Real estate agents lose leads because they reply too slow — 71% of buyers go with whoever responds first. Built a small AI system that fixes this: instant lead response, auto-qualifies them, books a call on the agent's calendar automatically. Even handles missed calls with an instant text-back. Just closed my first client with it. Happy to share more if anyone's building something similar, or if you know an agent who'd want this — would love an intro 🙏

A lot of people are creating prompts and setups to simulate Fable, so I gathered the best ideas and turned them into a Skill. Take a look and see whether it is useful for you. If it is not, please tell me why. I want to understand what is missing so I can improve it. Fable Mode makes the model work with a more disciplined methodology on complex tasks. It enforces a five-stage workflow: 1. Scope — understand the objective, expected deliverable, constraints, and what could go wrong. 2. Evidence — verify facts, files, sources, and assumptions before reaching conclusions. 3. Attack — challenge the plan itself, looking for weaknesses, risks, and overlooked issues. 4. Verification — test and validate the result before declaring it complete. 5. Reporting — explain what was done, what was validated, and what limitations remain. It also guides the model to: - use stronger models for planning and review; - use lower-cost models for straightforward execution; - choose the appropriate reasoning effort level; - avoid unnecessary clarification questions; - never rely solely on memory; - turn successful workflows into reusable methods. In one sentence: Fable Mode doesn't change the AI's intelligence—it changes how the AI plans, verifies, and delivers its work. It is especially valuable for research, strategy, software development, project analysis, and any task where mistakes can significantly impact the final outcome.

From AI operating systems and first client deliveries to open-source tools, second brains, and personal AI assistants, this week inside AIS+ showed that the best products often start by solving your own problems first. 🚀 Standout Wins of the Week inside AIS+ 👉 @Miguel Alfonso Murillo closed 3 clients using the AIOS he built for his own business, sharing how his journey evolved from experimenting with ChatGPT to running his operations with AI. 👉 @James Joens delivered his first client project just 11 days into AIS+, saving his client $1,400 on a single deal and following it up with his first in-person cold outreach meeting. 👉 @Jenni Saarenpää built her own AI-powered Wealth Analyzer after realizing the tool she wanted didn't exist, creating a personal FIRE planning app with powerful financial modeling. 👉@Konstantinos Karamatzianis built and open-sourced Session Guardian, solving Claude Code session limits for himself before sharing it with the entire community. 👉 @Girish Mohan created an AI Treasurer to manage expenses for a 100-person family festival, turning a real-life headache into a practical automation. ⸻ 🎥 Super Win Spotlight | @Jacob West Jacob joined AIS+ looking to build a business, not just learn AI. Since then, he has: - Built the confidence to leave his job and go all in on entrepreneurship - Closed larger AI projects by applying real business fundamentals - Shifted from learning tools to building a scalable business around them His biggest takeaway? Skills matter. But confidence comes from building, taking action, and surrounding yourself with people already doing what you want to do. 🎥 Watch Jacob's story 👇 ✨ Every week, members turn personal projects into client work, ideas into systems, and momentum into real businesses.

Day 1 done. Ended up combining two skills in one build: Firecrawl scraping + the newsletter automation. Pointed it at my own business instead of a demo topic (real estate in Dubai). Firecrawl pulls recent transaction data, Python turns it into the actual stats (median price/sqft, yields, MoM change), Claude writes the copy in my brand voice, infographic cards get rendered with my branding, and it all drops into Gmail as a draft so I can sanity-check it before it hits my clients' inboxes. AI never makes up a number. Everything on the cards comes straight from a scraped transaction, right down to price per sqft, yields, bedroom mix and the most-traded buildings that month. Screenshots below 👇 If anyone else is using this in the real estate industry, curious to see how you're helping your clients with it.

Today I finished building an AI-powered real estate lead management system using n8n + OpenAI + Airtable. The goal was to automate the journey from a website inquiry to a qualified lead with minimal manual work. Current features: ✅ Website lead capture ✅ AI-powered lead analysis & summaries ✅ Buyer/Seller classification ✅ Lead scoring & quality (Hot / Warm / Cold) ✅ Automated email follow-ups ✅ AI-generated SMS follow-ups ✅ Consultation booking ✅ Airtable CRM for lead, appointment & follow-up management ✅ Google Sheets integration ✅ Error handling throughout the workflow I've attached a few screenshots of the CRM to show how the data is organized after the automation runs. Still improving the system, but it's been a great project for learning how to combine AI with real business workflows. 💬 If you were building this, what feature would you add next? I'd genuinely appreciate any feedback or suggestions. #BuildInPublic #n8n #OpenAI #Automation #AIAgents #Airtable #CRM #WorkflowAutomation #RealEstate #ArtificialIntelligence