Build an AI Agent without Coding: A How to Guide

AI chatbots have evolved far beyond simple scripted responses. Today, they combine rule-based logic with powerful natural language processing (NLP) models, such as OpenAI’s GPT, to create smart, conversational assistants that can engage, support, and convert users across various platforms.

Whether you're looking to generate leads, support customers, or automate FAQs, building an AI chatbot can significantly enhance the user experience, reduce the workload for your teams, and improve both efficiency and profitability.

With Landbot, you can create an AI-powered chatbot without writing a single line of code. Our visual AI chatbot builder lets you design dynamic conversations, integrate AI models like GPT, and deploy your chatbot on both your website and WhatsApp, all from one intuitive interface.

In this guide, we’ll walk you through everything you need on how to build an AI chatbot using Landbot, from defining your goals to launching your bot live.

Define the Scope of Your AI Chatbot

Jumping straight into the building process can be tempting, but successful AI chatbots start with a defined strategy. A clear scope sets the foundation for a chatbot that not only works but performs at its best.

In this section, we’ll dive deeper into:

• How to set your chatbot’s purpose
• Establish the target audience it will serve
• Think about the type of experience it will deliver

What’s our Chatbot’s Goal?

To help you get through this, we recommend you think of your AI chatbot as a digital team member. Now reflect on its role: what job is it supposed to do? What do you expect from it?

Start by answering these questions:

• What problem am I solving for my users?
• What business goal will this chatbot support?
• What success metrics will I track? (e.g., leads captured, questions answered, conversions, managed tickets, etc.)

Here are some common goals and examples of how Landbot customers use AI chatbots to achieve them:

• Generate leads: as Choices did, you can qualify website or WhatsApp visitors, ask qualifying questions, and capture contact info. 
• Automate Support: an AI chatbot can be your greatest ally when it comes to providing assistance and answers to common questions using your own Knowledge Base. That’s exactly what FASTA did to reduce by 20% their phone and email dependency and their request resolution times, by increasing efficiency and improving customer satisfaction. 
• Boost conversions: Yes, your AI chatbot can also assist your users in choosing the right product or service according to their needs through interactive flows and AI-driven suggestions. 
• Collect feedback: Once the interaction with your prospect is over, whether they have purchased your product or not, you can trigger feedback and satisfaction surveys so they can evaluate their interaction with your brand.
• Book appointments: You can also integrate your AI chatbot with your calendar to automate the scheduling process of demos, visits, appointments, or meetings.

In short, be aware that the clearer your goal, the easier it’ll be to build your AI chatbot and measure its impact.

Understand Your Target Audience

Once you know your AI Agent's goal, the next step is to identify who it’s doing it for, which basically means knowing in depth your target audience. This will directly influence the tone of voice, the flow logic, and the type of questions. 

You might want to consider the following aspects:

• Demographics: Are your users young, busy professionals? Senior customers? First-time buyers?
• Channel habits: Are they more likely to message you on WhatsApp or visit your website?
• Language and tone: Should your chatbot be formal and professional, or casual and friendly?
• Tech comfort level: Do users expect button-based flows or prefer open-ended conversations?

In case you’re targeting multiple audiences (e.g., agencies vs. end-users), we recommend building different flows or using conditional logic to personalize the experience.

Designing an AI Chatbot (aka AI Agent)

Unlike linear bots that rely heavily on buttons and logic trees, AI agents use conversational AI (like GPT) to engage users in more natural language conversations. Instead of scripting every possible user input, you can train the AI chatbot with the knowledge it needs to understand, interpret, and respond meaningfully.

With Landbot’s AI agent capabilities, you can:

• Train the agent with your own content
• Control its personality (set tone, behavior, and limits)
• Define custom instructions for how it should handle queries and behave
• Guide key actions like lead capture or  handover

This approach is ideal if:

• You want your chatbot to sound more human and intelligent
• You expect users to type open-ended questions
• You have complex or varied content that’s hard to fit into pre-defined button flows

Plus, with Landbot, you can integrate your AI Agent with greater flows, or even with your own CRM and other tools to create an even more powerful AI agent.

