Rent their intelligence. Own your memory. Three things make my personal AI different: 1. A clone of me that gets sharper every day, on its own. A judgment-ownership module learns how I decide from my everyday conversations. I do nothing extra. The more I talk, the closer the clone gets. 2. A private RAG that cloud AI can write into but can never read. Not a prompt rule. There is simply no path. 3. A collection of AI blind spots. Not only facts that eight leading AIs don't know, but things they don't notice. Much of it is Japan-specific common sense that any Japanese person takes for granted and the AIs miss. When I spot one, I point it out and make them check. The moment it turns out they couldn't have caught it on their own, it gets flagged and filed. AI NOBORU collects these as AI blind spots. I'm a single father of three and a full-time stay-at-home dad. I also run my companies and do some investing. I built this alone, with no AnythingLLM, no frameworks, no existing packages. It's cloud AI models plus code I wrote myself. Diagrams and details here: https://www.aiofonesown.com/lab/ainoboru/en/ Here's how each one works, as of 4 October 2026. 1. The clone: judgment, not just memory. A module reads my everyday conversations and records what I chose, what I turned down, and why. That goes into the RAG, and whichever model I talk to next — Claude, GPT, or Gemini — answers with it in context. The aim is an AI that can answer "what would NOBORU do here?" Every conversation today makes tomorrow's clone a little more accurate. What it can't copy is genuinely new ideas. 2. The private RAG. Cloud models (Claude, GPT) produce parts — research summaries, findings from papers, pieces of finished work — and only from material that's safe to share. The parts move into the private RAG in one direction only. Using them happens only with local open models (Qwen3.6-35B-A3B, Gemma 4) on my own machines and NAS, through an interface no cloud model is connected to. You get the power of cloud AI without the data leaving. 3. The blind-spot collection. Claude, GPT, Gemini, Grok, DeepSeek, Qwen, Mistral, and PLaMo remember what's in a session or in their memory. But there are things I know that none of them do, and things they all fail to notice. When I run into one, I point it out and make them research it. Only at that moment, when it becomes clear they couldn't have gotten there without looking it up or being told, does it get flagged and filed as a known blind spot. A lot of them are Japan-specific: everyday common sense that any Japanese person shares, which the AIs answer shallowly or miss entirely. The collection holds what only I and AI NOBORU know, and the eight AIs missed. AI NOBORU collects these as AI blind spots. And how it's built: 44 parallel lanes, driven from one chat. 14 Codex lanes, 20 Claude Code lanes, 10 Gemini lanes, each able to run a different model. I talk only to Opus in the Claude Desktop chat. It splits the work across the lanes and reports back there. It works the best cloud AI models hard for very little money, instead of paying for one expensive brain. The principle hasn't changed: models are swappable parts, memory is what you own. The difference is that "memory" now means my judgment, not just facts about me. Where it came from. Back in June I posted here about a beginner's setup: a personal AI on a 2020 Intel iMac, built on AnythingLLM. That became a book, a Udemy course, and a template pack on Gumroad. What I run now is a different system, grown out of that one, with its own RAG and its own memory. It's a personal AI system I built entirely on my own. A note on what this is. This system isn't for sale. There's no product, no repo, no sign-up, no waitlist, and I'm not looking for customers, investors, or collaborators. I like my life as it is and I'd like to keep it that way. This is a dated record of what one person could build in 2026. If you're genuinely trying to think this system through, and not just passing by, I'll answer design questions as time allows. But my days go first to raising three boys and to making decisions for a mid-sized company. I don't have time to answer anything the website already covers, so please read it first, then ask: https://www.aiofonesown.com/lab/ainoboru/en/   submitted by   /u/AIofOnesOwn [link]   [comments]