Step-by-Step Walkthrough of Developing an Agentic AI Bot

This guide walks you through the process of building an Agentic AI Bot—from creating the agent to testing and refining its behavior.

Step 1: Create a New Agent

Create a new Agent from the Agentic AI dashboard and assign a meaningful name based on its purpose.

For example, if the bot is designed to collect document feedback, choose a name that clearly reflects its functionality.

Step 2: Configure the Agent

Open the newly created agent and configure its core settings.

During configuration, define:

Agent Type – Choose between a Classic Agent or an Authentication Agent based on your use case.

Language Model – Select the model that best fits your performance and cost requirements.

System Prompt – Define the agent's role, behavior, and responsibilities.

Actions – Configure the actions the agent can perform.

Step 3: Define the System Prompt

The System Prompt establishes the agent's behavior and responsibilities throughout the conversation.

Keep the prompt:

Focused on the agent's primary responsibility.

Short and easy to understand.

Free from unnecessary business logic or implementation details.

Only include instructions that should apply to every user interaction.

Step 4: Create Actions

Actions define what the agent can do beyond generating responses.

When creating an action:

Use a descriptive, action-oriented name.

Clearly describe when the action should be executed.

Avoid exposing backend implementation details within the action description.

Each action should represent a single responsibility, making it easier for the agent to determine when it should be invoked.

Step 5: Configure Action Parameters

Define the information required for the action to execute successfully.

Follow these guidelines:

Capture only the parameters that are required.

Keep parameter names meaningful and consistent.

Use concise descriptions that clearly explain the expected value.

Avoid capturing values that can be generated programmatically, such as timestamps.

Simple parameter definitions improve extraction accuracy and reduce ambiguity.

 

Step 6: Implement the Code Executor

The Code Executor performs the business logic associated with an action.

A typical implementation includes:

Reading the captured parameters.

Validating mandatory inputs.

Calling external APIs or backend services.

Processing the response.

Returning the appropriate result to the agent or directly to the user.

The business logic should remain within the Code Executor, while the System Prompt focuses only on defining the agent's behavior.

Step 7: Integrate External Services

Connect the agent with external systems required to complete user requests.

Common integrations include:

REST APIs

Databases

Google Sheets

Enterprise applications

Third-party services

Ensure that all integrations include proper validation, logging, and error handling to improve reliability.

Step 8: Test the End-to-End Flow

After implementation, validate the complete user journey.

Verify that:

The correct action is selected.

Parameters are captured accurately.

API integrations return the expected response.

The user receives the correct output.

Testing helps identify prompt improvements and ensures that the agent behaves consistently across different scenarios.

Step 9: Refine the Conversation Experience

Based on testing results, optimize the overall user experience.

Consider refining:

Welcome messages

Confirmation prompts

Response clarity

Parameter collection flow

Error messages

Small improvements to the conversation design often have a significant impact on usability.

Step 10: Debug and Optimize

If the agent behaves unexpectedly:

Review the System Prompt for conflicting instructions.

Verify that action descriptions are clear.

Validate parameter definitions.

Confirm that backend integrations return the expected data.

Test individual actions before validating the complete workflow.

Iteratively refining prompts, actions, and integrations helps improve the agent's consistency and overall performance.

Development Workflow

Create Agent
      ↓
Configure Agent
      ↓
Write System Prompt
      ↓
Create Actions
      ↓
Define Parameters
      ↓
Implement Code Executor
      ↓
Integrate External Services
      ↓
Test the Bot
      ↓
Refine & Optimize

Following this structured workflow helps create Agentic AI Bots that are easier to maintain, more reliable, and capable of delivering consistent, high-quality user experiences.