Android Headlines claims to have the specs and price for the entire Pixel 11 lineup. What the site shared basically lines up with everything else that we've heard in the lead-up to the August 12th event. The Pixel 11 is expected to get a $100 price hike, starting at $899, but will come with 256GB […]

There are exactly three sensible ways to get an SVG icon into a React codebase: paste it inline as a component, import the file through a build transform like SVGR, or reference it from a sprite. Most projects need only the first. This guide walks through the inline approach with Next.js and Tailwind specifics, and points to the deeper guides where a topic deserves its own article. Option 1: an inline JSX component Take a real icon from the catalog, convert the SVG attributes to JSX casing, and you have a dependency-free component. This is Lucide's search icon, exactly as it ships in the Lucide set , wrapped for React: export function SearchIcon ( props ) { return ( < svg xmlns = "http://www.w3.org/2000/svg" viewBox = "0 0 24 24" fill = "none" stroke = "currentColor" strokeLinecap = "round" strokeLinejoin = "round" strokeWidth = { 2 } aria-hidden = "true" { ... props } > < path d = "m21 21l-4.34-4.34" /> < circle cx = "11" cy = "11" r = "8" /> </ svg > ); } The JSX gotchas are all attribute casing: stroke-width becomes strokeWidth , stroke-linecap becomes strokeLinecap , and class becomes className . Icon pages on this site do the conversion for you: every icon offers React, Vue, Svelte, and Solid snippets next to the raw SVG, so you can copy the JSX form directly. If you have a folder of SVG files instead, the free SVG to component converter batch-converts them in the browser. Prefer importing .svg files over pasting? That is the SVGR route, covered step by step in our React with Vite and SVGR guide . Next.js: server components by default An icon component like the one above has no state, no effects, and no event handlers, which makes it a perfect React Server Component. In the Next.js App Router it renders to static markup on the server and adds nothing to the client bundle: import { SearchIcon } from " @/components/icons " ; export default function DocsHeader () { return ( < label className = "flex items-center gap-2" > < SearchIcon className = "h-5 w-5 text-zinc

“For example, in the University of Texas experiments, a participant listened to the phrase, “I didn’t know whether to scream, cry or run away. Instead, I said, ‘Leave me alone!’”. The decoder translated this brain activity as, “Started to scream and cry, and then she just said, ‘I told you to leave me alone.’”.” submitted by /u/Darkengine53 [link] [留言]

This is a submission for Frontend Challenge - Comfort Food Edition, Perfect Landing * What I Built: * I built Ember & Spice which is an interactive landing page celebrating Tandoori Paneer Tikka, one of North India's most iconic comfort foods. The site is built for a fictional restaurant of the same name and brings the dish to life through immersive visuals and interactive features. * The page includes: * A hero section with an aesthetic AI-generated tandoori video A sizzle effect — click the Sizzle button and sparks fly across the image An interactive skewer builder where you stack paneer, peppers, and onions then grill them A spice dial slider that visually changes the marinade heat from Mild to Fiery A CSS-art tandoor oven that roasts your built skewer An ingredient tasting plate — click cards to add items A recipe checklist with a live progress bar A reservation form with client-side validation Fully responsive, mobile-first design with scroll-reveal animations Demo: ** Live site* : https://tandoori-paneer.vercel.app/ **Github *: https://github.com/jogadiyadipak28-art/tandoori-paneer * Journey: * I chose Tandoori Paneer Tikka because it's the kind of dish that carries memory (PS: It's my favorite dish) the smell of charcoal, the bright orange marinade, skewers shared at family gatherings. I wanted the page to feel as warm and alive as the dish itself. The most fun part was building the interactive Kitchen Lab, the skewer builder, spice slider, and tandoor oven are all pure vanilla JS and CSS, no libraries. Getting the tandoor CSS art to glow and the skewer pieces to animate onto the rod was deeply satisfying. I'm particularly proud of the sizzle effect, clicking the button sends 16 spark particles flying across the hero image and story photo, with a brief brightness flash. It's a small touch but it makes the page feel reactive and alive. What I learned: How powerful IntersectionObserver is for scroll-reveal without any libraries. CSS aspect-ratio for keeping the

