Guys greetings from finland great to be here. Just watched the Nates YouTube 2h "B&S Claude OS course" video that he posted 1 month ago. Wondering does that relate the classroom AI OS material? 🤔

Let's get to know each other! Comment below sharing where you are in the world, a career goal you have, and something you like to do for fun. 😊

Hey everyone! 👋 I'm Andrea, B2B SaaS founder and the person behind Holito, an AI-native startup. I'm here with one main goal: keep pushing my knowledge around AI and everything it's reshaping in the way we build and grow businesses. What about you? I'd like to get to know you better guys? Drop a comment 🚀

I have started building OS yesterday. For what do you use AI OS guys? I wanna start business so AI OS will be my second brain

AI Agent for Real Estate Visualization from Construction Plans I’m building a tool that automatically generates photorealistic visualizations of a new build or renovation from architectural plans and the construction specification — including a finished, clickable web exposé. The goal is to show the completed property based purely on planning documents before the first brick is laid. What it can do: - 📐 Plan Analysis: Reads PDF plans and the construction specification, then creates a verified “project dossier” as the single source of truth — areas, rooms per floor, apartment layout, materials, existing structure vs. new build. Areas are extracted deterministically from the plans, not guessed by the AI. - 🛰️ Geodata Accuracy: For existing buildings, it automatically retrieves Street View via Google Maps for the real façade, plus satellite imagery for the roof and surroundings. This helps match the actual building instead of inventing a generic lookalike. - 🖼️ Three Visualization Categories: Exterior views, interior views, and 3D floor plans for each apartment. - 📊 Accurate Floor Plans: 2D and 3D floor plans are rendered from the same deterministically extracted wall mask, ensuring they are perfectly aligned and true to scale. Pure image AI cannot reliably do this. - 🌐 Web Exposé: The final output is a finished, clickable exposé containing all views. Architecture: Built around the WAT principle — Workflows, Agents, Tools. The AI only handles orchestration and decision-making, while the actual execution is done through deterministic Python scripts. This keeps accuracy high, because every step left to the AI multiplies the potential error. Tech Stack: Claude Code as the agent, Gemini 3 Pro Image (Nano Banana Pro) for image generation, PyMuPDF for plan/PDF extraction, the Google Maps API for geodata, and Python + Pillow for deterministic geometry. Key lesson so far: Image AI can produce impressive individual images, but it cannot guarantee consistent geometry across multiple viewpoints. That’s why I extract hard geometric truth from the plans and provide it to the AI as a reference, instead of letting it interpret everything freely. True, freely rotatable 3D has intentionally been postponed — for now, the exposé is image-based.