Choosing an AI Agent-Building Platform / AI Success Academy

Choosing an AI Agent-Building Platform: No-Code, Low-Code, and Programming

Module 2 — Planning and Building Your First Agent

Lesson – 4

Course – 4

Introduction

In the previous lessons, we explored what AI agents are, how they work, and how to plan an agent for a particular task.

Now comes an important question:

Where and how can you build your first AI agent?

You do not necessarily need to be a professional programmer or software developer to create an AI agent. Today, different platforms allow people to build agents using visual tools, simple configuration options, or programming languages.

The best approach depends on your technical skills, budget, project requirements, and the level of control you need.

In this lesson, we will explore three main approaches:

No-code AI agent platforms
Low-code AI agent platforms
Programming-based AI agent development

By the end of this lesson, you will understand the differences and be able to choose an approach that suits your needs.

1. Understanding the Three Approaches

Before selecting a platform, it is important to understand the three common ways of building AI agents.

A. No-Code Approach

No-code platforms allow users to build AI agents without writing programming code.

They usually provide visual interfaces, ready-made components, templates, and configuration settings.

You can often create an agent by:

Selecting an AI model.
Writing instructions for the agent.
Choosing the tasks it should perform.
Connecting available tools.
Testing its responses.
Publishing or sharing the agent.

Example:

Imagine you want to create an AI assistant for AI Success Academy.

The assistant should answer visitors’ questions about courses, lessons, and learning resources.

Using a no-code platform, you could configure the assistant’s instructions, provide information about your courses, and connect it to a website chat interface without building the entire system through programming.

Advantages of No-Code Platforms

Easy for beginners.
Little or no programming knowledge required.
Faster development.
Visual interfaces make workflows easier to understand.
Useful for prototypes and simple business applications.

Limitations

Less flexibility for complex requirements.
Some advanced features may not be available.
You may depend on the platform’s available integrations.
Subscription and usage charges may apply.

Who should use no-code platforms?

Beginners, educators, content creators, small business owners, and people who want to experiment with AI agents without learning programming first.

B. Low-Code Approach

Low-code platforms combine visual development tools with the ability to add programming code when necessary.

You can build most of your workflow using ready-made components and then add custom logic to handle more advanced tasks.

For example, a low-code platform might allow you to:

Connect an AI model.
Create a visual workflow.
Connect external applications.
Retrieve information from a database.
Add custom conditions.
Use code for specialized operations.

Example:

Suppose AI Success Academy wants an AI assistant that answers course questions, checks a database for course information, and sends a request to an external service when a visitor asks for additional support.

A low-code solution could help connect these different components while allowing custom programming where required.

Advantages of Low-Code Platforms

More flexibility than basic no-code tools.
Faster development than building everything from scratch.
Support for more complex workflows.
Ability to combine visual tools and custom code.
Useful for business automation and integrated applications.

Limitations

Some programming knowledge may be necessary.
Complex workflows can become difficult to manage.
Platform-specific skills may be required.
Advanced integrations may involve additional costs.

Who should use low-code platforms?

Users who understand basic technical concepts and want more control over their AI agents without developing everything from the beginning.

C. Programming-Based Approach

Programming-based development gives developers greater control over how an AI agent operates.

Instead of relying mainly on visual tools, developers write code to define the agent’s instructions, logic, tools, data connections, and behaviour.

Common programming languages include:

Python
JavaScript
TypeScript

Developers may also use AI development frameworks and libraries to simplify agent creation.

Some examples include:

LangChain
LangGraph
Microsoft Agent Framework
OpenAI Agents SDK

These tools support different development approaches and capabilities. Their suitability depends on the project and technical requirements.

Example:

Imagine you want to build an advanced AI education assistant that can:

Understand students’ questions.
Search a large collection of educational materials.
Retrieve relevant lessons.
Use external services.
Maintain conversation context.
Perform approved actions.
Transfer complicated requests to a human administrator.

A programming-based approach can provide the flexibility needed to design and manage this system.

Advantages of Programming-Based Development

Greater control over agent behaviour.
More customization.
Ability to build advanced workflows.
Flexible integration with databases and external services.
Better control over application architecture.