Final Tip: Draft the Intent Behind the Conversation

Before building, outline what you want the AI agent to accomplish:

• What kind of questions will users ask?
• What answers should the bot provide?
• When should it collect data or take action?
• Are there topics it shouldn’t cover?

Defining this intent helps you create proper and detailed prompts and knowledge sources accordingly, so your AI agent performs the way you expect. 

Now that we have the strategy well defined, it’s time to get down to work and start creating our AI Agent!

If you still don’t have a Landbot account, it’s time to create one for free so you can follow the process described below. 

Build Your AI Agent (Step-by-Step)

If you prefer to follow the instructions by watching a video, we recommend you take a look at the instructions from Nik in the video below: 

Once you access the platform, you will find direct access to the AI Agents section. 

Select the Channel for your AI Agent

The first step is to select the channel where you will want to launch the chat. In this case, we will select ‘Web’:

Now, we will need to start setting up our AI Agent. Let’s begin by giving it a name that matches our brand and a role that fits our needs: 

We will use a hypothetical example to complete and test our AI Agent. Let’s say we are building an AI Agent for a travel company that helps businesses simplify, optimize, and enhance their corporate travel experiences, allowing them to book faster while staying on budget.

How to Write the Right Instructions for Your AI Agent

Below, we will find one of the most important steps, the ‘Instructions’. Here, you will need to indicate how your AI Agent needs to behave and operate, how it should interact with users, the style it needs to follow when answering questions, how it should handle unusual situations, and how to collect key information. 

It’s worth taking the time to write as detailed instructions as possible. 

Also, make sure you indicate what the AI Agent should say in case an error occurs (right below the instructions!). 

Adding the Right Knowledge Source to your AI Agent 

Yes, that’s right, if we want our AI Agent to answer users’ queries accurately, we need to provide it with the correct information to do so. At the left of your panel, you will see the section ‘Knowledge Source’. 

Once we click on ‘Add source’, we will be able to choose whether we want to upload a PDF or directly copy the information in the text box below to train our AI Agent. You can do whatever is more convenient, just make sure you’re adding all the details, from the products you offer, your policies, pricing, and anything that can be of interest to the user. 

How to Get Key Information from our Users with our AI Agent

Considering our AI Agent role is ‘Customer Service Agent’ and that we plan it to be helpful for our lead generation strategy as well, we need to ensure that it collects key contact information from our customers and prospects. 

In the ‘Get user information’ section, we can indicate the data we want to store and under what fields. We can also add additional fields if we need more information. In our case, we would like to ask and save details about the budget:

These fields can be used later during the conversation, whether it’s in your AI Agent (by indicating that in the instructions) or in a linear bot. 

How to Set Up the Exit Conditions in Your AI Agent 

Right below the ‘Get user information’ section we just completed, there’s the ‘Exit Conditions’ setup. 

If we want to prevent our users from getting caught in a never-ending conversational loop with our AI Agent, we need to indicate here when the conversation should stop and go back to our linear bot to end the interaction with the user. 

Let’s say the goal we aimed to achieve, which is basically getting the contact information from our prospect, plus the budget, and answering any questions he/she might have, is already accomplished. We can point this out in the ‘Exit’ box: 

In this same panel, we can configure the connection between our linear bot and our AI Agent to create a better and enhanced workflow. We will delve into the entire process in the section below. 

How to Connect an AI Agent to a Linear Bot

As we mentioned in the ‘Exit Conditions’ section, we can easily connect our AI Agent to any of our linear bots and go directly to a specific block of the workflow. 

It might seem obvious, but the first thing we need to ensure is that we have our linear bot ready to go. 

