Build & Monetize AI Agents: Beginner's Guide to Automation

What is an AI Agent?

The clearest definition of an AI agent is that it is a digital worker that can understand instructions and take actions in order to complete tasks. In simple terms, an AI agent is like having a digital employee that you can build and program to do whatever you want.

The key difference between AI agents and traditional chatbots is that agents can actually take actions and complete tasks, rather than just providing pre-written responses. For example, an agent could check a calendar, book an appointment, update a CRM, and send a confirmation email - all automatically without human intervention.

The Anatomy of an AI Agent

There are 5 key components that make up a functional AI agent:

1. Brain: This is the large language model (LLM) that powers the agent's understanding and decision making, such as GPT-3, Claude, or Gemini.

2. Prompting: The instructions that define how the agent should behave and what actions it should take.

3. Memory: Allows the agent to remember context from previous interactions and build on past conversations.

4. Knowledge: Additional data or information that can be provided to the agent to enhance its capabilities beyond its base training.

5. Tools: The external systems and APIs that the agent can access in order to take actions and complete tasks.

The 3 Ingredients of Building AI Agents

When planning and building AI agents, there are really only 3 key elements to focus on:

1. Prompting: The instructions that define the agent's behavior and decision making.

2. Knowledge: The external data and information that the agent can access and utilize.

3. Tools: The actions and capabilities that the agent can perform by integrating with external systems and APIs.

By mixing these 3 ingredients in different ways, you can create a wide variety of unique and powerful AI agents for different use cases.

The Importance of Tools

Tools are the most powerful part of an AI agent, as they allow the agent to actually take actions and complete tasks, rather than just chat. Agents use APIs to interact with external systems and services, just like how we use the internet by making requests and receiving responses.

Understanding how APIs work, and how to build custom tools that expose functionality through APIs, is a crucial skill for creating valuable AI agents. This allows agents to automate all kinds of online tasks, from updating databases to sending emails, just like a human employee but much faster and more efficiently.

The Power of Multi-Tool Agents

The real magic happens when you give AI agents access to multiple tools, allowing them to combine different capabilities to solve complex problems. Just like a human employee would use various software and services to complete their work, AI agents can leverage a suite of tools to tackle tasks in a step-by-step, intelligent manner.

This ability to plan, take actions, and adapt their approach makes AI agents incredibly powerful digital workers that can automate a wide range of business processes. The potential for AI agents to transform how work gets done is immense.

Build 1: Sales Co-Pilot with Relevance AI

In this first build, we're going to create a sales co-pilot agent using Relevance AI. The purpose of this agent is to help sales reps at a hypothetical recruitment firm called "Big Boy Recruits" to be better prepared for sales calls.

The agent will have three main tools:

1. Company Researcher: This tool will take in a company URL and scrape the website to generate a summary of the company's details.

2. Prospect Researcher: This tool will take in a LinkedIn URL and scrape the prospect's profile to generate a summary.

3. Pre-Call Report Generator: This tool will combine the company and prospect research to generate a pre-call report that the sales rep can use to prepare for the call.

We'll build these tools in Relevance AI and then connect them together into an agent that the sales reps can interact with.

Build 2: Automated Lead Qualification Agent with n8n

In this build, we're going to create an automated lead qualification agent using the n8n platform. The purpose of this agent is to automatically research new leads that come in through a web form, determine if they are a good fit for the business, and then trigger the appropriate next steps.

The agent will:

1. Receive a new lead submission from a web form.
2. Use a Relevance AI tool to research the company.
3. Determine if the lead is qualified based on predefined criteria.
4. If qualified, trigger a workflow to notify the sales team.
5. If not qualified, send an automated email to the lead.

This build will demonstrate how you can use AI agents to automate lead qualification and routing within a business.

Build 3: Website and Phone-based Lead Generation Agent with Voiceflow

In this build, we're going to create a lead generation agent that can be accessed both through a website chat widget and a phone number, using the Voiceflow platform.

The agent will have the following functionality:

1. Answer common questions about the business and its services from a knowledge base.
2. Generate instant quotes for interested parties based on property type and size.
3. Capture lead information (name, email, etc.) for those who request a quote.