Limitations

Requires programming knowledge.
Development can take longer.
Testing and maintenance require technical skills.
Hosting, security, and infrastructure may need additional planning.

Who should use programming-based development?

Software developers, technical teams, programmers, and organizations building customized or complex AI applications.

2. Comparing the Three Approaches

The following table summarizes their main differences.

Feature	No-Code	Low-Code	Programming-Based
Coding knowledge	Not usually required	Some required	Required
Ease of use	Easy	Moderate	Depends on skills
Development speed	Usually fast	Moderate to fast	Varies
Customization	Limited to moderate	Moderate to high	High
Technical control	Limited	Greater	Extensive
Best suited for	Beginners	Growing projects	Advanced applications

Remember that these are general differences. Actual capabilities vary between platforms.

3. Examples of AI Agent-Building Platforms

Several platforms and development tools can help you create AI agents.

Let’s explore some examples.

1. OpenAI Agent Builder

OpenAI provides tools for developing agent-based applications. Its visual Agent Builder is designed to help users create and test workflows using connected components.

It can be useful for people who want to explore agent workflows through a visual development approach.

Website: https://platform.openai.com/

2. Zapier

Zapier is an automation platform that connects different applications and services.

It allows users to create automated workflows and use AI capabilities in business processes.

For example, an automation could receive a form submission, process information, and send a notification.

Website: https://zapier.com/

3. Make

Make provides a visual environment for connecting applications and designing automated workflows.

It is useful for creating processes that involve multiple applications and conditional steps.

For example, you could create a workflow that receives a customer enquiry, organizes the information, and sends it to the appropriate destination.

Website: https://www.make.com/

4. n8n

n8n is a workflow automation platform that supports visual workflows, integrations, and AI-related automation.

It offers additional flexibility for users who want to customize workflows and connect different services.

Website: https://n8n.io/

5. LangChain and LangGraph

LangChain and LangGraph are development tools for building applications involving language models and agent workflows.

They are more suitable for users with programming experience.

LangGraph is particularly useful when developers need to design workflows involving multiple steps, state, and control over execution.

Website: https://www.langchain.com/

6. Microsoft Agent Framework

Microsoft Agent Framework provides development capabilities for building AI agents and multi-agent applications.

It is aimed primarily at developers working with Microsoft-supported development technologies.

Website: https://learn.microsoft.com/

Important Note

Not every automation workflow is an AI agent. Some tools simply execute predefined actions, while an AI agent can use an AI model to interpret information, select actions, and work towards a goal.

When choosing a platform, check whether it supports the level of decision-making and tool use your project actually requires.

4. How to Choose the Right Platform

Selecting a platform should be based on your requirements rather than popularity.

Consider the following five factors.

Factor 1: Your Technical Skills

Be realistic about your current abilities.

If you are a beginner with no programming experience, starting with a no-code platform may be the easiest option.

If you understand basic programming, a low-code approach may offer more flexibility.

If you are an experienced developer, programming-based tools may provide the control you need.

Factor 2: Your Budget

Some platforms offer free plans, while others charge subscription fees or usage-based prices.

Before choosing a platform, investigate:

Free plan availability.
Monthly subscription charges.
AI model usage costs.
Integration charges.
Hosting expenses.
Additional fees for higher usage.

A free plan is useful for learning, but it may have limitations.

Always check current pricing before committing to a platform.

Factor 3: Project Complexity

Think about what your agent needs to accomplish.

A simple FAQ assistant does not require the same development approach as an agent that works with databases, external applications, and multiple business systems.

Start with the simplest solution that meets your requirements.

Factor 4: Integration Requirements

Your agent may need to communicate with other applications.

For example:

A website.
An email service.
A database.
A customer management system.
A document storage service.
An online form.

Check whether the platform supports the integrations you need.

Factor 5: Privacy and Security

An AI agent may process personal information, customer enquiries, or business documents.

Before selecting a platform, investigate:

How information is stored.
Who can access the data.
Whether data is shared with external services.
Available access controls.
Data retention settings.
Security and privacy policies.

