚 Recommended Reading If you are looking to dive deeper into perfecting your

Researchers have demonstrated they can make coffee comparable to conventional espresso using ultrasonic waves. Because the process doesn’t need hot water, it consumes 75 percent less energy.

I can't remember the last time I got excited about a fan. Normally, I just buy whatever Vornado or Dreo model fits my budget, but that was before I started testing the battery-powered Standing Circulator Fan from SwitchBot. As the name indicates, the SwitchBot fan is a 3D circulator - a fancy way of saying […]

Authentication is broken at its foundation - not just inconvenient. Passwords are shared secrets: hand one to a server, and you have instantly doubled your attack surface. With over 5 billion passkeys now active globally and Google reporting a 99.9% lower account compromise rate compared to passwords, the industry has already moved. This guide covers how passkeys work cryptographically, how to implement them in TypeScript, and the pitfalls to avoid before going to production. Why Passwords Are Structurally Broken The core issue isn't that users pick weak passwords - it's that passwords require a shared secret stored on both sides. The Verizon 2025 DBIR found that 22% of all breaches started with stolen credentials, and 88% of web app attacks relied on them. In 2024, infostealer malware alone harvested 548 million passwords. Adding 2FA helps but doesn't fix the root problem: SMS codes are SIM-swap targets, and TOTP tokens can be phished in real time by proxy attackers who replay codes within their validity window. What Passkeys Actually Are A passkey is a credential built on public-key cryptography, standardized through the WebAuthn spec and FIDO2. When you register, your device generates a public-private key pair - the private key stays locked in hardware (Secure Enclave, StrongBox, or a hardware key), and the server only receives the public key. At login, the server sends a random challenge, your device signs it with the private key after biometric or PIN verification, and the server verifies the signature. No secret is ever transmitted. This eliminates credential stuffing, server-side breach exposure, and phishing - because passkeys are cryptographically bound to a specific origin domain. The Cryptography Worth Understanding The standard algorithm is ES256 - ECDSA with the P-256 curve and SHA-256. Each credential is tied to a specific relying party ID (your app's domain). A passkey created for yourapp.com cannot be used on yourapp-phishing.com because the origin i

Body: Hey everyone 👋 I've been building hermes-agent-skills — a production-grade skill collection for Hermes Agent that does three things no other skill pack does: 1. Self-Evolving Skills Skills aren't static YAML. The built-in EvolutionEngine tracks 5 health dimensions (usage frequency, success rate, user corrections, freshness, command validity), assigns a health score, and tells you which skills are rotting. Think of it as npm audit for your AI assistant's capabilities. 2. SOUL.md Persona Awareness Drop a SOUL.md in your Hermes config — naming conventions, comment density, architecture preferences, commit style — and every skill that touches code output adapts to it. hermes-skill soul generate bootstraps one in one command. The persona-aware-coding skill reads it at runtime so your agent writes code that actually looks like you wrote it. 3. CLI Toolchain hermes-skill create my-workflow # scaffold a standards-compliant SKILL.md hermes-skill validate skills/ # validate against the Agent Skills Standard hermes-skill list skills/ -f json # enumerate with health metadata hermes-skill soul generate # bootstrap a persona file What's in the box (v1.1.0): | Skill | Phase | Hermes-only Feature | |---|---|---| | requirement-analyzer | Define | Persistent memory across sessions | | spec-driven-dev | Spec | /skills chain forming workflows | | test-driven-dev | Build | delegate_task parallel test execution | | debugger-coordinator | Verify | browser + terminal + vision tri-tool | | code-quality-guardian | Review | patch auto-fix + /curator tracking | | cicd-orchestrator | Ship | cronjob scheduling + webhook triggers | | skill-curator | Evolve | Direct /curator integration | | persona-aware-coding | Identity | Native SOUL.md persona system | Why this is different: Most agent skill collections are portable but shallow — they can't use any platform's unique superpowers. These skills go deep on Hermes specifically: slash commands, delegate_task, persistent memory, vision+browser+t