This build will show you how to create an agent that can seamlessly transition between chat and voice interactions, providing a consistent experience for the customer.

Build 4: WhatsApp-based Lead Generation Agent with Agent

In the final build, we'll use my own AI agent platform, Agent, to create a lead generation agent that can be connected to a WhatsApp number.

This agent will:

1. Engage with leads who message the WhatsApp number.
2. Gather information about their inquiry.
3. Automatically log the lead details into an Airtable database for the sales team to follow up.

This build will demonstrate how you can quickly create and deploy AI agents using a no-code platform, and integrate them with popular messaging channels like WhatsApp.

Throughout these four builds, you'll learn how to:

• Build custom tools and APIs using platforms like Relevance AI
• Integrate AI agents with workflow automation tools like n8n
• Create conversational agents for both chat and voice interactions
• Deploy AI agents on popular channels like websites, phone, and WhatsApp

By the end of this section

Becoming an AI Agent Entrepreneur

The final chapter of this video is all about how you can start to monetize the AI agent building skills that you've just learned. There are two main paths you can take:

1. Become an AI Agent Entrepreneur
2. Offer AI Agent Building Services

As an AI agent entrepreneur, the goal is to build your own AI agent products and services that you can sell directly to customers. This could involve building AI agents for specific industries or use cases and selling them as a SaaS (Software as a Service) offering.

For example, you could build an AI agent that specializes in lead qualification and sales prospecting, and sell it to businesses in the software or consulting space. Or you could create an AI agent assistant for real estate agents to help with tasks like scheduling, answering FAQs, and generating marketing content.

The key advantages of this model are:

• You own the intellectual property and can scale the business
• You can generate recurring revenue from subscription-based pricing
• You control the pricing and have higher profit margins than services

To be successful as an AI agent entrepreneur, you'll need to:

• Identify a valuable problem that can be solved with an AI agent
• Build a high-quality agent that delivers real value to customers
• Market and sell the agent effectively to find paying customers
• Continuously improve and expand the agent's capabilities over time

Offering AI Agent Building Services

The other path is to offer AI agent building services to clients. In this model, you position yourself as an expert in AI agent development and get hired by businesses to build custom agents for their needs.

This could involve:

• Building AI agents from scratch for a client's specific use case
• Integrating AI agents into a client's existing systems and workflows
• Providing ongoing maintenance, updates, and support for a client's AI agents

The advantages of this model are:

• You can get started more quickly without having to build your own product
• You can leverage your skills to get paid for your expertise
• You don't have to worry about marketing and sales as much

To be successful offering AI agent services, you'll need to:

• Build a portfolio of successful agent builds to showcase your skills
• Network and market yourself to potential clients in your target industries
• Develop a repe

In this comprehensive course, we have covered everything you need to know about building and monetizing AI agents, even if you have no prior experience in AI.

We started by defining what an AI agent is - a digital worker that can understand instructions and take actions to complete tasks. We then dove into the five key components that make up an agent: the brain (a large language model), prompting, memory, external knowledge, and tools.

Next, we explored a practical framework for understanding AI agents - the three ingredients of prompting, knowledge, and tools. We discussed how these elements can be mixed in various ways to create millions of different agent use cases.

We then took a deep dive into tools, learning how they work under the hood using APIs and schemas. This understanding is crucial, as tools are the most powerful part of an AI agent, allowing them to take real-world actions.

We also covered the power of combining multiple tools, which enables agents to solve complex problems just like humans would, by planning, taking actions, and reflecting on the results.

After building this foundational knowledge, we walked through four end-to-end agent builds across different no-code platforms. These included a sales co-pilot, a lead qualification agent, a customer support and lead generation agent, and an agent built on my own platform, Agent.

Finally, we explored the immense real-world value of AI agents and the massive opportunity they present. With AI and automation expected to impact up to 50% of current work by 2030, becoming AI-literate is one of the most valuable skills anyone can have.

Whether you're an aspiring entrepreneur, a business owner, or an employee looking to future-proof your career, this course has equipped you with the knowledge and practical skills to build and monetize your own AI agents. The possibilities are endless - it's time to put this powerful technology to work and create the life of your dreams.