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AI 资讯

Presentation: Automating the Web With MCP: Infra That Doesn’t Break

Paul Klein discusses the distributed systems challenges of scaling cloud-hosted browser infra for AI agents. He explains how to manage bursty, stateful multi-tenancy and secure Chromium environments against remote code execution using Firecracker. He also shares how to leverage the Model Context Protocol (MCP) to turn complex websites into accessible agentic tools. By Paul Klein

2026-06-16 原文 →
AI 资讯

Schlage’s UWB-enabled smart lock launches this month

It's been more than a year since Schlage announced its first smart lock to support ultra wideband technology (UWB), but now it's finally almost available to purchase. Starting June 29th, the Schlage Sense Pro deadbolt lock will be available for $399 in the US, allowing customers to unlock their doors by simply approaching them with […]

2026-06-16 原文 →
AI 资讯

How I Built Production-Grade AI Systems While Still a Student

🚀 Hello, DEV Community! I'm Nader Al Shawki , a final-year AI Engineering student at Al-Razi University, Yemen. This is my first post here, and I'm excited to start sharing my journey with this amazing community. 🎯 Who Am I? I'm passionate about building production-grade AI systems that solve real-world problems. My main areas of focus are: 🖼️ Computer Vision & Deep Learning 🤖 ML Model Deployment (Docker, FastAPI, REST APIs) 🧠 LLMs, RAG, and AI Agents (currently learning) 📊 Data Visualization & Analytics (Power BI) 💡 What I've Built So Far 1. 🍅 Tomato Leaf Disease Detection Platform Tech: YOLOv8, PyTorch, FastAPI, Docker What it does: Detects tomato leaf diseases from images with real-time inference. Containerized with Docker for easy deployment. 2. 🫁 Pneumonia Detection System Tech: PyTorch, CNN Architecture, Medical Imaging What it does: A deep learning model that detects pneumonia from chest X-ray images. 3. 📊 Sales Profit Analysis Dashboard Tech: Power BI, DAX, Data Analysis What it does: Interactive dashboard for tracking sales KPIs. 4. 😀 Face Detection & Emotion Recognition Tech: OpenCV, Deep Learning What it does: Real-time face detection, age estimation, emotion recognition, and gender classification. 5. 🍽️ Restaurant Website Tech: HTML5, CSS3, JavaScript What it does: Fully responsive restaurant website with interactive UI. 🌱 What I'm Currently Learning LLMs (Large Language Models) RAG (Retrieval-Augmented Generation) LangChain & AI Agents Workflow automation with n8n 🔗 Let's Connect 🐙 GitHub: Naderalshawki 💼 LinkedIn: in/nader-al-shawky 📫 Email: naderalshawki@gmail.com Thanks for reading! I'll be posting regularly about AI projects, tutorials, and lessons learned. Stay tuned! 🚀

2026-06-16 原文 →
AI 资讯

Luck == Opportunity Meets Preparation

There's a line usually pinned on the Roman philosopher Seneca: luck is what happens when preparation meets opportunity. People put it all over social media and like most things on social media, it gets repeated so often that it stops meaning anything. So let me try to make it mean something again, with a math equation and a football match that happened recently at the latest FIFA World Cup 2026. The equation nobody writes down We talk about luck like it's a single mysterious force, either you have it or you don't. But it's not one thing. It's two things multiplied together: Luck = Preparation × Opportunities Look at what that multiplication does. If your preparation is zero, it doesn't matter how many opportunities show up, zero times anything is still zero. And if you're the most prepared person alive but you never put yourself in front of a single opportunity, same result. Zero. The lucky people aren't the ones who got more luck handed to them. They're the ones who kept both numbers high. They got good and they kept showing up to the table where things happen. Hold that thought. Let's go to Texas. Japan, the Netherlands, and the 88th minute On June 14th, 2026, Japan played the Netherlands in their World Cup group opener in Arlington, Texas. On paper it was a mismatch in the most literal, physical sense. The Netherlands are tall . Van Dijk, Van de Ven, the whole spine of that team is built like a row of wardrobes. Japan are one of the shorter sides in world football, quick, technical, but not the people you'd bet on to win a header. If you were designing a contest specifically to humiliate the Japanese, you'd make it about jumping. And for most of the night, the script ran exactly as the bodies predicted. The Dutch dominated the run of play, around 60% possession, more passes, more touches in the box, the better expected goals. Van Dijk, a defender, rose for a cross and headed the Netherlands ahead. Later Summerville restored their lead. The Oranje even won the aer

2026-06-16 原文 →
AI 资讯

Same Prompt, Four AI Tools, One Cricket Banner: ChatGPT Won the Image, Grok Won the Video, and Claude Built a Website Again

