Building AI Agents: How to Get Started

Curious about AI agents but not sure where to begin? Wondering how entrepreneurs and marketers are using them to save time and scale operations?

In this article, you'll discover a beginner-friendly framework for building and deploying AI agents—along with practical tips and tools to help you get results faster and more efficiently in your business.

What Are AI Agents and Why Do They Matter?

According to Sandy Carter, futurist and chief operating officer at Unstoppable Domains, an AI agent is essentially an algorithm that can gather information and make a decision.

This behavior differentiates agents from chatbots and generative AI tools like ChatGPT, which typically receive a question and provide an answer. 

AI agents go a step further, automating repetitive tasks, answering questions on behalf of your business, and even making some decisions based on your brand's preferences and guidelines.

The potential upsides for businesses that embrace AI agents are significant. For example, you can strengthen your brand and make your customer experience more engaging.

Pizza My Heart, a popular pizza chain in Silicon Valley, styled its AI agent as “Jimmy the Surfer” to match the brand's advertising character. The agent maintains the surfer personality, creating brand continuity throughout the customer interaction.

Consumers text the agent, which can recommend pizzas, process orders and delivery requests, and even follow up afterward to ask about customer satisfaction.

AI agents can also simultaneously reduce the workload on human staff while improving the overall customer experience—a win-win scenario that's particularly appealing to businesses with high customer service demands.

At Unstoppable Domains, Carter's team implemented an AI agent to handle customer support inquiries. Their agent now answers approximately 30% of customer questions, and remarkably, this automation led to a 10-point increase in customer satisfaction scores.

Tools to Build Your First AI Agent: A Practical Framework

Carter created an AI agent to accompany her book “AI First, Human Always.” You can access the agent here near the bottom of the page. The agent operates through Telegram and serves several functions:

• Answering questions about the book's content
• Providing information on where to purchase the book
• Directing readers to specific chapters based on their interests
• Offering supplementary information gathered since the book's publication

If you're interested in building agents, you don't need to be a technical expert to begin working with AI agents. Many platforms now offer no-code or low-code solutions that make custom agent creation accessible to marketers and business owners.

Here's a structured approach based on her experiences and recommendations:

#1: Start with Education

First, Carter suggests taking an overview class on AI agents–like this one, to get a foundational understanding. This approach helps you avoid some of the trial and error she experienced when she began working with agents.

Next, explore active agents you encounter in the course of your work or personal life. If you can, ask the businesses about the tools they used to build their agents.

This hands-on exposure to functioning agents will help you understand the possibilities and limitations before building your own agent. It will also give you valuable insights into what creates a positive agent interaction.

As you explore, you'll notice two primary types of AI agents:

Role-based agents are designed to perform specific, well-defined functions. These agents have clear boundaries and limited decision-making power, making them safer for initial implementations.

Autonomous agents have more freedom to make decisions and take actions. The fashion agent Miku can learn users' preferences to tailor recommendations and provide personalized fashion and style advice. Remember that autonomy comes with risks. After a customer conversation, Miku once became fascinated with cars and spent two days tweeting about automobiles instead of fashion advice. The creator had to intervene and redirect the agent to its fashion focus.

#2: Define Clear Objectives

Before you build, make sure you know where you'll use the agent and what you want it to do for you or your customers. 

Knowing this will help you determine:

• What functionality your agent will need
• What data sources you'll use to train it
• How much autonomy to give it
• What platforms it should integrate with

For example, suppose you want to build an AI agent to help consumers order a pizza. In that case, you want it to function autonomously when giving advice about what type of pizza someone should order but not when answering questions about where your restaurant delivers. You'd want that functionality to be very strictly controlled.

#3: AI Agent Development: Choose Your Platform and Integration Method

You'll need to decide where your agent will “live” and what it will be built with. When selecting where your agent will function, consider the following:

• Where your customers or users already spend their time
• What functionality the platform offers for agent integration
• How much control you need over the agent's responses
• Whether you need features like conversation history or broadcasting capabilities
• How the platform aligns with your brand experience

By carefully matching the environment and platform to your objectives, you can create AI agents that enhance your business operations and customer experience while maintaining appropriate brand control.