In our case, we started our bot by asking the user their name, and next, we added the ‘Jump to’ block, where we linked our AI Agent chatbot: 

Once that is done (you can even add more blocks if you wish), let’s go back to our AI Agent, under the ‘Exit Conditions’ section. There, we will need to indicate the linear bot we have to connect, in our case ‘Linear bot’, and then copy the block ID from the linear bot that we want our AI Agent to jump to, and paste it below: 

And that’s it! As of this point, make sure both bots are published, and you can start testing it. We recommend you test both from the linear bot, because therefore you will be able to see how the entire workflow works, right from the beginning. 

Testing is a very important part. Anything you find odd, or if you see the AI Agent is hallucinating or not answering the way you want it to, make sure to write better prompts and instructions tailored to your specific use case. 

You can also find more information on our help article about how to create an AI Agent, with more technical information and some extra recommendations. 

FAQs About Creating an AI Agent Without Coding

1. What is an AI agent and how does it work?

An AI agent is an intelligent virtual assistant that uses artificial intelligence to understand and respond to user messages in natural language. Unlike traditional chatbots that rely on rigid decision trees, AI agents use advanced language models (like GPT) to generate dynamic, human-like conversations. With Landbot, you can build AI agents that are trained on your business content and customized to fit your brand's tone and goals.

2. Do I need to know how to code to build an AI agent?

No, Landbot’s no-code platform allows you to build powerful AI agents without any programming skills. Using a drag-and-drop interface, you can design your agent’s logic, train it on your content, and deploy it across channels like your website or WhatsApp—all without writing a single line of code.

3. How can I train my AI agent with my business content?

You can train your AI agent in Landbot by uploading documents (like PDFs), entering custom text, or connecting your website URLs. This content forms the agent’s knowledge base, enabling it to answer user questions accurately and conversationally. You can also fine-tune its personality and behavior with custom instructions.

4. Can I connect my AI agent to WhatsApp or my website?

Yes! Landbot lets you easily deploy your AI agent on both your website and WhatsApp. This omnichannel flexibility allows you to provide real-time, AI-powered support and lead generation wherever your audience prefers to interact.

5. What’s the difference between a chatbot and an AI agent?

A chatbot typically follows a scripted flow using buttons and pre-defined logic. An AI agent, on the other hand, is designed to understand free-text input and engage in open-ended conversation using artificial intelligence. Landbot’s AI agents combine the flexibility of conversational AI with the structure of no-code logic blocks, giving you a smart assistant that’s both intuitive and powerful.

6. How long does it take to build an AI agent?

With Landbot, you can build a basic AI agent in under an hour. More advanced agents—with custom logic, integrations, or extensive knowledge bases—may take longer. But thanks to the visual builder and AI tools, the process is still significantly faster than developing from scratch.

7. How much does it cost to build an AI agent with Landbot?

Landbot offers flexible pricing, including a free plan to get started. Paid plans give you access to premium features such as AI agents, WhatsApp integration, and advanced workflows. Compared to building a custom AI solution from the ground up, Landbot offers a cost-effective way to deploy smart, scalable agents for your business.

8. Can I integrate my AI agent with tools like HubSpot or Google Sheets?

Yes, Landbot supports integrations with CRMs, databases, spreadsheets, and other tools. This means your AI agent can collect data, trigger actions, and update records in real time, helping you automate more than just conversation.

9. Can my AI agent transfer the conversation to a human?

Definitely. You can configure your Landbot AI agent to automatically hand off the conversation to a live agent when certain conditions are met, such as when it doesn’t understand a request or when the user asks to speak to a person. This ensures a seamless customer experience.

10. How can I test and improve my AI agent?

After launching your AI agent, Landbot gives you access to usage analytics, performance metrics, and user feedback. You can review common questions, drop-off points, and conversation outcomes to fine-tune the agent’s flow and knowledge. Regular testing and iteration are key to creating an effective, high-performing AI experience.