Hey everyone 👋 I run an AI automation agency focused on end-to-end custom solutions for businesses in Central Europe. I've been building everything myself (workflows, AI agents, full-stack apps), but we've hit serious traction and I need to scale the team. 📊 Where we're at: - Built 20+ automation solutions for clients (real estate, e-commerce, hospitality) - Growing social media presence in our region - Currently working on a Real Estate Property AI Management System 🔍 Who I'm looking for: !! NOT looking for: No-code-only builders or beginners Looking for: Builders with junior+ coding & dev-ops experience who can handle: ✅ Backend/Infrastructure: - Python, Node.js, or similar - Postgres DB design - API integrations (REST, webhooks, OAuth) - Microservices architecture - Cloud deployment ✅ Automation & AI: - n8n workflows (or similar at scale) - LLM API integrations (OpenAI, Anthropic, Claude) - RAG systems, vector databases ✅ Frontend (bonus, not required): - React, Next.js - Dashboard/admin panel development ✅ Comfortable with: - Client-facing work (understanding requirements, proposing solutions) - Working async (EU timezone preferred but not required) - Project-based OR long-term collaboration 💼 Current project example: We're building a Real Estate CRM + Payment Automation System: Stack: - Postgres (EU region, GDPR compliant) - n8n for automation workflows (self-hosted) - React dashboard (agent performance, lead tracking, analytics) - Telegram Bot API (tenant communication) - AI services (PDF parsing, payment matching, email automation) Scope: - Lead management system (pre-sale CRM) - Automated payment processing & reminders - Agent dashboards & performance tracking - Email campaigns & templates - Offer builder & website API - Microservices: Lead capture, email service, offer generator, sales analytics, pipeline manager Timeline: 8-12 weeks 🤝 What I'm offering: Option 1: Long-term collaboration (Full-Time/Part-Time)

🧠 AI Product Launches, Updates & Research • Agnes AI hits 5M users & open-sources SEA LLM — Singapore’s Agnes AI announced it crossed 5 million registered users and released an open-source Southeast Asia-focused 8B-parameter LLM (Agnes-SeaLLM-8B). Significance: Boosts regional AI autonomy and developer access to open models. • Google Gemini launches “Personal Intelligence” feature — Google expanded Gemini’s capabilities with a new Personal Intelligence feature that, with consent, leverages Gmail, Photos, YouTube, Search data for context-aware answers. Significance: Advances personal AI assistance with deeper, consent-based context use. 🚀 Startup, Funding & Business Moves (No confirmed new funding rounds or acquisitions with clear Jan 15 execution dates discovered beyond product/user milestones.) 🏛️ AI Policy, Government & Ecosystem • Anthropic names India MD ahead of office launch — AI safety/LLM leader Anthropic appointed Irina Ghose as Managing Director for India, signaling market commitment ahead of its first India office. Significance: Strengthens AI R&D ecosystem and local presence for a major global AI lab. • Google launches Market Access Program for Indian AI startups — Google announced an initiative to help Indian AI startups scale globally, backed by reports of India’s market projected to grow ~$126 billion by 2030. Significance: Boosts global scaling support for India’s AI ecosystem and startup growth. 🏫 AI in Education & Skill Development • Pune college holds 5-day IT & AI programme — Bharati Vidyapeeth College of Engineering hosted a multi-day faculty development programme covering AI and IT trends, inaugurating a new Flow AI Innovation & Research Lab. Significance: Enhances institutional AI capability and research infrastructure. 🧠 Industry Research & Trends (Reported Yesterday) • AI adoption research highlights slow enterprise deployment — Carne research indicated only ~18% of asset managers have moved AI to core operations, reflecting cautious enterprise adoption. Significance: Suggests gap between AI awareness and meaningful deployment in finance.

I want to share something a little more personal than I usually do here—and use it as a conversation starter. I didn't get into AI and automation because I was obsessed with tech. I got here because I lost my dad. My father was the kind of person people came to for clarity. A mentor. A problem solver. Someone who always left things better than he found them. He eventually built a wedding officiating business, and he's the reason I became an officiant myself. When he passed away in November 2023, I entered the darkest season of my life. Business didn't stop, though. Emails still came in. Clients still needed support. I still had to show up, sometimes smiling through things I hadn't processed yet. At some point, I just didn't have the energy to keep doing everything manually. Both businesses started drifting—not because I didn't care, but because I was running on empty. Around that time, I leaned into AI and automation out of necessity, not ambition. I built systems that kept things running without me having to be "on" all the time. That gave me something I didn't realize I needed so badly: space to grieve, space to heal, and space to breathe. That experience changed how I see this work. For me, automation isn't about replacing people or chasing scale at all costs. It's about giving people enough freedom and clarity to show up where it matters most in their lives. I'm sharing this because I think we rarely talk about why we're really in this space. So I'm curious (and only if you're comfortable sharing): What's the deeper thing driving you to build, learn, and push so hard in this field? Not the surface-level goal. The real reason you get out of bed and keep going. I'd love to hear your stories.

In this video, I show you how to use Claude Code with n8n to build pretty much anything, from automations to full web apps. I walk through how to connect Claude Code to the n8n MCP server so it understands all the nodes, configurations, and how workflows actually work, and how to give it n8n skills so it can build and modify workflows effectively. Then I show you how to take existing n8n workflows, analyze and optimize them, and turn them into real front-end apps. We go through building the app, pushing it to GitHub, and deploying it on Vercel so you can see the full end-to-end pipeline. This setup makes it way easier than most people think to go from workflow to real product.