What Are AI Agents, How Do They Work & How To Make One?

AI agents are software programs powered by artificial intelligence that can take actions on behalf of a user to achieve a specific goal.

Unlike basic AI tools that only respond to queries or generate content, AI agents are goal-oriented, autonomous systems. They can reason, plan, interact with other systems, and execute tasks without constant human input.

Think of them as “digital workers” that follow instructions, make decisions based on logic and data, and complete multi-step tasks, often by talking to other agents, APIs, or software platforms.

What Are the Capabilities of AI Agents?

Here’s what makes an AI agent different from a simple chatbot or automation script:

• Autonomy: They can operate without continuous input once a goal is set.
• Goal-oriented reasoning: They make decisions to reach specific outcomes.
• Task decomposition: They break down complex tasks into manageable steps.
• Tool usage: They interact with external software like CRMs, spreadsheets, or databases.
• Multi-agent collaboration: They can coordinate with other agents to divide work or share updates.
• Memory: Many agents can store and recall relevant information across sessions.

How Do AI Agents Work?

AI agents follow a structured process to complete tasks intelligently and independently. Here's how they function step by step:

1. Receives a Goal

Every AI agent begins with a defined goal. This could be anything from “find 50 qualified leads” to “summarize this document.” The goal sets the direction and provides the context for all future actions.

2. Breaks the Goal Into Sub-Tasks

Once the goal is received, the agent breaks it into smaller, logical steps. This planning process is typically powered by a language model or logic framework. For example, generating leads may involve:

• Finding relevant companies
• Identifying key decision-makers
• Verifying contact information
• Formatting the results
• Uploading the data to a CRM

3. Uses Tools and APIs to Execute Tasks

After planning, the agent performs each task by interacting with external tools, systems, or APIs. It may:

• Access web scraping services to gather company data
• Call an email verification API
• Format and send the data to a third-party platform like a CRM

Each tool interaction is automated and context-aware.

4. Makes Decisions During Execution

As the agent progresses, it evaluates each outcome in real time. If a task fails, like an API returns an error or data is missing, it adjusts the approach, retries, or replans the task sequence to stay aligned with the original goal.

5. Coordinates With Other Agents (If Needed)

In more advanced setups, agents operate in groups. One main agent may delegate tasks to specialized agents:

• A data collection agent gathers information
• A verification agent checks accuracy
• A delivery agent uploads the final result

These agents share updates and collaborate to achieve the goal more efficiently.

6. Delivers the Final Output

After all tasks are completed, the agent compiles and delivers the final output. This could be a summary, a filled database, an action taken in a third-party system, or a report, depending on the goal it was given at the start.

How to Make Your Own AI Agent (in Minutes, with Lindy)

Making an AI agent might sound daunting, but Lindy makes it super easy. You can choose from one of Lindy’s pre-built templates or build from scratch.

Method 1: Build an AI Agent with a Pre-Built Template

Step 1: Sign Up on Lindy for FREE

Log into your Lindy account, or if you don’t have one, sign up for free.

Step 2: Find a Pre-Built Template

Once you’re in, you’ll be taken to Lindy’s dashboard. Scroll down to See all templates.

Select a template of your choice. If you need an AI agent for a certain task, type it into the search bar, and it’ll show you all the related templates.

Then select the template you want and click Add.

Step 3: Customize Your AI Agent Template

Now it’s time to set up and customize your AI Agent. You can do this in Settings and the Flow Editor.

Click each element to configure it.

Hook up your AI agent with your work tools. Lindy integrates with thousands of tools like Salesforce, Gmail, Slack, and so on.

Method 2: Build an AI Agent From Scratch

Have something unique in mind? Lindy can help you turn your vision into a reality. It even makes building an AI agent from scratch super easy.

Step 1: Create a New Lindy

Select New Lindy on the right of the dashboard.

Then click Start from scratch.

Step 2: Define a Trigger

Click the Select Trigger button in the Flow Editor.

Select an app of your choice.

Then select the exact action associated with it.

Step 3: Set a Response

Once you have selected a trigger, you need to tell Lindy what action it should take in response to it– and which app it should use.