If you're learning DevOps right now, there's a high chance you're experiencing at least one of these problems: Watching endless YouTube tutorials but forgetting everything after a week. Learning Docker, Kubernetes, AWS, Jenkins, Terraform separately without understanding how they fit together. Feeling overwhelmed by the massive DevOps roadmap. Jumping from one course to another without making real progress. Thinking you're learning fast when you're actually just consuming content. I know this because I made the same mistakes. When I first started learning DevOps, I thought mastering tools was the goal. I was wrong. The biggest challenge wasn't Docker, Kubernetes, AWS, or CI/CD. The real challenge was understanding why DevOps exists in the first place. Once I understood that, everything became easier. And two books helped me more than dozens of random tutorials. 🥇 Book #1: The Phoenix Project 👉 Buy Here If you're struggling to understand why companies use DevOps, start with this book. Unlike traditional technical books, The Phoenix Project teaches DevOps through a story. You'll follow an IT manager trying to save a failing company while dealing with: Constant production outages Deployment failures Team conflicts Slow software releases Business pressure As the story unfolds, you'll naturally learn: ✅ DevOps principles ✅ Bottlenecks and constraints ✅ CI/CD concepts ✅ Automation thinking ✅ Why collaboration matters The best part? You don't need years of experience to understand it. Even if you're a student learning AWS, Docker, Kubernetes, and Linux, this book makes complex DevOps concepts feel simple. Why I Recommend It Most beginners try to learn tools before learning principles. This book fixes that mistake. 🥈 Book #2: The DevOps Handbook 👉 Buy Here Once you understand the mindset behind DevOps, it's time to learn the practical side. That's where The DevOps Handbook comes in. Think of it as the blueprint used by high-performing engineering teams. Inside you'll learn:

Your password bar goes from "weak" to "strong" when you add characters. Have you ever wondered how React 'remembers' your inputs? 'State' is your answer. A state remembers what input you added. Assume you are typing your name "John", initial state is the blank slate (starting value, like empty input, counter at zero, or an empty whiteboard) in the input bar, whenever you add a new letter, a function named 'setState' is called to change the state from "" (empty input bar) to "J", then again to "Jo", again to "Joh", etc... And following the setState, React automatically re-renders the UI. Think of re-rendering as erasing everything and re-writing the UI with the new state. Initial state was "", then setState updates it from "" to "J". Following that, React automatically erases the first UI and then it will build a new UI with the new state. Why not just use a variable? You might be thinking, "Why don't just use variables and change them whenever you want it?", and you might do that, but the value only changes in your codebase, but the UI will still show the first value. (and that defeated the purpose) What is [state, setState] concept? const [state, setState] = useState('placeholder') is the basic syntax. useState provides an array of ['current-state', 'function to change state']. It is destructured to the two values (state = 'current-state' and setState = 'function to change state'). When you enter an input, the function is called and the 'current-state' will be updated to the 'new-state'. How to use it To use useState follow these two simple steps: Import useState from 'react' import { useState } from 'react'; Declare it (for example to input age): const [age, setAge] = useState(20); where, 'age' is current state. 'setAge' is the function that will create the new state. 20 is the placeholder. Now try it yourself! Open your React project and add a counter using useState. Watch the UI update every time you click.

The Quest Begins (The "Why") Picture this: I’m hunched over my laptop at 2 a.m., surrounded by empty coffee mugs, trying to get a simple Node.js API to run on a friend’s Windows machine. I’ve got the code, I’ve got the dependencies, but every time I hit npm start on his box I’m greeted with “Cannot find module ‘left-pad’” (yeah, I know, that’s a meme, but it felt real). It was like trying to cast a spell in Harry Potter while forgetting the wand‑movement — nothing happened, and I felt like a Muggle in a wizard’s duel. That night I realized the real dragon wasn’t the buggy code; it was the “it works on my machine” curse. I needed a way to package everything — the runtime, the libraries, the environment variables — into a single, portable chest that any teammate (or future‑me) could open and instantly get the same result. Enter Docker, the holy grail of reproducibility. If The Matrix taught us anything, it’s that once you see the underlying code, you can bend reality. Docker lets you see the container code and then bend your deployment reality to your will. The Revelation (The Insight) The big “aha!” came when I stopped thinking of Docker as just another VM and started seeing it as a lightweight, immutable snapshot of my app’s filesystem. Unlike a full VM that boots an entire OS, a Docker container shares the host kernel but isolates everything else — think of it as the Inception dream‑within‑a‑dream, but each layer is a read‑only snapshot you can stack like LEGO bricks. Here’s the secret sauce in three lines: Dockerfile – a recipe that tells Docker how to build the image. Image – the built, immutable artifact (the “DVD” of your app). Container – a running instance of that image (the “movie playing” from the DVD). When you docker build , Docker reads the Dockerfile line‑by‑line, creates intermediate layers, caches them, and finally spits out an image you can tag, push to a registry, and run anywhere. No more “it works on my machine” because the machine inside the cont

