LiveAI
Productivity (Intermediate)

A knowledge base that AI can actually read

Knowledge walks out the door with employees, documentation sits untouched, and AI doesn't know your project context. Here's how to build a knowledge base in 3 stages — with AI as its reader.

12 min read Intermediate Team leads, managers, knowledge workers
✓ A working knowledge base where AI answers with full project context
сценарий

Sound familiar?

Knowledge walks out the door with an employee — and you start explaining everything from scratch

Documentation lives in Confluence, but nobody reads or updates it

Tried Obsidian — without daily discipline, the system falls apart in a month

AI doesn't know your project — you copy-paste context into chat every time

Знакомая картина — разберём, что с этим делать ниже.

A different view on knowledge bases

A knowledge base works when someone reads it. Make that someone — AI

The classic problem with knowledge bases is that they require discipline. You need to update regularly, structure carefully, keep things current. After a month, enthusiasm fades and the base turns into an archive nobody visits.

Obsidian, Notion, Confluence — great tools, but they share the same problem: a knowledge base is only as useful as often it gets read. If nobody reads the docs, it doesn't matter how well they're organized.

In LiveAI, the reader is AI. Write information in a notebook → enable context → AI sees the contents with every request. No need to maintain perfect structure — just write it down. AI will figure it out.

How it works

LiveAI notebooks are sections of your knowledge base. AI sees the contents automatically and responds with full context.

Notebooks = knowledge base sections. One notebook per project or topic. AI sees contents with context enabled

AI reads the base for you. Ask a question — AI answers based on what's written. No searching for the right document

Switch context in one click. Project A, Project B, Onboarding — different notebooks, different context for AI

Stage 1: Collect

1

Create notebooks by project or topic

Each notebook is a section of your knowledge base. Start with 2-3 key projects.

  • Notebook 'Project: CRM' — product description, key decisions, contacts
  • Notebook 'Onboarding' — what new hires need to know
  • Notebook 'Processes' — how we work, which tools we use
Don't try to write everything at once. Start with what you explain most often — that's your key knowledge.
2

Write down key information

Write in any form you like. No tags, links, or special formatting needed.

  • 'We chose CRM system X because...' — key decisions
  • 'Main client is Company X, their requirements are...' — context
  • 'When a deadline is at risk — check this first...' — work procedures
Write the way you'd explain to a colleague. AI understands free text, lists, even chaotic notes.

Stage 2: Use

1

Ask questions — AI sees the base

Enable notebook context and ask away. AI answers based on what's written — not general knowledge.

  • 'Why did we choose this particular CRM?' — AI finds the answer in notes
  • 'What's the process for launching a new project?' — AI sees the procedure
  • 'Tell me about Client X's requirements' — AI knows the context
This is the key moment: instead of 'search Confluence' — 'ask AI'. The answer is based on your records.
2

Example: new team member

A new person joins the team. Instead of 3 days of explanations — AI answers their questions using the 'Onboarding' notebook.

  • 'What tools do we use?' — AI lists them from notes
  • 'How does document approval work here?' — AI explains, knowing your processes
  • 'Who's responsible for product launches?' — AI finds the contact in records
Write down a process once — and every new hire gets answers without pulling you away from work.

Stage 3: Grow

1

Add work results back to the base

The knowledge base grows naturally: every decision, every piece of feedback, every result becomes new context for AI.

  • Made a decision in a meeting? Write it down — AI will see it
  • Got client feedback? Add it — context gets more precise
  • Found a bug fix? Record it — next time AI will suggest it
This is the key difference from Confluence: here, records actually get used — AI references them with every request.
2

Switch between projects

Each project has its own notebook. Switch — and AI works in the new context.

Over time, each notebook accumulates more context. AI becomes more useful — with no extra effort.

Switching contexts

Different projects — different notebooks. Switch the notebook — switch the context. AI sees only the relevant knowledge.

Project: CRM

Product description, decisions, Client X contacts, work procedures. AI answers in this project's context.

Project: Mobile App

Different team, different stack, different clients. Switch — and AI works with this context.

What an AI knowledge base gives you

Time saved

New hires get answers in minutes, not days. No need to interrupt colleagues.

Knowledge doesn't leave

Key employee left? Their knowledge stays in the notebook — AI still answers.

Growing context

Every entry makes AI more useful. The knowledge base works for you — without daily discipline.

FAQ

Build a knowledge base that AI can read

Write key knowledge into notebooks, enable context — and AI starts answering with your project in mind. No setup, no plugins.

Related content

Guidesmart-notes-ai FeaturesAI Context Comparisonvs Obsidian SolutionsManagers