Click Perform an action.

Then again, select an app that should act in response to the trigger.

Finally, select what exact action it should take.

Step 4: Mix-Match, Test, and Optimize

Just like this, you can add a lot of triggers, conditions, and responses while setting up your AI agent. You can integrate different apps across sales, marketing, customer support, and more.

5 Types of AI Agents and What They Can Do

AI agents come in different types, each with specific capabilities based on how they process information and execute tasks. Here’s a breakdown of the most common types:

1. Reactive Agents

Reactive agents are the simplest type. They respond only to immediate inputs and don’t have memory or the ability to plan. These agents are useful for basic tasks like triggering an action when a specific command is given. For example, a chatbot that replies with pre-set responses based on keywords falls into this category.

2. Planning Agents

Planning agents go beyond reactive behavior. They can take a defined goal and break it down into smaller, sequential steps. These agents are capable of creating structured plans and following through to completion. A good example is an AI travel planner that books flights, hotels, and transportation based on your preferences.

3. Tool-Using Agents

Tool-using agents can interact with external software or APIs to complete tasks. They don’t just think, they act. These agents can read documents, extract data, fill out CRM entries, send emails, or move files between apps. They are especially useful in automating business workflows and handling operational tasks.

4. Collaborative Agents

Collaborative agents are designed to work with other agents in a shared environment. They can delegate tasks, communicate progress, and update each other in real time. This makes them ideal for complex workflows where multiple processes need to run in parallel. A multi-agent system handling end-to-end market research is a good example of this type.

5. Long-Memory Agents

Long-memory agents store and recall information across sessions. They can learn from past interactions, remember user preferences, and make better decisions over time. These agents are useful for ongoing tasks that require context, such as acting as a virtual executive assistant who manages calendars, communications, and recurring tasks.

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How to Use Agents? (Examples)

AI agents are being used across industries to handle everything from sales and support to research and internal operations. Here’s how businesses are putting them to work today:

1. Powering Sales Automation

In sales, AI agents can take over repetitive yet critical tasks. They can search for leads, qualify them based on job titles or industries, verify contact information, and update CRMs, completely hands-off.

For example, a company targeting CFOs in SaaS companies with 50–200 employees can assign that goal to an agent, which will complete the entire process autonomously. This frees up sales teams to focus on closing, not chasing.

2. Supporting Customer Service at Scale

AI agents help customer support teams manage growing ticket volumes. They can triage incoming issues, answer routine questions, escalate complex problems, and even generate summaries for human agents.

This shortens response times, reduces backlog, and improves customer satisfaction, without needing to scale your support headcount linearly.

3. Streamlining Marketing Operations

Marketing teams use AI agents to automate workflows that would otherwise take hours. Agents can generate blog ideas, repurpose video content into posts, schedule social media updates, and analyze performance data to recommend next steps.

This ensures campaigns move faster and content stays fresh without overwhelming the team.

4. Accelerating Research and Insights

In research-heavy industries like consulting, legal, or finance, AI agents can scan and summarize large volumes of data, from PDFs and websites to product manuals and market reports.

They can extract trends, compare competitors, or compile executive-ready insights in a fraction of the time it would take a human analyst.

5. Optimizing Internal Business Operations

AI agents are also becoming essential in day-to-day business ops. They can generate invoices, process employee onboarding documentation, clean and organize spreadsheets, or run compliance checks on routine data.

These behind-the-scenes tasks, when automated, lead to faster workflows and fewer human errors, without requiring additional staffing.

How Are AI Agents Different from Regular Chatbots?

AI agents go far beyond traditional chatbots by combining autonomy, dynamic decision-making, and real tool usage to complete complex, multi-step tasks independently.

What Powers an AI Agent?

• LLMs (Large Language Models) – For reasoning, planning, and dialogue (like GPT-4 or Claude).
• Orchestration Logic – Rules and state management to keep track of what the agent is doing.
• APIs & Integrations – To take action in external apps (e.g., CRMs, web scrapers, databases).
• Memory Systems – Short-term (for the task) or long-term (user preferences, task history).
• Tool Libraries – Predefined functions the agent can call to complete work.

