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Vane (Perplexica 2.0) Quickstart With Ollama and llama.cpp

Vane is one of the more pragmatic entries in the "AI search with citations" space: a self-hosted answering engine that mixes live web retrieval with local or cloud LLMs, while keeping the whole stack under your control. The project was originally known as Perplexica, Because the useful part of the stack is not only the UI but also where inference and data live, this comparison of LLM hosting in 2026 pulls local, self-hosted, and cloud setups together so you can place Vane next to other runtimes and deployment choices. This post focuses on the parts technical readers actually care about: how the system works, a minimal Docker quickstart, and how to run it with local inference via Ollama and llama.cpp (directly or through LM Studio). Along the way, each FAQ topic is answered in-context, not parked at the bottom. At a high level, Vane is a Next.js application that combines a chat UI with search and citations. The core architectural pieces are also exactly what you would expect from a m...

Streamlining Browser Extension Development: Overcoming Repetitive Tasks and State Management Complexities

Introduction: The Browser Extension Development Dilemma Building browser extensions is a lot like assembling a puzzle in a dark room. You know the pieces are there, but the process is riddled with repetitive tasks and hidden complexities that slow you down. Over the past five years, I’ve built large-scale, data-heavy extensions with complex UIs, real users, and revenue streams. Each project reinforced the same painful truth: extension development is inefficient by design. Take state management, for example. In a typical extension, state must be synchronized across multiple contexts—popup, background script, content scripts—each running in isolated environments. Without a unified system, developers resort to manual message passing and redundant synchronization logic. Impact → Internal Process → Observable Effect: Every state update triggers a cascade of messages between contexts, increasing latency and code complexity. Over time, this brittle architecture becomes a maintenance nightm...

This Website Actively Hates You 😈 | Anti-UX Experiment + 418 Teapot Chaos

😈 The Perfect User Experience (That Hates You) What if a website didn’t help users… but actively fought them? This project starts as a clean, premium interface — and quickly turns into a chaotic anti-UX nightmare. 🏃 Buttons escape before you click them 🖱️ Cursor behaves incorrectly (inverted illusion) 🔄 Scroll direction changes randomly 📦 Popups question your life choices 🚨 Fake system crashes appear randomly 📉 Loading never reaches 100% 😈 The interface actively resists you Inspired by the legendary HTTP status code: 418 — I'm a teapot ☕ This project embraces uselessness and intentional absurdity. This website solves nothing. HTML CSS JavaScript Chaos Engineering 😈 👉 https://dev-challenge-sage.vercel.app/ 👉 (Paste your GitHub link here) --- We didn’t break UX. We made UX fight back.

From Zero to Hero

A maioria aprende programação do jeito errado! Comecei a programar com 12 anos, em um trabalho da escola. Nada demais. Só curiosidade e vontade de fazer aquilo funcionar. Hoje, mais de 20 anos depois, eu posso dizer uma coisa com tranquilidade: A maioria das pessoas aprende programação do jeito errado. E não é culpa delas. O problema é o caminho que vendem por aí: "Aprenda IA e ature milhões" Só que isso não te ensina a programar de verdade. Durante minha carreira — trabalhando com sistemas web, principalmente em finanças — eu vi isso se repetir várias vezes. Gente travando no básico, sem entender o que está fazendo, dependendo de tutorial pra tudo. E eu também já passei por isso. Já fui freelancer, já trabalhei em agência, já estive em empresa global… e em todos esses lugares, uma coisa sempre foi clara: -> quem domina a base, resolve Não existe uma única forma "certa" de aprender. Mas existe, sim, uma forma pior: Se você está começando agora, provavelmente já caiu nessa. E tudo be...

sudo - Power Tool, Not a Magic Fix

If you've spent any time in a Linux terminal, you've typed sudo in front of a command. Maybe it was because something was blocked, maybe someone told you to, or maybe you just picked up the habit. Either way, most beginners use it constantly without really thinking about what it's doing. So let's talk about it. What sudo actually is, when you should reach for it, and where it can genuinely get you into trouble. sudo sudo stands for "superuser do." When you put it in front of a command, you're telling Linux to run that command as the root user, the most powerful account on the Root can read, modify, or delete anything. No file is off limits, no permission can stop it, and nothing it does is automatically undoable. That's a lot of power to invoke casually. sudo Makes Sense There are plenty of situations where sudo is exactly the right tool. Installing software, editing system configuration files, managing users, restarting services. These all genuinely require elevated privileges and...

Building an Explainable AI Toolkit for Laravel (Not Just Another ChatGPT Wrapper)

AI is everywhere right now - but most integrations have one big problem: They give answers, but not explanations. If you’re building real applications (customer support tools, decision systems, analytics dashboards), that’s a serious limitation. So I built something to fix that. Most AI integrations in web apps look like this: $response = AI::ask("Summarize this feedback"); And you get: “The customer is unhappy and requests a refund.” But: Why did the system decide that? What signals influenced the output? How confident is it? Can we audit or trace this decision later? This becomes a huge issue in real-world systems: customer support automation decision workflows enterprise dashboards compliance-sensitive environments The Idea: Explainable AI for Applications Instead of just generating responses, what if AI systems could return: structured outputs reasoning / explanation confidence scores decision traces That’s where explainable AI (XAI) meets backend engineering. What I Built I cre...

