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The Build section covers everything you need to create production-ready agents — from defining their behavior and logic to connecting external tools and knowledge sources.

Key concepts

GoalDocsDescription
Define global prompt, instructions, and skillsAgentDesign how your agent responds and what skills it has to get things done
Create agentic, goal based conversations
with tool calling
PlaybooksGive your agent flexible reasoning to navigate open-ended conversations
Handle complex, multi-step processes — with or without AIWorkflowsDesign precise, step-by-step conversation flows with the visual builder
Add knowledge to your agentKnowledge baseUpload documents and data to ground your agent’s responses
Connect external toolsToolsEnable your agent to call APIs, integrations, functions and MCP servers
Store and manage dataVariablesUse variables to capture, store, and pass data through conversations
Manage sensitive dataSecretsSecurely store API keys and credentials for use in tools and integrations
Select agent frameworkFrameworkSelect between agentic (recommended) or conversational flow framework

Agent

Control how your agent thinks, responds and routes users:
  • Global prompt: Applied to every turn to shape how the agent responds, independent of routing or skills. This usually includes # Personality, # Goal, # Tone, and # Guardrails.
  • Instructions: Defines how the agent routes requests and decides which skills to use.

Skills

Skills control what your agent can do for users — things like checking an order status, booking a demo, processing a return, or resetting a password.
  • Playbooks: Autonomous reasoning for open-ended conversations — your agent decides how to navigate based on context, intent, and goals.
  • Workflows: Visual workflow builder for more deterministic, multi-step conversation flows with branching, conditions, and integrations.
Workflows can use playbooks & other AI-powered steps, so you can build agentic experiences with deterministic control where it matters. You can also build fully scripted interactions with scripted messages, buttons, conditions, and other non-AI steps.
This is a critical decision you’ll make when building AI agents in Voiceflow:
Use a playbook when…Use a workflow when…
Flexibility matters more than predictabilityPredictability matters more than flexibility
The conversation is open-endedThe process has strict business logic
The agent needs to reason about what to doThe steps are the same every time
There are many possible pathsThere’s one, or a few correct paths
There’s no universally correct choice — selecting a playbook or a workflow comes down to your specific use case and the needs of your business.If you’re unsure, we recommend starting with a playbook as it provides more flexibility and is easier to iterate on as you learn what your customers actually need. You can always introduce workflows later to handle specific conversations that benefit from a more structured approach.

Knowledge base

Extend your agent with external data and integrations that sync automatically:

Tools

Tools can be used in playbooks or workflows:
  • API tools: Connect to external REST APIs to fetch data or trigger actions.
  • Function tools: Write custom JavaScript logic that runs during conversations.
  • Integration tools: Pre-built connectors for Salesforce, HubSpot, Zendesk, Twilio, and more.
  • MCP tools: Use Model Context Protocol servers to extend agent capabilities.
  • System tools: Update the internal state of conversations and show native UI artifacts.

Data management

Capture and use data throughout conversations:
  • Variables: Store user inputs, API responses, and conversation state to personalize interactions.
  • Secrets: Securely manage API keys and credentials used by tools and integrations.

Next steps