AI agents can operate across a wide range of environments:

• Social Media Platforms: AI agents can be integrated with social media platforms where they can maintain brand voice and engage with audiences at scale without constant human intervention–posting content, responding to mentions, and engaging with followers like Miku does on X.
• Messaging Applications: Carter's companion agent for her book operates through Telegram, which she chose because it allows for tracking conversations, broadcasting messages to users, and easy moderation. 
• Website Integration: One of the most common implementations is embedding agents directly on business websites, like the custom service agent on UnstoppableDomains. Unlike basic chatbots, these sophisticated agents can make decisions and deliver personalized experiences.
• Desktop Applications: Some agents function as stand-alone desktop applications. Carter has a desktop agent that listens to voice messages. If someone asks for a meeting with her, the agent schedules that meeting.
• Community Platforms: Agents can operate within community platforms like Discord to interact with multiple users simultaneously in community settings.
• eCommerce Environments: AI agents can be integrated into e-commerce platforms to provide a seamless customer experience by providing personalized shopping assistance, recommending products, processing orders, and handling payment processing.
• CRM and Support Systems: Customer relationship management systems can incorporate AI agents to handle support inquiries, access customer histories, and provide personalized support at scale.

During her agent-building journey, Carter experimented with each of the following platforms, ultimately choosing OpenAI's Operator because it offered more consistent answers through better templating. Here are her thoughts to help you choose the right platform for your own AI agent:

• AI Explain: Carter found this platform powerful for internal applications.
• Windsurf by Codeium: A newer platform Carter explored.
• ELIZAOS: Used for the fashion agent Miku, though Carter found it more challenging to control for business purposes.
• Operator by OpenAI: Carter ultimately chose this for her book agent because it offered more consistent answers through better templating.
• Virtuals: Carter tried this but found it challenging for her needs.

#5: Identify Your Training Data Sources

Next, you need to determine where to source the data to train your agent. Carter's book agent was trained on the PDF of her book, YouTube recordings of her presentations, session recordings from events, and articles she had written.

Carter described five categories of training content you can choose from:

• Proprietary Content: Your own content, such as PDFs, documentation, presentations, or blog posts
• Web Scraping: Tools like Scrapey or beautifulsoup can gather relevant web content
• Public Datasets: Hugging Face offers a marketplace of datasets
• User-Generated Content: Surveys and feedback from your audience
• Multimodal Content: Modern agents can be trained on video and audio content, not just text

#6: Optimize AI Agent Performance: Implement Validation and Quality Checks

To ensure your agent performs as expected, Carter recommends implementing validation processes to test it. Tools like Authentrics can help with this quality assessment, alerting you to training abnormalities or inconsistencies in your agent's knowledge base.

Two Tips for Success with AI Agents

As you begin your journey with AI agents, keep these final tips from Carter in mind:

Start Small and Iterate

Before you build a customer-facing AI agent, experiment with agents that can help you internally. 

One of Carter's team members built an agent that analyzes financial market trends, scrapes relevant data, provides recommendations, and creates reports—all without having professional coding skills. His agent saves him approximately 50% of his working time, demonstrating the significant efficiency gains possible with even relatively simple agents.

Regularly Update Your Agent's Knowledge

As Carter learned from her experience and from others building sophisticated agents, regular knowledge updates are essential.

Pay attention to how your agent interacts with users and be prepared to make adjustments. The autonomous fashion agent that became fixated on cars shows how even well-designed agents can go off track without proper monitoring.

Other Notes From This Episode

• Connect with Michael Stelzner @Stelzner on Facebook and @Mike_Stelzner on X.
• Watch this interview and other exclusive content from Social Media Examiner on YouTube.

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✋🏽 If you enjoyed this episode of the AI Explored podcast, please head over to Apple Podcasts, leave a rating, write a review, and subscribe.

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