Dokumentation

AI Agents Overview

Understanding the different types of AI agents in Fabric and when to use each one.

Fabric AI includes multiple specialized agents, each designed for specific tasks. This guide helps you understand which agent to use and how they work together.

What is an Agent?

An AI agent is an autonomous system that can:

  • Understand — Interpret your requests and context
  • Plan — Break down complex tasks into steps
  • Execute — Perform actions like generating documents or calling APIs
  • Learn — Improve from feedback and past executions

Unlike simple chatbots, agents can take actions, use tools, and complete multi-step workflows.

Agent Types

Fabric provides several types of agents:

┌─────────────────────────────────────────────────────────────────┐
│                        Fabric AI Agents                          │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  ┌──────────────────────────────────────────────────────────┐   │
│  │                    FABRIC ORCHESTRATOR                    │   │
│  │         Routes tasks to the right specialized agent       │   │
│  └──────────────────────────────────────────────────────────┘   │
│                              │                                   │
│          ┌───────────────────┼───────────────────┐              │
│          │                   │                   │              │
│          ▼                   ▼                   ▼              │
│  ┌──────────────┐    ┌──────────────┐    ┌──────────────┐      │
│  │   Document   │    │     CUGA     │    │    Custom    │      │
│  │  Generator   │    │ (General AI) │    │    Agents    │      │
│  └──────────────┘    └──────────────┘    └──────────────┘      │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘

Fabric Orchestrator

The intelligent coordinator that routes your requests to the right agent or tool.

Best for:

  • Complex multi-step tasks
  • Tasks requiring multiple tools
  • When you're not sure which agent to use
  • Workflow automation

Capabilities:

  • Semantic routing to find the best executor
  • Task decomposition and planning
  • MCP tool execution
  • Agent delegation via A2A protocol
  • Trust-based approval workflows
  • Memory and learning from past executions

Learn more about the Orchestrator →

Document Generator

A specialized agent for creating structured documents.

Best for:

  • PRDs and product documentation
  • Technical specifications
  • Architecture documents
  • User stories and acceptance criteria
  • API documentation

Capabilities:

  • Multiple document templates
  • RAG context integration
  • Real-time streaming with diff highlighting
  • Confirm/reject workflow for changes
  • Export to PDF, DOCX, Markdown

Learn more about Document Generation →

CUGA (Configurable Generalist Agent)

A powerful generalist agent for complex automation.

Best for:

  • Browser automation and web scraping
  • Complex API orchestration
  • Multi-step workflows
  • Tasks requiring code execution
  • Autonomous task completion

Capabilities:

  • Full Playwright browser automation
  • Sandboxed code execution
  • Screenshot analysis
  • Human-in-the-loop approvals
  • Memory system for learning

Learn more about CUGA →

Custom Agents

Create your own agents for specific workflows.

Best for:

  • Organization-specific processes
  • Unique document types
  • Custom integrations
  • Specialized domains

Capabilities:

  • Custom prompts and instructions
  • Configurable MCP tools
  • Custom approval workflows
  • Template-based creation

Learn how to create custom agents →

Choosing the Right Agent

TaskRecommended AgentWhy
Generate a PRDDocument GeneratorOptimized for structured documents
Create 10 Jira tickets from PRDOrchestratorMulti-step with MCP tools
Scrape competitor websitesCUGABrowser automation needed
Generate weekly reportCustom AgentOrganization-specific format
"Just help me with X"OrchestratorRoutes automatically

How Agents Work

1. Request Understanding

When you send a message:

User: "Create a PRD for user authentication with OAuth support"


┌─────────────────────────────────────────────────────────┐
│                  Request Analysis                        │
│  • Task type: Document generation                        │
│  • Document type: PRD                                    │
│  • Key topics: Authentication, OAuth                     │
│  • Complexity: Medium                                    │
└─────────────────────────────────────────────────────────┘

2. Context Retrieval

The agent gathers relevant context:

┌─────────────────────────────────────────────────────────┐
│                  Context Sources                         │
│  • Project workspace documents                           │
│  • Previous project documents                            │
│  • Organization knowledge base                           │
│  • Past similar requests                                 │
└─────────────────────────────────────────────────────────┘

3. Planning

For complex tasks, the agent creates a plan:

┌─────────────────────────────────────────────────────────┐
│                    Execution Plan                        │
│  Step 1: Retrieve auth-related documents                 │
│  Step 2: Generate PRD outline                            │
│  Step 3: Expand each section                             │
│  Step 4: Add acceptance criteria                         │
│  Step 5: Review and format                               │
└─────────────────────────────────────────────────────────┘

4. Execution

The agent executes each step:

  • AI generation — Call LLM to generate content
  • Tool calls — Execute MCP tools if needed
  • Validation — Check output quality
  • Streaming — Send updates to user in real-time

5. Learning

After completion:

  • Record what worked and what didn't
  • Update memory for future requests
  • Improve routing accuracy

Agent Communication

A2A Protocol

Agents communicate using the Agent-to-Agent (A2A) protocol:

Orchestrator                    Document Generator
     │                                  │
     │─── Discover capabilities ───────>│
     │<── Agent manifest ───────────────│
     │                                  │
     │─── Task: Generate PRD ──────────>│
     │<── SSE: Progress updates ────────│
     │<── SSE: Content chunks ──────────│
     │<── Result: Complete document ────│
     │                                  │

AG-UI Protocol

Agents communicate with the UI using the AG-UI protocol:

  • State deltas — Real-time state updates
  • Tool calls — Visibility into agent actions
  • Streaming — Token-by-token generation
  • Approvals — Human-in-the-loop requests

Multi-Agent Workflows

The Orchestrator can coordinate multiple agents:

Request: "Create a PRD, then generate Jira stories"


        ┌───────────────────┐
        │   Orchestrator    │
        │   (Coordinator)   │
        └───────────────────┘

        ┌───────────┴───────────┐
        │                       │
        ▼                       ▼
┌──────────────┐       ┌──────────────┐
│  Document    │       │   Jira MCP   │
│  Generator   │──────>│     Tools    │
└──────────────┘       └──────────────┘
   (Step 1)               (Step 2)


                    Stories created in Jira

Agent Configuration

Model Selection

Choose which AI model the agent uses:

  • GPT-4 — Complex reasoning, code generation
  • Claude 3.5 Sonnet — Long documents, nuanced content
  • GPT-3.5 Turbo — Fast, cost-effective

Temperature

Control output creativity:

  • 0.0 — Deterministic, consistent
  • 0.7 — Balanced (default)
  • 1.0 — Creative, varied

System Prompts

Customize agent behavior with prompts from your library.

MCP Tools

Enable specific tools for the agent:

  • GitHub, Jira, Slack integrations
  • Custom API endpoints
  • Database queries

Next Steps