This is a submission for Frontend Challenge - Comfort Food Edition, Perfect Landing What I Built The Comfort Atlas is a spinning 3D globe of comfort food from ~100 countries. Virtually travel the globe and have a taste of the comfort foods from 100~ countries. Moussaka in Greece, Jollof Rice in Nigeria, Pho in Vietnam. There is also a "featured dish of the day" that rotates deterministically so it's the same for everyone visiting that day. And the fun feature: visitors can type in their own comfort dish and generate a downloadable, passport-stamp-style card in one of three color styles. Demo https://comfort-atlas.netlify.app/ Journey I started with a flat SVG world map, clickable countries, keyboard support, a hover tooltip on the map, all built on real elements so accessibility came for free. It worked fine, but it looked very meh. So i decided to try something i have never done before. Make a globe! I used cobe which promised a 3D globe out of the box. First attempt rendered absolutely nothing but floating dots. 😂 With a lot of the help of my friend claude, we found out that their docs are outdated, and there is not a createGlobe() draws exactly one synchronous frame and expects you to drive a requestAnimationFrame loop calling .update() yourself. Two things on the globe I'm especially proud of, because neither had any library support: a hover tooltip that tracks a marker in 3D space, and a fading "trail" of great-circle arcs between the countries you've visited. Both came down to translating the projection math out of a minified bundle into something readable, then reimplementing it myself. What I would do next: dark mode. What I learned: a lot about accessibility in 3D/canvas, which is so much more difficult than the 2d one, one check for a11y is never enough. Maps are hard, and getting something to track a moving 3D object from regular DOM is even harder. Licensed under MIT Fun fact: I don't like Moussaka, even though i am greek, my comfort food is Pizza. xD

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Every automated system receives a particular shape of the world. That shape is expressed through records, documents, events, exceptions, and missing values. If the designers have not identified those forms—and the ways they can become malformed—the machine inherits their ignorance and reproduces it at scale. The question is not simply whether the AI failed. The useful question is whether the human-built system knew what success meant, knew the shape of its data, and knew how to recognize when it was wrong. Start with the shape of the data Before selecting a model, draw the workflow as a sequence of data transformations. What enters each stage? In what form and from what source? Which values are valid, absent, duplicated, stale, delayed, or contradictory? How will each violation be detected? What must the workflow do next? Each data shape needs a corresponding failure model. An unknown here is not merely uncertainty for the machine; it is a measurement failure in the organization. The remedy is to collect the missing data or explicitly design for its absence. Otherwise, the system is being asked to operate in a world its designers have not described. Stabilize the deliverable A system cannot be stabilized around a target that continues to move. The deliverable must be more than an aspiration written in a prompt. It should be expressed as observable conditions and anchored to a representative corpus: examples that are acceptable; examples that are unacceptable; examples that are genuinely ambiguous. Human reviewers should first demonstrate that they can apply those distinctions consistently. If they cannot agree on what success looks like, the model is not being measured against a specification. It is being measured against human disagreement disguised as one. The model is not the system Only then does it become meaningful to place an AI model inside the workflow. The model is one transformation among many: Input → validation → retrieval → normalization → model infere

submitted by /u/deepCelibateValue [link] [留言]

😤 The Problem That Drives Everyone Crazy Ever tried building a Telegram Mini App? Write your code. Spin up ngrok (and pray it doesn't crash). Go to @BotFather, paste the tunnel URL. Grab your phone, open the bot, type console.log() — and pray again. Repeat for every theme, platform, and user type you need to test. It's 2015, folks. And there's still no official emulator. "The main difficulty is the inability to run a project as easily as in a browser via localhost — and the absence of a developer console." — Habr, March 2025 💡 Introducing: TMA DevKit A local emulator and bridge inspector for Telegram Mini Apps. Think Redux DevTools, but for window.Telegram.WebApp. In one sentence: paste your Mini App URL into the panel, and it runs inside an iframe with a full emulation of the Telegram client — no phone, no ngrok, no BotFather. ✨ What DevKit v2 Can Do (and Why It's Awesome) 🧠 MCP Server for AI-Powered Debugging — Brand New! Connect any AI assistant (Claude, GPT, local models) via the Model Context Protocol. Ask questions about your app's state, event flow, or initData validation — and get instant debugging suggestions. 🔧 A Real Mock, Not a Stub Full window.Telegram.WebApp API surface (all methods, properties, events). Cryptographically valid initData generation with HMAC-SHA-256 signature using your bot token. Backend validation passes as in production. Compatible with @telegram-apps/sdk v3 out of the box. ⚡ 5 One‑Click Quick Scenarios Scenario Description iOS Premium iPhone user with Premium subscription Android Free Regular Android user New User With referral parameter Group Launch Emulates opening from a group chat Desktop Wide viewport on computer Switch contexts in seconds — no manual input. 📊 Bridge Event Inspector All web_app_* calls displayed in real time. Group by type, filter, pause, export logs as .txt. emit console to fire client → app events (theme_changed, main_button_pressed, etc.). ☁️ CloudStorage Editor Visual key‑value editor. No more guessing what