I run Convertify , a free image converter built on Rust and libvips. Last week I decided to stop guessing about format performance and actually measure it. I took 50 real images (26 PNGs, 24 iPhone HEIC photos), ran 17 conversions through the production pipeline, and recorded every file size and encode time. Some results confirmed what everyone says. Others did not. The three results that surprised me 1. Converting HEIC to JPG makes files 14% bigger , not smaller. This one hurt. "Convert iPhone photos to JPG" is probably the most common advice on the internet. But HEIC wraps the HEVC codec, which compresses roughly 2x better than JPEG. Going from a better codec to a worse one means the file grows. Every time. If you actually want smaller iPhone photos: HEIC to WebP saves 43%, HEIC to AVIF saves 57%. 2. AVIF encodes 7x slower than WebP for 10% more compression. AVIF Q63: 55 KB, 1.30s per image. WebP Q80: 61 KB, 0.19s per image. That is a 10% size difference for a 7x speed penalty. For a single hero image, nobody cares. For a batch pipeline processing thousands of product photos, that is the difference between 3 minutes and 21 minutes. 3. PNG at 600 DPI is smaller than PNG at 300 DPI when rasterizing PDFs. This was the weirdest one. I was benchmarking PDF-to-image and noticed PNG output shrank from 2,221 KB at 300 DPI to 1,660 KB at 600 DPI. I spent an hour convinced I had a bug. Turns out it is a real property of PNG encoding. Higher DPI renders smoother gradients between adjacent pixels, and PNG's prediction filters (Paeth, sub, up) compress smooth gradients dramatically better than the sharp edges you get at lower resolutions. Not a bug. Just PNG being PNG. The quick reference table Conversion Size change Speed JPG to WebP Q80 -64% 0.19s JPG to AVIF Q63 -68% 1.30s PNG to WebP Q80 -92% 0.21s PNG to JPG Q85 -86% 0.07s HEIC to JPG Q85 +14% 1.90s HEIC to WebP Q80 -43% 5.64s HEIC to AVIF Q63 -57% 14.52s WebP to JPG Q85 +60% 0.09s AVIF to JPG Q85 +80% 0.15s What I actual

Part 2 of a beginner-friendly series on learning Python from scratch. In Part 1 , we installed Python, wrote our first program, and learned the syntax rules that hold everything together. Now it's time to start storing and working with information — which means variables and data types. What is a Variable? A variable is a name that points to a value stored in memory. Think of it as a labeled container you can put something into, and refer back to later by name. name = " Ramesh " age = 25 Unlike many other languages, Python doesn't need you to declare a variable's type ahead of time. You just assign a value with = , and Python figures out the type on its own. This is called dynamic typing . x = 5 # x is an integer x = " hello " # now x is a string — totally legal in Python This flexibility is convenient, but it also means you need to be a little more careful — Python won't stop you from changing a variable's type halfway through your program, even if that wasn't your intention. Variable Naming Rules Python is strict about how variable names can look: Must start with a letter or an underscore ( _ ) — never a number. Can only contain letters, numbers, and underscores. Cannot be a Python keyword ( class , for , if , etc.). Are case-sensitive — age , Age , and AGE are three different variables. age = 25 # valid _age = 25 # valid age2 = 25 # valid 2 age = 25 # invalid — cannot start with a number my - age = 25 # invalid — hyphens aren't allowed Naming conventions Python's style guide (PEP 8) recommends snake_case for variable names — lowercase words separated by underscores: first_name = " Ramesh " total_score = 95 Assigning Multiple Variables Python lets you assign several variables in a single line, which keeps code compact and readable. # One value to multiple variables x = y = z = 10 # Multiple values to multiple variables name , age , city = " Ramesh " , 25 , " Chennai " Data Types in Python Every value in Python belongs to a data type, which determines what kind of