Challenges and Limitations of Using AI Agents

AI agents offer powerful automation, but like any advanced system, they come with trade-offs. Understanding these limitations helps you set them up for success and avoid costly mistakes.

1. One of the biggest challenges is clarity. AI agents need well-defined goals to function effectively. If you give vague instructions like “find good leads” without specifying who, where, or how many, the agent may return inconsistent or irrelevant results.

2. They can also go off-track. Without proper sandboxing or constraints, an agent might loop indefinitely, misuse tools, or trigger workflows in unintended ways. This makes guardrails and testing essential.

3. Security is another major concern. Since agents often require access to CRMs, email tools, databases, or payment systems, you need strict permission controls and logging. Otherwise, a misconfigured agent could create risks by changing or exposing sensitive data.

4. Cost is also a factor. Some agents rely on continuous reasoning or multiple API calls to complete a task, which can quickly become expensive, especially at scale or in enterprise use cases.

That said, when you design with clear goals, proper permissions, and usage limits, AI agents can automate tasks that normally take hours or days, making them a valuable addition to any modern workflow.

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Get Started with AI Agents Using Lindy

If you're ready to build your own AI agent without any coding at all, Lindy is just the platform for you. It makes it fast, flexible, and free to try.

With Lindy, you can:

• Use pre-built templates to launch AI agents in seconds
• Connect with 5,000+ tools like Gmail, Slack, Notion, Salesforce, and more
• Build multi-step workflows using natural language and a visual flow editor
• Start from scratch or templates, no technical setup needed

Whether you're automating sales tasks, streamlining research, or building an internal assistant, Lindy helps you create powerful AI agents tailored to your workflow.

Try Lindy for FREE today!

Frequently Asked Questions

1. What’s the difference between an AI agent and an automation tool like Zapier?

Zapier follows fixed workflows triggered by specific events. AI agents go further because they understand goals, make decisions, and adapt in real time. They can reason through complex tasks, use multiple tools, and interact with data. While Zapier moves information, AI agents complete entire workflows with built-in intelligence.

2. Do I need to know coding to build an AI agent on Lindy?

You do not need any coding knowledge to build an AI agent on Lindy. The platform offers a visual builder and templates that let you create workflows by selecting triggers and actions. You can customize how your agent behaves and connects with your tools using a simple drag-and-drop interface.

3. Can AI agents be used in regulated or secure industries like healthcare or finance?

AI agents can be used in secure environments if they are configured properly. You must limit their access to sensitive data, apply strict permission controls, and monitor all activity. With the right safeguards, AI agents can operate in industries with high compliance standards like healthcare, banking, and legal.

4. How is an AI agent better than a regular AI chatbot?

AI agents do more than respond to messages. They understand context, use external tools, and take actions that solve complete tasks. A chatbot might answer questions, but an AI agent can manage workflows, update systems, and follow through on goals without requiring constant user input.

5. What kind of tasks are best suited for AI agents?

AI agents work best on tasks that are repetitive, logic-driven, or depend on large amounts of data. Examples include qualifying leads, summarizing documents, routing support tickets, managing schedules, and syncing information between systems. They can handle the full process instead of just one part of it.

6. Can I train the AI agent to follow specific workflows for my business?

Yes, you can build custom workflows that match your exact process. Lindy lets you choose when the agent should act, what tools it should connect to, and what sequence of steps it should follow. You can shape the logic based on your team’s needs and software stack.

7. Is there a free version of Lindy to test AI agents?

Lindy offers a free plan that lets you explore templates, build new agents, and test basic workflows. You can connect popular tools, create automation chains, and see how agents perform in your real environment. This gives you hands-on experience before committing to a paid version.

8. How to build AI agents from scratch?

To build from scratch, first choose a trigger like receiving a form submission or an email. Then decide what action the agent should take. Use Lindy’s flow editor to link steps together, select the apps involved, and add logic to handle different outcomes. Test your agent and refine it based on how it performs.