# Workspace vs Context Pack

AIWorkspace separates the installed product, user-local settings, and project memory.

This distinction keeps the system simple, shareable, and safe for unrelated projects such as `client-mobile` and `it-support`.

## Three-Layer Model

```text
AIWorkspace Core
  reusable installed product

User/App Registry
  local machine settings and registered context packs

Project Context Packs
  one isolated context package per project, client, or workstream
```

## AIWorkspace Core

The core is the reusable product. It can be shared with a team.

Typical location during development:

```text
~/Developer/ai-workspace
```

It contains:

```text
apps/
scripts/
connectors/
templates/
docs/
examples/
```

It should not contain real project memory, captured messages, customer names, ticket details, or private prompts.

## User/App Registry

The registry is local to one developer machine. It records which context packs are available and which project is active.

On macOS, the target location is:

```text
~/Library/Application Support/AIWorkspace/
```

Example registry:

```json
{
  "schema": "aiworkspace.projects.v1",
  "default_project": "client-mobile",
  "projects": [
    {
      "id": "client-mobile",
      "context_path": "/Users/david/Developer/client-mobile-ai-context"
    },
    {
      "id": "it-support",
      "context_path": "/Users/david/Developer/it-support-ai-context"
    }
  ]
}
```

The registry is not intended for Git.

## Project Context Pack

A context pack is the portable project-specific unit. It may be a private repo, a team-shared repo, or a local folder.

Example:

```text
client-mobile-ai-context/
  aiw.project.json
  knowledge/
  inbox/
  connectors/
  agents/
  prompts/
```

Each context pack owns its own:

- canonical memory;
- raw evidence;
- connector definitions;
- people/channel/system maps;
- prompts and agent instructions specific to that project.

## Why Not Store Everything In One Workspace Repo?

One developer can work on unrelated projects. A single monolithic workspace can accidentally mix:

- channels from different organizations;
- people maps from unrelated clients;
- raw evidence with different privacy rules;
- prompts that only make sense for one domain;
- AI behavior learned from one project but harmful in another.

Context packs prevent this by making project boundaries explicit.

## Optional Product Repository Binding

Product repositories should stay clean by default. If useful, a repo can contain a small optional binding file:

```text
.aiworkspace.json
```

Example:

```json
{
  "project": "client-mobile",
  "context_path": "/Users/david/Developer/client-mobile-ai-context"
}
```

This file should point to context. It should not contain memory, secrets, or raw evidence.