The next attempt was the standard Maps URL: window . open ( `https://maps.google.com/maps?daddr= ${ lat } , ${ lng } ` , ' _blank ' ); This opens Maps, but in the browser — not the app. And it shows the route preview, not turn-by-turn navigation. What worked: Android Intent URLs Android supports a special URL scheme that tells Chrome to launch a native app directly: window . location . href = `intent://navigation/now?ll= ${ lat } , ${ lng } &title=Next+stop#Intent;scheme=google.navigation;package=com.google.android.apps.maps;end` ; Breaking it down: intent:// — tells Chrome this is an Android intent navigation/now?ll=${lat},${lng} — opens Maps in navigation mode, starting immediately #Intent;scheme=google.navigation — the URI scheme to use package=com.google.android.apps.maps — the target app package end — closes the intent syntax This opens the Google Maps app directly and starts turn-by-turn navigation automatically — no extra taps needed. It also works with Android Auto. The full function export function openNavigation ( destination : { lat : number ; lng : number }): void { window . location . href = `intent://navigation/now?ll= ${ destination . lat } , ${ destination . lng } &title=Next+stop#Intent;scheme=google.navigation;package=com.google.android.apps.maps;end` ; } Call it on any user gesture (tap, click) and it works without being blocked by the browser. The app The full PWA is open source if you want to see the context: 🔗 GitHub repo 🌐 Live app Built with React + TypeScript + Vite + Dexie.js + @vis .gl/react-google-maps. If you're building a PWA that needs to hand off to Google Maps navigation on Android, this intent URL is the cleanest solution I found. Hope it saves you the hour I spent figuring it out.

This is a submission for the June Solstice Game Jam ( https://dev.to/challenges/june-game-jam-2026-06-03 ) What I Built I built Solstice Assassin, a tactical stealth-action game set inside a collapsing digital mainframe. You play as Alex, a self-aware digital anomaly trapped inside the Solstice Grid, a secure virtual system originally created by Alan Turing. Alex awakens with almost no memory except one critical piece of information: «CREATOR: ALAN TURING» The catch? Today is the Summer Solstice, the longest day of the year, and at midnight the system will execute a complete purge of all dynamic data. Alex has one final day to recover lost memories, outsmart the system's security forces, and find a way to survive. Gameplay combines tactical movement, stealth, procedural level generation, enemy AI, and resource management. Players infiltrate security sectors, collect awareness data, avoid or eliminate hostile "Cleaners", and manage powerful abilities such as Dash, Cloak, Radar, and Time Warp. The Solstice theme isn't just part of the story—it directly affects gameplay. Throughout each mission, the system progresses through different Solar Phases: 🌅 Golden Dawn ☀️ High Noon 🌇 Crimson Sunset 🌑 Eclipse Each phase changes visibility, stealth effectiveness, enemy behavior, and the overall tactical landscape. High Noon makes players highly exposed, while Crimson Sunset rewards stealth and careful planning. By the time Eclipse arrives, the entire system begins breaking down. My goal was to create a game where the passing of the longest day isn't just a background theme but something the player constantly feels through the mechanics themselves. Video Demo https://youtu.be/48RM1iTZjOg?si=JYz86wVzNMjeZmmw In the video I demonstrate: Tactical movement and infiltration Dynamic Solar Phase transitions Enemy AI behavior and pathfinding Awareness recovery and progression systems Alex's abilities AI-generated mission briefings and voice interactions Procedural level generation End-o