TL;DR — A few weeks ago I tested four AI tools on a build job: a website for my son's cricket academy. This time the job had nothing to do with code. The coach just wanted a banner he could post. Same four tools, totally different result. ChatGPT made the best image, Grok made the best video, Gemini wouldn't make anything, and Claude tried to solve a graphics problem by writing HTML. If you read the last post , you've met my son's cricket coach. He runs MMCA — Maverick Master's Cricket Academy. Started in 2020, based in Bengaluru, genuinely good with the kids. The website is live now and parents have started messaging him on WhatsApp. So last weekend he came back with the next thing he needed, which is the thing every small academy actually runs on: "Can you make me a weekend batch banner? Something I can post in the parent groups." Now, this is a completely different job from the last one. That first experiment was design and development — agents writing real code, running tests, deploying to Cloudflare. This one is just graphics. No repo, no deploy, nobody reviewing a pull request. Just: here's my logo, here's a sample I like, make me something I'd be happy to send out. So I figured I'd run the same four tools again and see what happened. Same brief, same logo, everything on the default model with no special settings : ChatGPT, Claude, Gemini, Grok. Here's roughly what I typed, the way a normal client would brief you: Similar to this banner, make one for MMCA Academy (since 2020, logo attached). Weekend batch Sat 4:30—7, Sun 7—9:30pm. Add a small phrase like the sample. Be creative, keep it simple, but don't copy the sample exactly. The whole test really came down to one instruction: be creative, but don't copy. Whatever each tool did with that told me everything. Round 1: the static banner ChatGPT got it on the first go. "WEEKEND BATCH. TRAIN. PLAY. GROW." Logo top-left, the "Since 2020" bit kept, timings in clean little cards, an enrol number, three badges acros

2026-06-16 原文 →
AI 资讯

Apple’s smart home camera service is starting to impress me

Apple's HomeKit Secure Video service is getting in on the Apple Intelligence party to bring more descriptive alerts from your connected cameras and let you search footage using natural language. The Apple Home app is also getting better notifications powered by AI and is finally adding support for energy reporting. These improvements were announced at […]

2026-06-16 原文 →
AI 资讯

Apple’s weird anti-nausea dots cured my car sickness

I'll just work from the car, I thought. But after a few minutes of staring at my screen on quick mountain switchbacks I could feel the first signs of cold, coagulated nausea bubbling up from that sweaty place in my gut. I looked to the horizon for relief, but nothing helped… until I remembered Apple's […]

2026-06-16 原文 →
开发者

Building a Lead Generation Platform for Businesses

We Built Korexbase: A Lead Generation Platform for Finding Business Leads by City and Niche Building software is exciting. Building software that solves a real problem is even better. Over the past few months, we've been working on Korexbase , a lead generation platform designed to help businesses discover targeted leads faster. The Problem Many agencies, sales teams, freelancers, and startups spend hours manually searching for potential customers. The process usually looks something like this: Search for businesses online Collect contact information Copy everything into spreadsheets Repeat the process every day It's slow, repetitive, and difficult to scale. We wanted to simplify that workflow. The Idea Korexbase allows users to search for business leads by: City Industry Business category Instead of manually collecting data, users can generate leads and manage them through a clean dashboard. The goal isn't to replace sales. The goal is to help businesses spend less time searching and more time closing deals. Building the Platform A major focus during development was creating a dashboard that feels simple and easy to navigate. Some areas we focused heavily on included: Responsive layouts User-friendly navigation Clear data presentation Fast loading interfaces Consistent design patterns Challenges Like most projects, we faced a number of challenges: Designing for Simplicity One of the biggest lessons was that adding more features doesn't automatically create a better product. We spent a lot of time simplifying interfaces and removing unnecessary complexity. Creating a Better Dashboard Experience Presenting lead generation data in a way that is useful without overwhelming users required multiple design iterations. We focused on: Better spacing Better visual hierarchy Cleaner cards and tables Improved responsiveness Product Positioning An interesting challenge was refining the product's positioning. As development progressed, we learned more about what users actually w

2026-06-16 原文 →
AI 资讯

Claude Desktop vs Antigravity 2026: Why I Moved Back

Originally published on rikuq.com . Republished here for Dev.to's readers. I dropped my $100/month Claude Max subscription and migrated entirely back to Antigravity. If you want the verdict upfront: Claude Desktop is still the best tool for beginners who need the AI to guess their intent from clumsy prompts. But if you have solid documentation discipline and cost efficiency is a serious factor for your SaaS, Antigravity is now the clear winner. I'm a Chartered Accountant by trade with zero formal coding experience. I’ve shipped three production AI SaaS— Prism , Citare , and BatchWise —relying entirely on AI tools. I started with VSCode, moved to Antigravity (when it was just an IDE), and eventually landed on the Claude Desktop App. Claude was incredible; it operated in the background, handled my stack, and I didn't need to know what was happening under the hood. But the bills started stacking up. When my Claude usage consistently hit $100 a month, efficiency became a priority. I fired up the new version of Antigravity and found the recent updates had completely transformed it. It is no longer just an IDE—it is a full agentic desktop experience that mirrors what made Claude so good. TL;DR — The 2026 Reality Feature Claude Desktop App Antigravity (New Update) Best for Beginners, unlimited budgets, "pure performance" Experienced AI directors, cost-conscious solo founders Pricing $100+/mo (Claude Max) $20/mo (Gemini Advanced) Agentic Workflow Exceptional. The benchmark. Identical. Background execution, zero friction. Context Handling Better at anticipating intent from messy prompts Huge total memory, but requires tighter prompting MCP Support Native Native (handles them just as well) Verdict Keep it if cost doesn't matter Switch to it if efficiency is the goal The Catalyst for Switching My path to Antigravity wasn't a calculated feature comparison. It was pure economics combined with a pleasant surprise. I had previously dropped Antigravity when it was just an IDE. When

2026-06-16 原文 →