Quick Start

This guide describes the target production flow for a new developer using AIWorkspace.

The current repository still contains an active project-specific implementation. During refactor, these commands may be implemented incrementally.

1. Install AIWorkspace

Install the app, CLI, and local services from the reusable core repo:

git clone <team-ai-workspace-repo> ~/Developer/ai-workspace
cd ~/Developer/ai-workspace

The target CLI entry point is:

aiw

During development, commands may still be run through Python scripts.

2. Register Or Create A Project Context Pack

aiw project register ~/Developer/client-mobile-ai-context

Or create a new one:

aiw project create it-support --display-name "IT Support" --path ~/Developer/it-support-ai-context

The context pack contains project memory and project-specific connector configuration.

3. Connect Evidence Sources

Add only the connectors this project needs:

aiw connector add mattermost --project client-mobile
aiw connector add photos --project client-mobile

For another project, the connector set may be completely different:

aiw connector add tickets --project it-support
aiw connector add calendar --project it-support

4. Detect Local Repositories

AIWorkspace should help detect local repos and associate them with projects:

aiw repo scan ~/Developer --project it-support

For projects whose source code lives on another machine, the context pack should say so explicitly in aiw.project.json.

5. Start Context Services

Start services for the active project:

aiw services start --project client-mobile
aiw services status --project client-mobile

The service manager should start only capabilities configured for that project.

6. Configure AI Clients

Generate AI client integration files on demand:

aiw agent configure opencode --project client-mobile
aiw agent configure copilot --project client-mobile
aiw mcp config --client vscode

The preferred integration path is MCP, so AI clients can request current context without copying memory into product repositories.

7. Use AIWorkspace From Any AI Tool

The AI client should call MCP with a project id:

{
  "project": "client-mobile"
}

Example tool calls:

project_current_context(project="client-mobile")
project_search_memory(project="it-support", query="printer onboarding")
communication_latest(project="client-mobile")

8. Keep Canonical Memory Clean

Project memory lives in the context pack:

<context-pack>/knowledge/

Raw evidence lives separately:

<context-pack>/inbox/

Do not treat raw captures, indexes, logs, or AI chat history as canonical memory.

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