How I organized all my marketing content into three folders any AI can use.

Knowledge, decisions and methods. It took me four restructures in eight months to land on this, and it's the reason my AI stopped asking where things are. Here's the exact structure, the instruction file at the top of each folder, and how to copy it in Claude Code, ChatGPT or whatever you use.

Every AI tool has the same weakness. It's only as good as the context you hand it, and most marketers hand it context one chat at a time. You paste the brand voice again. You re-explain the ICP again. You dig through last month's thread for the positioning you finally got right.

For a while my files lived wherever the conversation happened. A research run ended up next to a client deliverable. A half-formed idea about AI search sat in the same folder as my pricing. The AI couldn't tell which was decided and which was a guess, so it treated them the same.

Today everything I do, for my own marketing and for clients, lives in three homes. Each has one job. Each has a short instruction file the AI reads before it does anything. Here's the whole thing on one page:

Three columns: Knowledge in the vault folder for things still evolving, Decisions in the growth folder for things I've decided, and Methods in the delivery folder for things that work for anyone. A bar underneath reads knowledge, proven in decisions, hardened into methods.
The three homes. Every file I create goes into exactly one of them.

How I ended up with three folders after four reorganizations

I didn't design this up front. I can see every step of how I got here in my commit history, because each restructure fixed a specific mess.

Timeline from February to September 2026: Split, Brand brain, Genericize, Growth home, Vault reset, Rename.
Eight months, pulled straight from my git log.

Every one of those fixes was the same fix. I was separating things that change from things that don't, and things that belong to me from things that belong to anyone.

How I sort every file with one question

When something new shows up, whether it's an article, a call transcript, a draft or a decision, I ask one question: could new evidence change this?

The part that took me longest to learn is the rule in my instruction file: route by type, not by where the conversation happened. A single client call can produce a decision, a learning and a reusable method. They go to three different places, even though they came out of one conversation.

The AI can't tell a guess from a decision unless the folder tells it.

How I gave every folder its own instruction file

This is the piece that makes the structure work with AI and not just for me. At the top of each home there's a short file the AI reads before it does anything else. In Claude Code it's called CLAUDE.md. In other tools it's project instructions, a rules file or AGENTS.md. Same idea.

A file explorer showing the workspace: growth with business, config, brand, production, research and the vault; delivery with skills, templates, clients and lessons; and the site. CLAUDE.md files are highlighted in each.
My actual workspace, with client names replaced. The highlighted files are the instructions the AI reads first.

Each instruction file answers three questions and nothing else:

  1. What is this folder for? One sentence, and how it relates to the other two homes.
  2. Where does each kind of thing go? The subfolders, and the routing rules for anything new.
  3. How do we write here? My style rules: no em dashes, no banned AI phrases, no number without a source.

Here's the one at the top of my growth folder, shortened:

The CLAUDE.md file for the growth folder: a drop routing section with four numbered rules sending reusable things to delivery, decided business truth to growth, evolving knowledge to the vault, and ambiguous things to the vault inbox with a question.
The routing rules live in the file, so I never re-explain them in a chat.

Notice rule four. When the AI can't tell where something belongs, it doesn't guess. It parks the item in the inbox and asks me. That one line has saved me from more mis-filed work than anything else in the file.

How I route anything I paste in

Day to day, I almost never pick a folder myself. I paste something in and say "file this". The AI applies the routing rules and tells me where each piece went and why.

Notes from a sales call split three ways: the buyer behavior quote goes to vault sources, the pricing objection goes to growth business, and the discovery question goes to delivery templates.
An illustrative example. One set of notes, three destinations.
What I type

File this. If it splits, split it. Tell me where each piece went and why, and ask me about anything you're not sure of.

The "tell me why" part matters. Reading the AI's reasoning is how I catch the times it treated an opinion as a decision. It's also how I noticed my rules had gaps. Each time I corrected a routing call, I updated the instruction file, so I only had to correct it once.

How I built a second brain the AI maintains

The vault is the home I rebuilt most recently, and I didn't invent the pattern. It comes from Andrej Karpathy's LLM Wiki gist, published in April 2026. He describes it as "an idea file", something you paste into your own AI agent and let it build from. The line that sold me:

"Obsidian is the IDE; the LLM is the programmer; the wiki is the codebase."

His point is that you stop writing your notes yourself. In his words: "You never (or rarely) write the wiki yourself." The LLM "writes and maintains all of it", and you're "in charge of sourcing, exploration, and asking the right questions." That was exactly my problem with the old swipe file. I was the only one who could maintain it, so nobody did.

Karpathy's pattern has three layers, and my vault maps onto them one to one:

Karpathy's layerWhat it isIn my vault
Raw sourcesDocuments you curate. Never changed.sources/, dated filenames, read-only
The wikiMarkdown pages the LLM writes and updateswiki/, split into aeo, agency, channels, clients and tools
The schemaA document telling the LLM how the wiki is structured and which workflows to followCLAUDE.md at the top of the vault
index.md + log.mdA catalog of every page, and an append-only record of every ingest and updateSame names, same jobs

I open the whole folder in Obsidian to read it. Every page links to others with [[wikilinks]], so the graph view shows which ideas connect. But Obsidian is just the reader. Claude Code does the writing, and the files are plain markdown that any AI tool can open. What I added on top of Karpathy's version is the inbox/ and the routing out to my other two homes.

Three stages: inbox for a daily note written by me and the AI, sources for raw material that is read-only, and wiki for pages written by the AI only. Below, index.md lists every page and log.md records every change.
My version of Karpathy's LLM Wiki. Capture is cheap and daily. Structure happens later, on purpose.

