Most people build AI agents that work in silos. Each one knows its own lane and nothing else. That's how mine started. DD analyst for underwriting. Builder intel for homebuilder tracking. Market scout for county scoring. None shared knowledge. So I built Scholar — the training department for my AI org. 🔬 Scholar researches knowledge tracks daily — earnings calls, acquisition models, market trends, regulatory changes. Structured knowledge files. 📡 Pushes to every director. Scores findings for relevance, injects into memory files. 🧠 Pre-flight context injection. Every director reads shared knowledge before acting. 🔄 Directors write back. Knowledge compounds automatically. 42 entries across 5 departments per digest cycle. Every agent gets smarter daily without my input. The real unlock isn't multiple agents. It's agents that educate each other.

How would you setup Claw to become expert ib a field given a certain book as a pdf or word doc? And is it better than RAG system with Claude ai agents? Waiting for your thoughts and comments. Comment below for brainstorm ing

Hi Community! I am Ben, a fullstack developer and AI Entrepreneur. I want to build an OpenClaw and Obsidian system to transform Copywriting Top books into Auto Viral article generation System. Looking for early founders and contibuters. Please comment if your interested.