I spent the last couple of months building Reclaim — an AI job-search agent for engineers, done solo, taking up nights and weekends. It reads your résumé, scores it honestly, and matches you against real open roles. It's live at reclaim.careers (free scan, no signup). This isn't a launch post — it's a breakdown of the stack and, more usefully, the things that broke. Here's how it's built. The stack Frontend — Next.js on Vercel. App Router, server components where it made sense. Vercel for hosting because the deploy-on-push loop is frictionless and I was optimizing for solo velocity, not infra control. Backend — FastAPI on Render. I split the Python backend out rather than doing everything in Next API routes, because the heavy lifting (résumé parsing, the matching pipeline, scraping) is Python-native and I wanted it isolated from the frontend's request lifecycle. Database — Supabase + Prisma. Postgres under the hood. Prisma for the schema and type-safe queries; Supabase for the managed Postgres and some auth-adjacent data. Auth — Clerk. Handles sign-up, sessions, the whole identity layer. More on Clerk below, because it's where I lost the most hours. Payments — Stripe. Live mode, subscription tiers with a trial. Lookup keys drive tier resolution in the webhook so pricing changes don't require code changes. The actual "AI" — Gemini. This is the interesting part, so it gets its own section. Gemini does the real work The thing I care about most: the AI isn't a chatbot bolted on the side. Gemini makes the actual product decisions. Résumé reading: parse the PDF, extract real structure, and score it — not against keyword density, but against whether the claims are substantiated. The whole premise is honesty: most AI résumé tools keyword-stuff to beat the ATS, which backfires the second you're in an interview and can't back up your own résumé. Reclaim does the opposite — it flags where you're genuinely strong and where you're stretching. Matching: scores the résumé against

Yelp has confirmed a licensing agreement with OpenAI that will extend Yelp content into AI platforms, including the OpenAI ecosystem powering ChatGPT. The deal positions Yelp’s reviews, ratings, photos and business information within a growing AI-driven local discovery experience, while opening a potential path for users to request quotes from local service providers through ChatGPT. The agreement is more consequential than a new search result format. Yelp is expanding its data-licensing strategy beyond conventional search surfaces, while ChatGPT gains access to a major source of local business content. For people asking an AI assistant where to eat, which contractor to contact or how a nearby business is rated, the quality, freshness and governance of the underlying data will matter as much as the answer itself. What the Yelp and OpenAI agreement covers In its February 2026 earnings and shareholder release , Yelp announced an agreement with OpenAI and described it as part of its AI transformation and strategy to license content for local discovery across AI ecosystems. That is the confirmed foundation of the development. Axios has reported the practical user-facing direction: ChatGPT will surface Yelp reviews, ratings, photos and other business details in responses to local queries. Yelp has also signaled that its Request a Quote capability could be integrated into ChatGPT in the near term, enabling users to initiate an inquiry with a service provider from the AI interface. Capability What the research supports Status Yelp content in ChatGPT Reviews, ratings, photos and other business details are expected to surface for local queries. Reported user-facing outcome of the confirmed licensing agreement Request a Quote in ChatGPT Users may be able to initiate quote requests with local service providers through the AI interface. Signaled for a future rollout Data timing and interface design Reporting describes real-time business data, but exact latency, update frequency

Hi, sorry if this is a repeated question on this subreddit but I want to know what is the monthly cheapest reasonable AI setup for myself. Basically im a "full stack developer" yea its lost its meaning but anyways I have like 5 projects with a company which is react laravel based (each in their own project folder thus i use file path to call them). Im at the stage where its bug fixing or sometimes new integrations with the already linked 5 apps. My current setup is the $20 per month cursor plan. I used infinite agent + composer 2.5 to do 8hrs of work per day. However, i find that before the month ends im usually out of tokens. What do u guys recommend is the cheapest way i can manage? Similarly i do some freelancing too that has next & node.js website building from scratch (around 70hrs per month). What do u recommend would get me with quicker work done but within this price. What do u think i should setup to either continue with the same flow but more tokens i guess? Im hearing about kimi. Would that be better and easier to do the tasks which r pretty straight forward? submitted by /u/Da_BrownNoob [link] [留言]

When you first install WordPress, it is easy to think that every popular plugin will improve your website. After all, the WordPress plugin directory contains tens of thousands of plugins, each promising better SEO, stronger security, faster performance, or beautiful design. That is exactly where many beginners make their first mistake. A new website does not need 30, 40, or 50 plugins. Every plugin you install adds more code that must be maintained, updated, and secured. While the number of plugins alone does not determine performance, unnecessary or poorly coded plugins increase the chances of conflicts, slowdowns, and security issues. Security experts also continue to report that plugins account for the overwhelming majority of WordPress vulnerabilities. The better approach is simple. Install only the plugins that solve an essential problem. Choose one high quality plugin for each task, avoid duplicates, and ignore everything else until you actually need it. Here are the only five to six plugins that most brand new WordPress websites need. The Minimalist Plugin Rule Before installing anything, remember this simple rule: One plugin, one job. If one plugin already handles SEO, you do not need another SEO plugin. If one caching plugin is active, never install a second one. If your hosting company already performs automatic backups, you may not need a backup plugin running every day. Keeping your plugin list small makes your website easier to manage, faster to update, and less likely to develop compatibility problems. An SEO Plugin Recommended: Rank Math SEO or Yoast SEO Every website needs an SEO plugin. Without one, you miss important features such as: XML sitemaps Meta titles and descriptions Search engine indexing controls Schema markup Social sharing previews For beginners, Rank Math's free version includes a generous feature set, while Yoast SEO remains one of the most established and beginner friendly alternatives. Either option works well. The important rule i