Three folders, three rules:

The lesson I wrote in my own daily note when I set this up: capture and structure are separate jobs. My first version tried to file every lesson into the right wiki page as I captured it. That made capture slow enough that I skipped it. Now capture is one quick note, and turning notes into wiki pages is a separate step I run later.

I'll be honest about where it stands. The wiki is young. Most of the value so far is in the daily notes and the habit, not in a big polished knowledge base. The structure is there so it can grow without turning back into a swipe file.

How I promote an idea from note to playbook

The three homes aren't just storage. Ideas move through them in one direction.

Three steps: Learned in the vault wiki with status evolving, Proven in growth where the page is marked ready-to-promote, and Hardened in delivery as a skill or template any client gets on day one.
Every wiki page carries a status in its frontmatter. The AI suggests; I decide.

Something I learn about AI search starts as a wiki page. I try it on my own marketing first. If it works, the page gets marked ready-to-promote, and it becomes a skill or template in delivery that every client gets. The AI is allowed to flag candidates. It's never allowed to promote anything on its own. That's the rule that keeps untested ideas out of client work.

How I give every client the same folder

Inside delivery there's a client-scaffold template. Every new client folder is a copy of it: an instruction file, a config folder with their voice guide, ICP, content pillars and seed keywords, then folders for research, intelligence, production and lessons.

A client-scaffold template on the left copied into three identical client folders, each with CLAUDE.md, a config folder holding voice guide, ICP, pillars and seed keywords, and intelligence, research, production and lessons.
Names removed. The shape is identical for every client, including the demo client I use for testing.

Because the shape never changes, a skill written once works on every client. It knows the voice guide is at config/voice-guide.md without being told. It also keeps clients apart: a skill running on one client's folder never sees another client's research.

How I'd set this up in ChatGPT, Claude or anything else

I run all of this in Claude Code, because it works directly on files on my machine. But the structure doesn't depend on that. The split between knowledge, decisions and methods works in any tool. Only the names change.

Table mapping each home across tools. Instruction file: CLAUDE.md, project instructions in ChatGPT and Claude, AGENTS.md or a rules file elsewhere. Knowledge, Decisions and Clients become separate projects in ChatGPT and Claude. Methods become Custom GPTs in ChatGPT and Skills in Claude.
The same three homes in whatever you already use.

If you live in ChatGPT or Claude.ai, here's how I'd start:

  1. Make a "My business" project first. Upload your decided docs: offer, ICP, voice guide, banned words. Put the routing rules and style rules in the project instructions. This is your growth home, and it does the most work.
  2. Make a "Knowledge" project. Drop articles, studies and call notes in as files. Ask it to keep a running summary document, and tell it in the instructions that nothing in here is decided.
  3. Turn repeat work into methods. Any prompt you've used three times becomes a Custom GPT (ChatGPT) or a Skill (Claude). Keep it generic, with no client names inside.
  4. One project per client. Same files, same names, every time. Copy the instructions from a template project.

The part you lose outside a file-based tool is routing. ChatGPT can't move a file from one project to another for you. You'll do that sorting yourself, but you'll be using the same question.

What I got wrong along the way

One thing I'd keep exactly as it is: when an automated sync between folders ran into files it wasn't sure about, it quarantined them instead of overwriting them. I lost nothing. Build that same caution into any rule that moves your files.

How to copy my setup

Start with three folders and three instruction files. You can add everything else later.

Starter structure
marketing/
├── growth/            # decisions: true about my business today
│   ├── CLAUDE.md      # or project instructions
│   ├── business/      # offer, pricing, plan
│   ├── config/        # voice guide, ICP, pillars, banned words
│   └── production/    # what I'm making
├── vault/             # knowledge: could change
│   ├── CLAUDE.md
│   ├── inbox/         # daily notes
│   ├── sources/       # raw, dated, never edited
│   └── wiki/          # AI-written pages
└── delivery/          # methods: works for anyone
    ├── CLAUDE.md
    ├── skills/        # or prompts/
    ├── templates/
    └── clients/
        └── client-a/  # copied from templates/

And a starter instruction file you can paste into the top folder and adapt:

CLAUDE.md / project instructions
# What this is
My marketing workspace. Three homes, routed by type,
not by where the conversation happened.

# Routing: apply in order
1. Works for any brand or client      -> delivery/
2. Decided truth about my business    -> growth/
3. Evolving knowledge or evidence     -> vault/sources/
4. Not sure                           -> vault/inbox/, then ask me
A single drop can split. Report where each piece went and why.

# Rules
- Read growth/config/voice-guide.md before writing anything.
- Never treat vault/ content as a decision.
- Never put client names in delivery/.
- No number without a source.
Want this set up for your team?

On a 30-minute call we map your team's marketing work into the three homes and pick the first workflows to build. The same setup runs my client work: Intryc doubled its AI visibility in 28 days.

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Then three prompts to get going:

  1. Sort what you have

    Here's a list of my current docs. Sort each one into growth, vault or delivery using the routing rules, and explain any you're unsure of.

  2. Write your config

    Interview me one question at a time to write growth/config/voice-guide.md and icp.md. Use only what I tell you.

  3. Capture daily

    Write today's note in vault/inbox/: what we covered, what I learned, what I decided. Tag anything that belongs in another home.

The one thing to take away

Before you file anything, ask could new evidence change this? If yes, it's knowledge. If no, it's a decision. If it would work for anyone, it's a method. Write that rule in a file the AI reads first, and you'll stop explaining your business at the start of every chat.

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Want this set up for your team?

Three homes.
set up in one call.

On a 30-minute call we map your team's marketing work into knowledge, decisions and methods, and pick the first workflows to build. You leave with a short list worth building. The same setup runs my client work: Intryc doubled its AI visibility in 28 days.

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