New here? This is the fastest way to get OpenClaw up and running on your own server. You'll need two things: 1. A VPS (I recommend Hostinger — it's what I use) 2. An API key from an AI provider (Anthropic, OpenAI, Gemini, or xAI) Step 1: Get a VPS If you don't have a VPS yet, grab one from Hostinger. They have a one-click OpenClaw template built right into their Docker Manager, so you don't need to mess around with the command line. 👉 Get a Hostinger VPS here (20% off with this link) The KVM 2 plan is more than enough to run OpenClaw comfortably. Step 2: Deploy OpenClaw If you're buying a new VPS: • Head to the Hostinger VPS marketplace and select OpenClaw • Choose your plan, click Deploy • OpenClaw is automatically pre-selected as the application • Complete the purchase If you already have a Hostinger VPS: 1. Go to your hPanel → Docker Manager (install it if you haven't already) 2. Navigate to the Catalog section 3. Search for OpenClaw and click Deploy Step 3: Configure Your Environment During deployment, you'll see a configuration screen where you can add all your LLM API keys. ⚠️ Important: Copy your OPENCLAW_GATEWAY_TOKEN before moving on. You'll need it to log in. If you forget, you can find it later in Docker Manager → your project → Environment section. You only need ONE AI provider key to get started. You can always add more later. Step 4: Wait for Deployment Docker will pull the OpenClaw image and start the container. This usually takes 1-2 minutes. Wait until the status shows "Running".

This is a pretty big one. Not just small tweaks… there are some meaningful upgrades that change how things work day-to-day. Here are the highlights worth knowing: ⚠️ Breaking changes (important) - Qwen OAuth via portal.qwen.ai has been removed - You now need to use Model Studio with API key auth - Older configs (over 2 months) won’t auto-fix anymore — they’ll fail validation instead If you’ve got older setups running, it’s worth double-checking things. 🔧 New features & improvements - xAI integration upgraded (better search + smoother setup) - Image generation added via MiniMax (including image-to-image editing) - Plugins can now request approval before running tools (huge for control) - apply_patch now enabled by default for OpenAI/Codex models - Better onboarding flows for web search + tools 💡 Platform improvements - Cleaner plugin system (less manual setup needed) - Better CLI backend support (including Gemini CLI) - File uploads and messaging actions becoming more unified across platforms - Improvements to container setup and workflows 🛠 Fixes (lots of them)There’s a long list, but the big wins are: - More stable agent runs (fewer crashes) - Better handling of API errors and rate limits - Fixes for Telegram, WhatsApp, Discord, and more - Improved image handling across providers - Cleaner UI behaviour in multiple areas My takeThis update is all about stability + control. Less “it kinda works”More “it works properly and predictably” Especially with: - plugin approvals - better error handling - improved integrations If you’re building anything serious with OpenClaw, this is a solid step forward. If you’ve updated already, I’d be interested to hear what you’ve noticed. Cheers Jason

If you’re actively using OpenClaw, this latest release is actually a meaningful step forward… not just small tweaks. A few things stood out to me 👇 1. Better OpenAI / RAG compatibility They’ve added /v1/models and /v1/embeddings, plus improved how model overrides work. 👉 In plain terms: If you're building anything with RAG, embeddings, or external tools… things should just connect more smoothly now. 2. Tools are finally clearer (big one) The /tools endpoint now shows what your agent can actually use right now. Plus there’s a new “Available Right Now” section in the UI. 👉 This removes a lot of guesswork.Before, you’d try something and hope it worked… now you can see it upfront. 3. Teams + Slack got a serious upgrade - Microsoft Teams now uses the official SDK with proper AI UX - Slack replies are cleaner and interactive elements work better 👉 If you're building bots for clients, this makes things feel much more “production ready”. 4. Skills are much easier to install They’ve added one-click install recipes for things like: - coding agent - GitHub issues - Whisper - Trello - weather 👉 This is a big step toward making OpenClaw usable for non-devs (or at least less painful). 5. Docker + CLI improvements You can now run OpenClaw commands directly inside containers with --container. 👉 Useful if you're hosting on a VPS or running multiple environments. 6. Loads of real-world fixes There are a ton of fixes across: - Telegram - WhatsApp - Discord - Slack - Docker setups 👉 Basically… fewer random breakages and more reliability. My takeaway This update feels like OpenClaw is moving from “powerful but a bit rough around the edges”to “something you could actually rely on for real deployments”. The direction is clear now: - better integrations - better UX - less friction setting things up If you're using it already it's worth pulling the latest version. Cheers Jason 🙌

Why is there so less noise here around this hype topic? Hard to find others who get OC up and running...

I have been paying close attention to AI, but not from the usual angle. I am less interested in shiny tools.More interested in what helps people move faster, think clearer, and remove friction from daily work. Based in Montreal, and curious to connect with people who are actually using this stuff for real. What are you using AI for right now?