# Getting Started

AI Workspace is a local, profile-based context system for AI-assisted work. It keeps project memory, raw evidence, local services, and AI client integrations organized without making any single AI tool the source of truth.

## Core Idea

Use the workspace as a companion repo beside your real project or client work:

```text
implementation repo / corporate tools / chat evidence
        ↓
AI Workspace inbox and memory curation
        ↓
human-readable project knowledge
        ↓
local index and MCP context server
        ↓
OpenCode / Claude Code / Copilot / other AI clients
```

## First Run

From the repository root:

```bash
python3 scripts/aiw/services.py doctor --profile fidelity
python3 scripts/aiw/services.py status --profile fidelity
python3 scripts/aiw/indexer.py build --profile fidelity
```

The `fidelity` profile is the first real project profile in this repo. New projects should follow the same shape but keep their own profile configuration and project memory isolated.

Create a new isolated profile with:

```bash
python3 scripts/aiw/profile.py create my-project --display-name "My Project"
python3 scripts/aiw/profile.py doctor --profile my-project
```

## Daily Use

1. Open the project knowledge vault in Obsidian or your Markdown editor.
2. Start only the local services needed for the profile.
3. Capture raw evidence into the profile inbox.
4. Promote useful, verified facts into canonical Markdown.
5. Let AI clients query context through MCP or direct file reads.

## Key Rules

- Canonical project memory is Markdown, not chat history or vector storage.
- Inboxes contain evidence, not promoted memory.
- Indexes are derived and rebuildable.
- MCP is read-only by default.
- Secrets belong in ignored local `.env` files.

## Next Reading

- [Architecture](architecture.md)
- [Profiles](profiles.md)
- [Memory Model](memory-model.md)
- [MCP](mcp.md)
- [Services](services.md)
- [Security and Privacy](security-and-privacy.md)