You can now leave reviews on the about page (only paying members which is a little annoying but that's Skool settings not mine) It would seem there is a review page, even if you may not be staying long or have gotten your fill out of the content, if I have helped in any way please leave a review by clicking on this link to help others understand what is in here! https://www.skool.com/cliefnotes/about

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!

EDIT: WE HAD OVER 100 PEOPLE SIGN UP IN TEN MINUTES....GOING TO BE ROLLING OUT ACCESS ON SLOWER BASIS NOW SO I DONT RUIN MY BANK ACCOUNT WITH TOKEN SPEND FOR YALL (im covering ai costs for everyone) but keep applying we are keeping track and will be letting more people in and reaching out about getting you all access one by one especially VIP. Our Platform is here, the thing a lot of you have been asking for and I have been teasing Take your ICM folders and second brains, put them in the cloud, and work on them together in real time. You upload your folders and files. One strong model with a good harness reads the map and becomes the agent you need. No new agents to build, no zip files to pass around. Each workspace runs in its own container. It renders your markdown, edits your files, installs packages, runs Python and Playwright, and multiple people can work in the same space at once. No Mac Mini needed to keep your data separate either. We're opening it to VIP and alpha testers first, and I'm covering the AI cost while we test so cant do a full role out yet. Free AI use which is great for those users, not great for my bank account haha. ✍️ Sign up for access: https://docs.google.com/forms/d/e/1FAIpQLSdSnToxclxt8EgoB2GizrEvHP7gzOedVcRXdCkpi1SZwR8ZfA/viewform 🔗 Questions, or want to work heavier with this? Email info@eduba.io

I have been living inside ICM for a while now, and it changed how I build. Recently I started pairing it with one more idea, and the combination clicked hard enough that I wanted to share it here and see what you all think. Quick version: ICM 2.0 = ICM (the interpretable filesystem) + Colibri style routing (a router that only wakes the experts a task actually needs). One gives you a system you can read. The other gives you a system that stays light. Together they run local and sovereign (this system build ACTUALLY helped me move the needle, i.e. KPI, creating content, closing deals, etc) --- 🗂️ First, why ICM already wins For anyone newer to it, the core of ICM as I understand it: 1. The filesystem is the operating system. Plain-text steps, one job per folder. No black box. 2. It documents itself. Every folder says where you are and what is next, so you never lose the thread. 3. It is resumable. Close the laptop, come back next week, pick up exactly where you were. 4. It is portable. What runs in your head, in an agent, or on a local model is the same folder of plain steps. The magic is interpretability. You can always open the box and see the reasoning. 🐦 The piece I added: Colibri (the router) The problem with a big system is that it gets heavy. You do not want every folder, every expert, every context loaded for every task. A hummingbird does not flap every muscle to hover, it uses only what the moment needs. Colibri is a mixture-of-experts idea applied to a whole life or business: 1. Only a sliver is ever active. Roughly 5 percent at a time, not the whole library. 2. A router picks the ~8 experts the task needs** and wakes only those folders. 3. Core stays pinned, the rest streams in** on demand and caches while it is hot. 4. It learns to predict which experts you will reach for next, so the right context is already warm. 🧬 Put them together and you get ICM 2.0 1. The ICM filesystem becomes the DNA / schema** — the canonical map of every expert the system can call.

One chat. One agent. One long context that fills with tool dumps, half-ideas, and "sure, let's build that." You call it brainstorming. The context window says otherwise... The problem When design and doing share one seat: - Context floods. Digests never form. - Weak approaches never die. They just get rewritten. - You "approve" a vibe, not a design. - Build starts before the frame can defend itself. Pretty threads. Soft decisions. Expensive rework. The idea: a design swarm I shipped a skill pack for this: brainstorming-swarm v1.0.0. Not a build swarm. A design swarm. 1. Fan independent lenses (failure, stakeholder, constraint, temporal, experiential). 2. Return digests only. Schema caps. No raw dumps into the conductor seat. 3. Hold hard gates for the human (redirect discovery, pick the winner). 4. Stop at a written design. Do not build from this skill. If your harness can run multi-seat, multi-tab, or multi-chat: dispatch-first. If it cannot: serial fallback with the same stages and honest labels. Floor is not default. The habit: orchestrator, not doer The main chat advises, routes, and synthesizes. Heavy work leaves the seat. Brief in. Digest out. Same turn when the work qualifies. Workers execute. They do not own taste or rewrite the method. You keep the gates. That is the job. Micro example Goal: redesign a personal reading list app. - Five lens digests, each capped. - Three competing approaches under different axioms. - Critique kills two, salvages one hybrid. - You pick. Spec writes. Session halts. No code in that run. That is the point. Get it Deep Dive (method + diagrams): https://aris-space.com/documents/workflows/brainstorming-swarm Members on Ari's Space: download the skill pack zip (v1.0.0). Load SKILL.md. Point it at a hard problem. Prefer dispatch-first. Stop at written design. Argue first. Code second. //A<3