I started with a single CLAUDE.md, but as my work grew, it turned into a nested structure, three separate root maps, each routing to its own set of workspaces underneath it, rather than one flat list of projects. My setup: - Personal root map — Routes across everything in my own life and ventures: personal admin, side projects, a festival film concept, everything that's mine, not the company's. - Company capabilities registry — Routes across every AI-driven pipeline the company runs: report builders, a document builder, a video production pipeline, each one its own workspace with its own state. - Company corporate file structure — Routes across the actual document filing system for the whole organization, broken into numbered departments (executive/strategy, finance, standards and templates, and so on), each department getting its own scoped context. What each context includes: - Personal root map — Where each life area or venture actually lives, and a firm rule that company work never gets stored here, it only passes through on its way to the company structure. - Company capabilities registry — Current state of every capability (what's live, what's dormant, what's still pending a decision), plus a routing table so a request for "the video pipeline" or "the cost report" goes straight to the right workspace without guessing. - Company corporate file structure — One CONTEXT.md per department, describing only what belongs in that department and nothing else, plus a generated register acting as the master index across all of them. I'm structuring it this way so each level only has to know about the level directly beneath it, not everything in the whole system at once, which keeps every session focused and fast. This follows the principles of: One fact, one location — Department-level rules live only in that department's CONTEXT.md, never duplicated into the root map or into another department. If a rule changes, it changes in exactly one file.

I am running an ICM knowledge base for my engineering company using GitHub, VS Code, and Claude Code. The efficiency gains in our workflows have been massive, and I see a clear opportunity to offer this to other regional companies as a new business unit. ​However, this dev-centric stack creates too much friction to be presented directly as a product to non-technical clients. ​The model I envision starts with heavy consulting to align the client's processes and culture. Once maturity is reached, it transitions into a managed service: issue tracking, periodic context pruning, and ad-hoc consulting for new agentic features. ​Has anyone here successfully commercialized this philosophy? I am particularly interested in how you package the delivery and abstract the technical friction (like the IDE and repo management) for the end user. Are there platforms already solving this?

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Hey Clief Notes fam! 👋 I’m Junmarvi from the Philippines, currently based in the UAE. I work in materials and operations in the EPC industry, with a Computer Science background. Over time, I’ve moved deeper into AI-directed engineering—designing and shipping production-ready systems, workflows, internal tools, and structured workspaces for agents, context, verification, and standards. My goal now is to keep expanding what I can build, connect with more serious builders, and create opportunities that will eventually allow me to return home to the Philippines and continue this work with my family. Right now, I’m focused on improving how I orchestrate AI across architecture, implementation, security, testing, deployment, and long-term maintainability—while building a stronger network around real-world AI engineering. .

Hi everyone. Is there any rule of thumb on how many words in every layer of an ICM workflow? Im trying to narrow it down in a large repo with many canonical things that apply for every workflow and I have 1263 words in layer 0 and a context routing of 871 words.