Knowledge & data
AI knowledge system for your knowledge
Your knowledge is your business – and it lies scattered: the method in your head, the exercises in five different folders, the good phrasings in old emails, the session notes on paper. With every new offer you gather together what you've long had.
AI knowledge system
01AI knowledge system
For coaches and consultants the knowledge is the asset – which is why a system that structures it and lets it work along resonates especially strongly here: method, exercises, programmes, content ideas and session learnings live in one place, ordered so that AI can search, summarise, take notes and run routines in it. You ask "which exercise fits with decision blocks?" and get YOUR exercises with a source, not internet wisdom. The voice note after the session files itself and, in passing, becomes a content idea. In the morning the prep for the day is ready. I work this way myself – a large part of my daily business now runs through exactly such a system, with AI as a colleague inside it.
Up front: I won't promise a "second brain in one go" – the entry point is one area, say your exercise library, otherwise it fails on upkeep. And the most important thing in coaching: anything personal about clients stays out or gets its own strict data-protection concept – the system holds your method, not your clients' stories. The AI never writes unchecked.
02Demo
The knowledge system of the fictional coach “Anna Baur” – on the left the order in which method, programmes and content live, on the right three everyday moments with it. Click through and watch where it lights up in the tree.
The architecture behind it has two layers: at the bottom the vault – structured folders and notes that belong to the business. Above it the AI layer with documented rules: it reads only at first, then writes with approval, and sensitive areas stay locked. Calendar and tools dock on, routines run within clear limits.
The most honest proof of this model: this website came about exactly this way – I work in such a system myself every day, with AI as an employee inside it.
03How it works
- 01
Take stock: where does your knowledge live?
Head, folders, course booklets, email phrasings, session notes. Plus: what do you keep gathering together, and what would be lost if your laptop broke tomorrow?
- 02
Build the structure, small and documented
A clear ordering system: method, exercises, programmes, content, learnings. With simple rules – and the firmly drawn-in line that anything personal about clients doesn't belong in it.
- 03
Fill one area first
Usually the exercise and method library: what do you have, when do you use it, what's your experience with it? Existing material moves in curated, not copied.
- 04
Connect the AI: reading first, then writing
First the AI only answers questions from your knowledge – with a source. Once that holds, writing with sign-off is added: filing session notes, content drafts, programme building blocks. Rights and limits are documented.
- 05
Add routines – step by step
Session prep in the morning, a content pipeline from session learnings, follow-ups on open inquiries: the AI takes over defined tasks within clear limits – each one only once the previous one runs.
04Stages
The entry point is Tier 1, the team knowledge base – for solo coaches, the method library is the right start.
Entry: the queryable knowledge
One area – your exercises and method – is structured and made queryable. In seconds you find what you'd otherwise gather across five folders.
Extended: the AI works along
Filing session notes, content drafts, programme building blocks – the AI writes along in the system, every change with sign-off, anything personal about clients stays out.
Full build: routines run
Session prep, content pipeline, follow-ups – defined routines run on their own within clear limits. The knowledge system becomes your back office.
05Technical implementation
- The knowledge layer is yours: a Markdown vault (e.g. Obsidian), Notion or a comparable system – content without vendor lock-in.
- The AI layer is an assistant with access to the vault (e.g. Claude Code as the agentic layer) – with documented rules: which areas, which rights, which routines.
- Hard line to client data: anything personal, session content tied to real people, stays out or gets a strict data-protection concept.
- Tiered rights logic: reading first, writing only in defined areas with sign-off.
- Upkeep routines are set up alongside – the two-minute note after the session is the engine, without which the system ages.
- Typical content: method and frameworks, exercise library, programme flows, content ideas, anonymised learnings.
for context · This shows how something like this usually gets built – not how it has to be built for you. What actually fits is worked out in the project: around your existing setup, your team, and what stays easy to maintain.