Fabric Orchestrator

The Fabric Orchestrator is the brain of Fabric AI. It intelligently routes your requests to the right agents and tools, manages complex multi-step workflows, and learns from every interaction to get better over time.

What Makes the Orchestrator Special?

Before the Orchestrator

With the Orchestrator

Core Capabilities

1. User Intent Detection

The Orchestrator understands what you're asking for, including explicit requests:

Recognized intents:

• Explicit tool requests — "use the Jira tool", "search with GitHub"
• YouTube URLs — Automatically routes to transcript extraction
• Workspace references — "my docs", "attached files" → use RAG
• Integration triggers — "post to Slack", "send an email"
• Fabric patterns — "summarize", "extract wisdom", "analyze claims"

2. Semantic Routing

The Orchestrator uses AI embeddings to find the best executor for your task:

Why this matters:

• No need to remember which tool does what
• Works with 100+ tools without confusion
• Natural language understanding
• Respects explicit user preferences

3. Task Planning

Complex requests are automatically decomposed:

4. Priority-Based Executor Assignment

Each step is assigned the optimal executor based on capability and speed:

5. Context Flow

Each step can use outputs from previous steps:

Variable interpolation allows referencing previous step outputs:

// Step 4 can reference previous outputs
{
  message: "PRD: {{step-1.output.title}}. Tickets: {{step-3.output.ticket_ids}}"
}

6. Trust-Based Approvals

The Orchestrator learns what you approve:

7. Memory System

The Orchestrator remembers what works and what doesn't:

Positive Memory (Letta + Qdrant):

• Successful routing patterns
• Effective tool combinations
• Working prompts and parameters

Negative Memory:

• Failed approaches
• Rate-limited operations
• Error-prone patterns

New request similar to past failure:
"⚠️ Similar task failed 3 days ago due to rate limiting.
 Automatically batching operations with delays."

8. Graceful Recovery

When things go wrong, the Orchestrator handles it:

Workflow Integrations

The Orchestrator includes built-in integrations for common services—faster than MCP:

Available Integrations

Integration vs. MCP Tools

Fabric AI Tools

Built-in tools for content processing without external dependencies:

YouTube Tools

• fabric_youtube_transcript — Extract raw transcripts with optional timestamps
• fabric_analyze_youtube — Apply patterns: summarize, extract_wisdom, analyze_claims, create_keynote

Web Tools

• fabric_scrape_url — Scrape and readability-enhance web content
• fabric_analyze_webpage — Apply Fabric patterns to web content

Audio Tools

• fabric_transcribe_audio — Convert audio files to text

MCP Tool Integration

The Orchestrator can execute MCP tools directly:

Available Tools

• GitHub — Issues, PRs, repositories
• Jira — Tickets, sprints, projects
• Slack — Messages, channels
• Notion — Pages, databases
• Linear — Issues, projects
• And many more...

Tool Selection

The Orchestrator automatically selects tools:

Tool vs. Agent Delegation

Starred Preferences

Prioritize your favorite tools, servers, and agents:

How to Star

1. Go to Settings → MCP Servers or Agents
2. Click the ⭐ icon next to items you use frequently
3. Starred items get priority in routing decisions

What Starring Does

Using the Orchestrator

Starting a Conversation

1. Go to Agents → Fabric AI (Orchestrator)
2. Type your request naturally
3. The Orchestrator handles the rest

Example Requests

Simple:

"Create a PRD for user authentication"

Multi-step:

"Create a PRD for the payment feature, then generate
user stories and create them in Jira"

With context:

"Based on our Q4 roadmap, create a technical spec
for the new API gateway and post a summary to #engineering"

YouTube processing:

"Summarize this video and extract the key insights:
https://youtube.com/watch?v=..."

Web research:

"Scrape this article and create a summary with key takeaways:
https://example.com/article"

Execution Modes

Choose the right mode for your task:

Attaching Context

Improve results by attaching:

• Workspaces — Documents for RAG context
• Projects — Previous project documents
• Specific files — Upload directly

Workflow Visualization

Watch your workflow execute in real-time:

Approval Workflows

When Approvals Are Needed

The Orchestrator requests approval for:

1. High-risk operations — Delete, bulk updates
2. External actions — First-time tool usage
3. Expensive operations — Large API calls
4. Unknown patterns — New types of requests

Risk Levels

Approval Interface

Consolidated Prompts

Multiple approvals are grouped into one:

Before: 5 separate approval prompts
After:  1 consolidated prompt with all actions listed

Advanced Features

Follow-up Handling

The Orchestrator understands context:

You: "Create a PRD for auth"
Orchestrator: [Generates PRD]

You: "Actually, also include OAuth support"
Orchestrator: "Updating PRD to include OAuth..."
[Modifies existing document, not starting over]

Journey Tracking

Full context is maintained:

• Current phase of execution
• Decisions made and why
• Assumptions with confidence levels
• All artifacts generated
• Complete conversation history

Real-time Signals

Query workflow state anytime:

// Get current progress
const progress = await orchestrator.query('progress');
// { currentStep: 2, totalSteps: 5, status: 'executing' }

// Get generated artifacts
const artifacts = await orchestrator.query('artifacts');
// [{ type: 'prd', name: 'Auth PRD', status: 'complete' }]

Generalist Agent Delegation

For complex tasks requiring autonomous execution:

Next Steps