Robot Training Data Is Turning Labor Into Infrastructure

A man in southern India folds hand towels while wearing a GoPro on his forehead. The point is not surveillance for its own sake; according to Los Angeles Times reporting, the footage becomes robot training data for a U.S. client trying to teach machines to perform real-world tasks. If that sounds like a story about robots replacing workers, it is. But that is not the most important part. The more important frame is this: labor is being reclassified as AI infrastructure. Workers are no longer only producing towels, seams, or warehouse throughput. They are producing the motion traces, retries, corrections, and first-person context that make their own jobs legible to machines. That shift changes the economics. Once labor becomes data generation, the value no longer sits mainly in the finished good. It moves upstream to whoever owns the dataset, the model, the customer relationship, and eventually the robotic system that can replay the work without paying the worker again. The news itse...

How to Connect Mila to Claude Desktop via MCP in 30 Seconds

If you've been using Claude Desktop and wished it could create documents, spreadsheets, and presentations for you — now it can. Mila is an AI-native office suite with a built-in MCP server, so you can connect it to Claude (or Cursor, VS Code, or any MCP client) in seconds. Mila is a collaborative platform for documents, spreadsheets, and slide presentations — think Google Docs meets AI. With 74,000+ users across 50+ countries, it's built from the ground up for AI workflows. The Mila MCP server gives your AI assistant 23 tools to: Create rich documents with headings, tables, and formatting Build spreadsheets with formulas and cell formatting (A1 notation) Design slide presentations on a 960×540 canvas Organize content into servers (workspaces) Full CRUD operations on all document types Sign up at mila.gg and grab an API key from mila.gg/api-keys. Open your claude_desktop_config.json and add: { "mcpServers": { "mila": { "url": "https://mcp.mila.gg", "headers": { "Authorization": "Bear...

Open-source AI Built Qwen’s Reach. Alibaba Wants Cloud Cash

Three hundred million downloads and more than 100,000 derivative models is what success looks like in open-source AI—at least until someone in finance asks where the money is. Alibaba’s own filings say Qwen reached that scale, while AP and Bloomberg report the company is now chasing much harder numbers: cloud revenue up 34% on AI demand, and a target of $100 billion a year in AI and cloud revenue within five years. The easy reading is betrayal. Alibaba used openness to make Qwen famous, and now wants to funnel everyone back into paid services. The better reading is more important: open models were never the business. They were the distribution layer. That distinction matters because it is about to repeat across the industry. Developers still talk about model releases as if the prize is winning Hugging Face. Large vendors increasingly treat that as top-of-funnel marketing for cloud, enterprise integration, and model-as-a-service. Popularity is cheap. Monetization is hard. The Financi...

The Remote Developer's Guide to Southeast Asia in 2026: Internet Speeds, Co-Living Costs, Visa Rules, and the Cities That Actually Work

You know that feeling? The one where you're staring at your screen at 11:47 PM, your third coffee is cold, and you realize... you haven't seen sunlight in two days. Yeah. That's burnout knocking. But here's the thing I learned after three years of remote work: it's not the code that kills you. It's the environment. The noisy roommate. The WiFi that dies during your production deployment. The landlord who thinks "high-speed internet" means 10 Mbps. So I started looking Southeast Asia. Cheap, right? Tropical, right? Wrong answer. Because a recent report from the Asia Real Estate Summit just dropped a truth bomb: the days of renting a $200 shack with "maybe internet" are over. SEA in 2026 is building actual infrastructure for people like us. But you still need to know where to look. And what to avoid. Let me back this up with something real. I found a peer-reviewed study in the Journal of Urbanism that tracks exactly what I've been seeing on the ground: "tech migrant corridors" are res...

I built a pixel-perfect, printer-independent report designer with Avalonia UI

I’ve released ACR Designer, a WYSIWYG report designer for the ACR (Across Report Renderer) engine. It focuses on pixel-perfect layout and printer-independent rendering. Key features: WYSIWYG report designer Pixel-perfect layout (dot-level accuracy) Printer-independent rendering Built with C# and Avalonia UI Runs natively on Windows and macOS GitHub: https://github.com/acrossreport/acr-designer This is my first time building a full cross-platform desktop application with Avalonia, and I was impressed by how smoothly it works across platforms. Feedback is welcome.

I Built a Security Tool That Does Absolutely Nothing (And It's Terrifyingly Realistic)

This is a submission for the DEV April Fools Challenge What I Built: Demo: Code: / security-theatre-simulator IT Security Theatre Simulator 🎭 A devastating satire of enterprise security tools that generate impressive reports with zero actual value. Built for the DEV Community April Fools Challenge 2026 by ShadowStrike (Strategos). What This Does This tool perfectly simulates enterprise security software by: Taking way too long to do absolutely nothing Displaying impressive progress bars that measure fictional work Generating CRITICAL findings about non-existent threats Providing completely useless recommendations Creating reports with suspiciously precise but meaningless statistics Looking professional enough that executives might actually buy it Installation Option 1: With pretty colours (recommended) pip install colorama python security_theatre.py Option 2: Without colours (it still works, just less theatrical) python security_theatre.py Usage python security_theatre.py Then sit...