Most people open Claude Cowork and just... type. They're missing 80% of what it can do. Here are 5 ways I use it to actually get work done — not just generate text: → Auto-organize files without touching a folder → Send emails without opening my inbox → Summarize any doc in seconds → Schedule tasks that run on their own → Turn raw data into a shareable report Swipe through 👉 Which one are you trying first? Drop it below 👇

Most people use n8n to automate workflows. I used it as the backend of a live SaaS product. 💡 What I built Legal Contract Risk Analyser Upload a legal document → AI analyzes every clause → you get a full risk report in under 5 minutes. This is not a workflow sitting inside the n8n canvas. 👉 It’s a real web app anyone can open and use. ⚠️ Why I built this Most of us sign contracts we don’t fully understand. - 20 pages of legal text - 2–3 hours of reading - Still unsure what’s risky And the worst part? The riskiest clauses don’t look risky. Example: “The Client accepts full responsibility for all third-party claims” Looks harmless. It’s not. And keyword search? Completely useless here. 🧠 How it works This is where things get interesting. Instead of keeping everything inside n8n, I split it into: Frontend + Backend + AI pipeline 🔧 Under the hood: → n8n → runs the entire backend pipeline → Google Gemini → analyzes each clause, scores risk, rewrites it simply → Hybrid RAG (pgvector + BM25) → finds risky patterns using semantic + keyword search → Supabase → stores knowledge base + analysis results → HTML / CSS / JS → frontend UI → Netlify → makes it publicly accessible 🎯 What you get Every clause gets: ✅ Risk level (High / Medium / Low) ✅ What it actually means (no legal jargon) ✅ A safer alternative No more guessing. No more signing blind. 🧩 Who this is for - Freelancers reviewing contracts - Startups signing vendor agreements - Business owners who can’t afford hidden risks 🔥 The real lesson n8n is not just an automation tool. It can be your backend for real AI products. Same tool. Different thinking. Try it with any contract — link in comments 👇 If you’re interested in seeing the Product Requirement Document (PRD) and how I built this end-to-end,drop your email in the comments — I’ll share it.

Been deep in Anthropic's ecosystem lately and wanted to share what's working for me — especially for anyone building AI automations and workflows. 🤖 CLAUDE (claude.ai) The core assistant and honestly one of the best reasoning models out there right now. What sets it apart isn't just raw capability — it's how it handles nuance, pushes back when something's off, and stays honest. Great for research, writing, strategy, and complex problem solving. If you're not using Claude as your primary AI assistant, it's worth testing. 👥 CLAUDE COWORK This is the collaboration layer — shared projects and persistent context for teams. Instead of everyone running separate Claude conversations and copy-pasting outputs into Slack or Notion, Cowork lets you build on shared context together. Huge for agency teams or anyone running client workflows where multiple people need to interact with AI outputs. 💻 CLAUDE CODE This is the one that's blown me away. It's a terminal-based agentic coding tool that actually reads your entire repo, writes and edits files, runs commands, and iterates — all step by step with your approval. It's not just autocomplete. It's more like pairing with a dev who actually understands your project structure. The three together create a really powerful stack: ✅ Claude for thinking + research ✅ Cowork for team collaboration ✅ Claude Code for actually building and shipping For anyone in this community building AI automation services — this combo is worth serious attention. Claude Code in particular can dramatically speed up n8n workflow builds, custom integrations, and client deliverables. Who else is using any of these tools? Drop your experience below 👇

I'm now a n8n Verified Creator. Been learning AI automation- building real workflows, experimenting, failing, and figuring things out step by step. Every build teaches something new. More builds coming soon 🚀 Check out my profile here: https://n8n.io/creators/divyanshugupta/

Been building quietly for the past few weeks and finally ready to share. I submitted SnapCaption AI to the Flowroom AI App Creation Contest — and honestly, I learned way more than I expected during this build. 🚀 What it does You upload a photo → AI actually looks at it → and in ~10 seconds you get: - 3 platform-optimized captions - A 3-slide Instagram story - 30 ready-to-use hashtags Plus 5 tone styles: Funny, Heartfelt, Poetic, Gen-Z, Professional Works for IG, LinkedIn, Twitter. 🧠 The interesting part — Vision AI This isn’t a generic caption generator. The AI analyzes the actual image — scene, lighting, mood — not just keywords. But getting this right was tricky… - It would hallucinate random stuff (“midnight vibes” on a bright beach pic 😅) - Sometimes added irrelevant context like timestamps - Had to build a validation + retry layer to clean outputs 🛠️ Stack - Flowroom (app infra) - GPT-4o Vision (image + captions) - Vanilla JS - CSS animations Tried to make it feel like a real product, not just a demo. 💡 3 key learnings 1. Vision AI = prompt engineering gameIf your prompt isn’t tight, the output drifts fast. 2. UX matters more than AILoading states, copy buttons, history — spent more time here than on the model. 3. Shipping > perfectHad bugs till the last minute. Real-world fixes hit different vs sandbox builds. 🔗 Try it If you post content regularly, would love your feedback (especially on caption quality across different images) Link: https://flowroom.com/room/3SeEI4 Happy to answer anything about the build 👇