https://github.com/RinDig/icm-architect Most AI tools try to understand your project by stuffing as much of it as they can into one chat. That is slow, expensive, and they still miss the thing that matters: if I change this, what else breaks? The new System map form walks a repo (or a notes folder) and writes a small catalog instead: - What the pieces are — in your words and in the code’s words (“Chat” is actually called Incubator) - What is real vs leftover vs fake — so nobody builds on a feature that only exists in an old doc - If you change X, what else moves — and what looks related but is the wrong thing You do not get a 40-page audit report. You get index-card pages. A later agent opens the catalog, one card, and the file it points at. That is it. Same idea as the rest of ICM: the folder is the map. A person can open it. An agent can walk it. Nobody has to hold the whole system in their head. Ask it to “map this repo”

It’s live. Starting today, everyone in Clief Notes has access to the new Clief Notes AI. The easiest way to use it? Don’t overthink it. Ask it the question you would normally ask me. “Where should I start?” “What should I focus on next?” “Where did you talk about [topic]?” It’ll use what’s already inside Clief Notes to help answer you and point you toward the right lesson or resource when there’s something worth going deeper on. The goal isn’t to give you another AI tool to play with. It’s to make everything already inside this community easier to actually use. If you want Access to it Comment "READY" and we'll send you access to it!

Hey everybody! I hope you are doing well. I know I've been a little quiet the past few months, but I have some interesting news and wanted to share a little 'sauce,' if you will, that I came across while writing and publishing my new AI book on Amazon. By the way, I highly recommend that if you have ever wanted to write a book, you just do it!!! Here's my story: #1. I happened to come up with a new way to use AI (July 2025) and wanted to test whether anyone was even interested in learning it, so I posted my ideas on LinkedIn. #2. After about a month of posting almost every day, I had a good idea of what people were thinking and saying, and how to lay out the book (so I thought LOL), and I started writing. #3. I had the first version of about six chapters done and shared it with 10 people on LinkedIn who expressed interest, and 4 of them actually read it. #4. I took their feedback, revised some chapters, and wrote a couple more. #5. I then gave the book out again (V2) and connected with two people who had read the whole book and were willing to jump on a Zoom call with me. #6. As I watched the first person start using AI the way I thought it should be done, I realized she had built her 'AI Intelligence System' correctly but was still using it like a search engine, and I realized I was MISSING half the book. 🤣 #7. So I condensed the now 8 chapters down to 6 and then wrote the second half of the book, showing people how to use AI not like a search engine or an answer machine. (I call it briefing AI like a CEO.) #8. I gave that version of the book (V3) to about 100 people (A mentor of mine a couple of years ago mentioned that when you do write a book, try to get 100 people to read it before you publish it; that will give you the truth you need about whether it should be published) I received more feedback, made some tweaks, and, after writing the book 4 1/2 times, I went ahead and published it. And believe it or not, I hit best-seller status in two days. The 'secret' is to send your Amazon book link to everyone who read it and ask them to buy it at a low price the day after publishing.

If anyone's curious if the methods I'm teaching here will last long enough. Just know that y combinator is now asking for solutions we built years ago. https://www.ycombinator.com/rfs

Recently a lot of excellent community discussion around how to ICM, largely because that’s the foundation but also refocused due to @Bas Rosario’s Post on ICM as building a Cake. Having experienced rapid growth in my past, one of the hardest things to do is keep language and definitions aligned. If I say the Agent did this, where does your brain go? Lines get crossed because you have so many levels of understanding and perspective. Some people are coming from non-technical backgrounds and have learned through corporate ai marketing. Others coming from corporate environments where language is defined for them by the management and designers building their infrastructure. Mini cultures with their own language. One of the brilliant aspects of ICM is it's commonality with almost anyone on a computer. It's just a folder, from that foundation we can all get on board. What's difficult is what happens next. I had this conversation with claude during a planning session. Claude asked me did I want agents or roles? I responded back by did he mean an agent like claude or codex, which is really an LLM, a purpose built agentic piece of software that the market tells me is an agent that does stuff? Or a folder acting as an agent with a specific role. I didn't know what the underlying meaning implied, how to answer? So I asked here was the response. 1. Engine — the LLM brand (Claude, Codex, Kimi, Minimax). Raw cognition, rented capacity, the electrons. Interchangeable. 2. Agent — the ICM folder. Persistent shaped context: identity + rules + reference + memory + boundaries. A standing operator that exists on disk and endures across sessions. This is your "folders hold attention" — an agent is where attention lives. 3. Role — a lens/hat: a function performed at one step of a process. It exists only in the doing. Where attention points right now.