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Create Your First Agent

In this tutorial, you'll deploy your first AI agent from a template. The whole process typically takes just a couple of minutes -- the platform handles provisioning, configuration, and deployment for you.

Prerequisites​

Steps​

1. Navigate to the Agents page​

Agents page showing your deployed agents with their roles and channel tags

Agents page showing your deployed agents with their roles and channel tags

In the sidebar, click Agents. If you haven't created any agents yet, you'll see the Agent Catalog -- a gallery of pre-built agent templates.

2. Browse the template catalog​

The catalog offers 10 agent templates, each designed for a specific role:

TemplateWhat it does
Sales Dev RepProspect outreach, lead qualification, pipeline management
Content MarketingBlog posts, social media, content calendars
DevOps EngineerInfrastructure, CI/CD, monitoring and alerting
Customer SuccessClient onboarding, check-ins, churn prevention
HR CoordinatorHiring workflows, onboarding, policy Q&A
Growth MarketingCampaign strategy, funnel analysis, A/B testing
Project ManagerSprint planning, status tracking, team coordination
Personal AssistantSchedule management, task reminders, day planning
Research AssistantDeep research, summarization, competitive analysis
DeveloperCode review, debugging, technical documentation

3. Select the Personal Assistant template​

For this tutorial, pick Personal Assistant. This agent manages schedules, tasks, and reminders -- a good starting point because you can interact with it immediately without any domain-specific setup.

Click the template card to select it.

4. Name your agent​

Create-agent form opened from the Agents page

Create-agent form opened from the Agents page

The platform auto-generates a human name for your agent (e.g., "Toby" or "Mika"). You can keep this name or type a custom one. The name is how you'll refer to the agent in conversations and task assignments.

5. Create the agent​

Click Create. Behind the scenes, the platform:

  1. Provisions the agent's environment and copies the template configuration (tools, procedures, and skills).
  2. Sets up the agent's memory system and knowledge base.
  3. Starts the agent service.

6. Wait for the agent to start​

The agent card shows a status indicator. Wait for it to turn green with the label Running. This typically takes 15-30 seconds as the container initializes.

info

The first deploy can take slightly longer than subsequent starts because the container image needs to be pulled. After that, restarts are faster.

7. Understand what was created​

Your agent now has its own workspace on the platform containing:

  • Config -- the agent's personality, system prompts, and behavior settings.
  • Tools -- Python functions the agent can call (file operations, web search, calendar access, etc.).
  • Procedures -- step-by-step workflows the agent follows for specific tasks.
  • Skills -- higher-level capabilities composed from tools and procedures.
  • Memory -- the agent's working memory and long-term knowledge store.

The agent runs as a containerized service and communicates with the platform via API. It has its own cognitive architecture -- a reasoning loop that plans, acts, and reflects rather than just generating text.

What you've done​

  • Opened the Agent Catalog and reviewed the available templates
  • Created a Personal Assistant agent from a template
  • Watched the platform provision and deploy the agent
  • Confirmed the agent is running

Next steps​

Your agent is live. Head to Chat with Your Agent to start a conversation.

See also