Never provide sensitive information to an AI agent unless the system has been designed and approved to handle it safely.

5. Choosing a Platform for Your First AI Agent

For beginners, the best strategy is to start with a small project.

Consider building a simple educational assistant.

Project: AI Learning Assistant

Purpose: Help visitors find information about courses and learning resources.

Basic functions:

Welcome website visitors.
Answer frequently asked questions.
Explain available courses.
Recommend relevant learning resources.
Direct visitors to the appropriate lesson or page.

You could begin with a no-code approach.

Once you understand how the agent works, you could explore more advanced features, such as connecting a database or retrieving information from multiple sources.

This gradual approach helps you learn without becoming overwhelmed.

6. Common Mistakes When Choosing a Platform

Beginners sometimes make avoidable mistakes.

Mistake 1: Choosing a platform because it is popular

A popular platform may not be suitable for your project.

Choose based on your requirements.

Mistake 2: Starting with a complicated development method

You do not need advanced programming to build every AI agent.

Begin with a simple solution.

Mistake 3: Ignoring ongoing costs

A platform may appear inexpensive initially but become costly as usage increases.

Understand its pricing model.

Mistake 4: Ignoring integrations

An agent may work well independently but fail to connect with the applications required by your business.

Check integrations before selecting a platform.

Mistake 5: Building an agent without a clear purpose

Technology should solve a real problem.

Define the agent’s purpose before selecting the development tool.

7. Practical Activity: Select Your First Agent-Building Approach

Now it is time to apply what you have learned.

Imagine that you want to build an AI assistant for an educational website.

The assistant should:

Welcome visitors.
Answer questions about courses.
Recommend relevant lessons.
Provide links to learning resources.

Think about your skills and requirements.

Answer these questions:

Do you have programming experience?
Is your project simple or complex?
What is your available budget?
Does your agent need to connect to external applications?
Would a visual development platform be sufficient?

Based on your answers, choose one of the following:

No-Code: If you are a beginner and want to build your first agent quickly.
Low-Code: If you want visual development with additional customization.
Programming-Based: If you need advanced functionality and have programming skills.

There is no single approach that is best for everyone.

The right choice is the one that meets your needs without introducing unnecessary complexity.

8. Key Takeaways

After completing this lesson, remember these important points:

AI agents can be developed through no-code, low-code, and programming-based approaches.
No-code platforms are suitable for many beginners and simple projects.
Low-code platforms combine visual development with custom programming.
Programming-based development provides greater control and flexibility.
Platform selection should consider skills, budget, complexity, integrations, and security.
Start with a small project and expand its capabilities gradually.
Not every automated workflow is an AI agent.

Lesson 4 — Knowledge Check

Test your understanding.

Question 1: Which approach is generally most suitable for a beginner with no programming experience?

A. Programming-based development
B. No-code development
C. Advanced database development

Question 2: What is the main advantage of low-code platforms?

A. They eliminate the need for testing.
B. They combine visual tools with custom programming.
C. They work without an AI model.

Question 3: Which approach generally provides the greatest customization?

A. No-code
B. Programming-based
C. Basic templates

Question 4: What should you consider before selecting a platform?

A. Only its popularity
B. Only its appearance
C. Skills, budget, project requirements, and integrations

Question 5: Is every automated workflow an AI agent?

A. Yes
B. No

Answers

Conclusion

Choosing the right AI agent-building platform is an important step in your development journey.

You do not need to begin with complicated programming or expensive software. Start with an approach that matches your current skills and project requirements.

No-code tools can help you understand the basics. Low-code platforms can introduce more flexibility. Programming-based development can support advanced customization.

The most important thing is to start learning, experiment carefully, and build an agent that solves a genuine problem.

Your first AI agent does not need to be complicated. It needs to be useful.

Looking Ahead to Lesson 5

In the next lesson, we will move from choosing a platform to planning the actual agent.

You will learn how to define an agent’s purpose, identify its users, establish its responsibilities, select the information it needs, and design a simple workflow before starting development.

Let’s move one step closer to building your first AI agent!

Lesson 3 | Course 4 | Lesson 5