122 lines
2.8 KiB
Markdown
122 lines
2.8 KiB
Markdown
# Quick Start
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This guide describes the target production flow for a new developer using AIWorkspace.
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The current repository still contains an active project-specific implementation. During refactor, these commands may be implemented incrementally.
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## 1. Install AIWorkspace
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Install the app, CLI, and local services from the reusable core repo:
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```bash
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git clone <team-ai-workspace-repo> ~/Developer/ai-workspace
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cd ~/Developer/ai-workspace
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```
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The target CLI entry point is:
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```bash
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aiw
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```
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During development, commands may still be run through Python scripts.
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## 2. Register Or Create A Project Context Pack
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Register an existing context pack:
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```bash
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aiw project register ~/Developer/client-mobile-ai-context
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```
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Or create a new one:
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```bash
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aiw project create it-support --display-name "IT Support" --path ~/Developer/it-support-ai-context
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```
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The context pack contains project memory and project-specific connector configuration.
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## 3. Connect Evidence Sources
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Add only the connectors this project needs:
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```bash
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aiw connector add mattermost --project client-mobile
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aiw connector add photos --project client-mobile
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```
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For another project, the connector set may be completely different:
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```bash
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aiw connector add tickets --project it-support
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aiw connector add calendar --project it-support
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```
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## 4. Detect Local Repositories
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AIWorkspace should help detect local repos and associate them with projects:
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```bash
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aiw repo scan ~/Developer --project it-support
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```
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For projects whose source code lives on another machine, the context pack should say so explicitly in `aiw.project.json`.
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## 5. Start Context Services
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Start services for the active project:
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```bash
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aiw services start --project client-mobile
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aiw services status --project client-mobile
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```
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The service manager should start only capabilities configured for that project.
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## 6. Configure AI Clients
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Generate AI client integration files on demand:
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```bash
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aiw agent configure opencode --project client-mobile
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aiw agent configure copilot --project client-mobile
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aiw mcp config --client vscode
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```
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The preferred integration path is MCP, so AI clients can request current context without copying memory into product repositories.
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## 7. Use AIWorkspace From Any AI Tool
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The AI client should call MCP with a project id:
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```json
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{
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"project": "client-mobile"
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}
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```
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Example tool calls:
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```text
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project_current_context(project="client-mobile")
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project_search_memory(project="it-support", query="printer onboarding")
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communication_latest(project="client-mobile")
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```
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## 8. Keep Canonical Memory Clean
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Project memory lives in the context pack:
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```text
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<context-pack>/knowledge/
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```
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Raw evidence lives separately:
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```text
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<context-pack>/inbox/
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```
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Do not treat raw captures, indexes, logs, or AI chat history as canonical memory.
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