Supercharge Your Customer Support: Build a Zendesk AI Agent in 10 Minutes with Agents.do

Customer support teams are on the front lines, dealing with a relentless flood of inquiries. From simple "Where is my order?" questions to complex technical issues, the volume can be overwhelming. While chatbots were a step forward, they often fall short, lacking the autonomy to resolve issues without human intervention.

What if you could deploy a digital team member that not only understands customer requests but can also access your tools, analyze data, and take decisive action—all on its own?

Welcome to the world of autonomous AI agents. This post will show you how to build and deploy a powerful, Zendesk-integrated customer support agent using the Agents.do platform in just a few minutes. Let's get started.

Beyond Chatbots: The Power of Autonomous Agents

First, let's clarify what we mean by "autonomous AI agent." Unlike a traditional chatbot that follows a rigid, predefined script, an autonomous agent, or digital worker, is designed to:

• Understand High-Level Objectives: You don't program a step-by-step workflow; you give it a goal, like "resolve common customer issues efficiently."
• Operate Independently: It can perceive its environment (e.g., a new ticket in Zendesk), reason about the best course of action (e.g., check order status in Shopify), and execute tasks (e.g., reply to the customer and resolve the ticket).
• Integrate Seamlessly: It connects to your existing business systems—CRMs, e-commerce platforms, knowledge bases—to gather information and perform actions, just like a human agent would.

This level of autonomy is a game-changer for customer support, promising to automate entire workflows, not just initial conversations.

Introducing Agents.do: Your AI Workforce as Code

Agents.do is a developer-first platform for building, deploying, and managing these autonomous AI agents. Our core philosophy is "Business-as-Code." Instead of relying on complex UIs or rigid "no-code" builders, we empower developers to define their AI workforce using a simple, declarative SDK.

This approach offers significant advantages:

• Version Control: Your agent's logic, skills, and configuration are stored in code, manageable with tools like Git.
• Scalability: Easily deploy, duplicate, or modify agents as your business needs evolve.
• Transparency: The agent's capabilities are clearly defined in a single, readable file.
• Robustness: Leverage the power of code to build sophisticated and reliable digital workers.

Let's Build "Amy," Our Customer Support Agent

Now for the fun part. We'll define a customer support agent named Amy. Her primary objective is to handle incoming inquiries via Zendesk, resolve common issues, and escalate complex ones.

The Agent's Profile: Defining the "Who" and "Why"

Using the Agents.do SDK, we start by defining the agent's core identity and purpose. This is where we set the high-level objectives that will guide all its future actions.

import { Agent } from 'agents.do'

// Create a customer support agent
const customerSupportAgent = Agent({
  name: 'Amy',
  role: 'Customer Support Agent',
  objective: 'Handles customer inquiries and resolves common issues',
  keyResults: ['responseTime', 'resolutionTime', 'escalationRate', 'customerSatisfaction'],
  url: 'https://amy.do',
  // ... more properties to come
})

Here, we've given Amy a name, a role, and a clear objective. We've also defined the keyResults we'll use to measure her performance.

The Code in Action: The Complete Agent Blueprint

Let's put it all together. Here is the complete code to define Amy. It’s declarative, easy to read, and captures the entire business process in a single block of code.

import { Agent } from 'agents.do'

// Create a customer support agent
const customerSupportAgent = Agent({
  name: 'Amy',
  role: 'Customer Support Agent',
  objective: 'Handles customer inquiries and resolves common issues',
  keyResults: ['responseTime', 'resolutionTime', 'escalationRate', 'customerSatisfaction'],
  url: 'https://amy.do',
  integrations: ['chat', 'slack', 'email', 'zendesk', 'shopify'],
  triggers: ['onTicketCreated', 'onMessageReceived'],
  searches: ['FAQs', 'Tickets', 'Orders', 'Products', 'Customers'],
  actions: ['sendMessage', 'updateOrder', 'refundOrder', 'resolveTicket', 'escalateTicket'],
})

Let's break down the new properties:

• integrations: This is Amy's toolkit. By listing 'zendesk' and 'shopify', we grant her the ability to interact with those platforms' APIs.
• triggers: This tells Amy when to wake up and get to work. 'onTicketCreated' in Zendesk will activate her.
• searches: This is her knowledge base. She can look up information in 'FAQs', past 'Tickets', and 'Orders' to understand the context of an inquiry.
• actions: These are the verbs—the tasks she is authorized to perform. She can 'sendMessage' to a customer, 'resolveTicket' in Zendesk, or even 'refundOrder' through Shopify if the conditions are right.

From Code to Deployment: The Agents.do Platform

Once you've written this definition, the Agents.do platform takes over. You commit the code, and our agent orchestration engine brings Amy to life. The platform manages her entire lifecycle, monitors her performance against the keyResults you defined, and provides detailed logs and observability so you always know what your digital workforce is doing.

When a customer creates a new ticket in Zendesk, the 'onTicketCreated' trigger fires. The platform activates Amy, providing her with the ticket's context. She can then use her searches and actions to autonomously work towards her objective, whether that means looking up an order in Shopify and sending a status update or escalating a complex bug report to a human agent via Slack.

Ready to Deploy Your First Digital Worker?

In less than 30 lines of code, we've defined a sophisticated, autonomous AI agent capable of handling real-world customer support tasks. This "Business-as-Code" approach makes building an AI workforce faster, more scalable, and more powerful than ever before.

Imagine deploying agents for sales development, data entry, market research, and more—all managed with the same developer-centric workflow.

Ready to supercharge your business operations? Get started with Agents.do today and build your first autonomous agent.

Frequently Asked Questions (FAQ)

Q: What are autonomous AI agents?
A: Autonomous AI agents, or digital workers, are AI-powered entities designed to understand objectives, perform complex tasks, and operate independently across various digital systems to achieve specific business goals.

Q: How does the Agents.do platform work?
A: Agents.do provides a developer-first, 'Business-as-Code' framework. You define an agent's role, objectives, and integrations using our SDK. The platform then orchestrates the agent's actions, manages its lifecycle, and provides observability.

Q: Is Agents.do a no-code platform?
A: No, Agents.do is a low-code, developer-centric platform. It empowers developers to codify business logic and create robust, scalable, and version-controlled AI agents using simple APIs and SDKs.