Join me as I demonstrate how to instantly deploy your own complete development and application hosting stack using only free cloud resources. In this live demo, I'll show you how to: - Launch two powerful servers with just one click - Get your own self-hosted app deployment platform (think Vercel/Netlify, but yours) - Set up browser-based remote workspaces and development environments - Access everything through simple web interfaces What you'll get: - Server 1: Personal app deployment platform for hosting websites, APIs, and databases - Server 2: Remote workspace server for secure browsing and development environments - Total resources: 4 CPU cores, 24GB RAM, 160GB storage - completely free - Ready in minutes: No complex setup, no credit card required Perfect for developers, students, or anyone wanting their own cloud infrastructure without the monthly bills. I'll walk through the entire process from deployment to accessing your new servers. Bring your questions - we'll have time for Q&A at the end!

Just recorded a tutorial on connecting Agent Hub with n8n! Agent Hub is a new platform that lets you create and combine agents across multiple platforms like n8n, flowise, etc. https://www.skool.com/vibe-coders/classroom/a51ef45d?md=4b49bd7fdba54616ad0fafb026a58d3d Join the waiting list at theagenthub.co - connect agents from different platforms for cross-platform AI conversations and workflows. Quick Setup: 1. Download "Basic Agent Hub Chat Bot" n8n template 2. Import into n8n workflow 3. Configure webhook URL and bearer token authentication 4. Set up your AI model (OpenAI, OpenRouter, etc.) 5. Test connection and activate

Is this achievable? Looking to vectorize course content and create personalized roadmaps for each user. Been thinking about this all weekend after buying my 7th Skool course I'll never finish. The technical approach I'm exploring: - Vectorize all course content using OpenAI embeddings - Store in Pinecone/Supabase vector DB - AI assessment to understand user's current state - Generate personalized paths based on semantic similarity + user goals - Track progress and adapt as they go - Chunking content effectively (too big = lose nuance, too small = lose context) - Balancing prerequisite requirements with personalization - Making assessment feel conversational, not like a test - Deciding whether to use pure content vectors or add behavioral signals Made a quick video showing what I've got so far: My real question: Is this overengineering the problem? Like, do we even need AI-powered personalization or would better UX solve the same issue? Anyone else working on similar vectorization/personalization problems? What approach are you taking? Specifically curious about: - How you handle prerequisite dependencies in personalized paths - Whether you're using behavioral data or just content embeddings - If anyone's seen actual completion rate improvements from personalization genuinely trying to figure out if this is worth pursuing further or if I'm solving the wrong problem.

I've added three questions for call type, length, and frequency to our poll. If you've already given your preferred times, take a sec and give us your thoughts on these as well. https://heyform.self-host.ai/form/bj80vVNI

i’ve been working on a tool that spins up two free servers for you: - one’s a dev box you can mess around with, try stuff, break stuff, rebuild it - the other’s a coolify box so you can actually host the things you make the whole thing’s automated — just want to see how it runs for different folks. if you’re in, drop a reply with: 1. your platform → windows, mac, or linux 2. your skill level (1–5) → you’ll need: - a domain on cloudflare - a github account don’t stress if you don’t have these — i’ll walk you through it. bonus points if you already do.