Update: How My Local AI Agent "Daemon" Learned Logical Discipline (Part 2)

🧠 Part 2: I Didn’t Patch the Code, I "Nurtured" the Logic 🚀 Solving AI Contextual Leakage Without Vector DBs Yesterday, I shared my journey building Daemon, a local AI agent with "Stable Memory" using n8n + PostgreSQL. Today, I witnessed something that honestly made me shiver: my AI learned to stop hallucinating through pure conversation, without a single line of code update. 🧪 The "Gagak" (Crow) Failure: A Reality Check In my first stress test, I hit a wall called Contextual Leakage. I gave Daemon two separate contexts in one session: Personal: "I'm researching Crows for a personal logo." Project: "Our new project is 'Black Vault'. What’s a good logo?" 🔴 The Result (FAIL): Daemon im mediately jumped the gun: "A Crow logo for Black Vault would be perfect!" It was being a "Yes-Man," assuming connections where none existed. It lacked Logical Discipline. 🛠️ The "Meta-Conversation" Strategy Instead of rushing to tweak the system prompt or adding more nodes, I treated Daemon like a Thi