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IT job market: how have no-code platforms transformed jobs?

notebook codes

Estimated reading time: 10 minutes

In the last ten years, society has faced a major revolution marked by digitalization, connectivity, internet of things and even artificial intelligence. The truth is that today there are technologies so advanced that no sci-fi film from the 1980s was able to predict. 

With such digital transformation, the job market found itself obliged to follow these trends and we currently have a technological reality that is widespread in the corporate world. 

Virtual clocking in and collaborative cloud spaces are just a few examples of the tools used in home office companies in different niches. It is no longer necessary for an organization to be focused on technology sectors to be technological. 

To some extent, all companies use digital solutions, whether to organize its structures or offer services. 

Within this context, O job market in Information Technology (IT) becomes increasingly inflated and more professionals are required. After all, have you ever wondered how these companies manage to develop so many technological solutions? 

However, there are not many qualified professionals to meet this demand. For this reason, the low-code and no-code platforms emerge to solve this problem once and for all. 

These solutions offer affordable and simple programs that allow you to create applications, automate processes, provide reports and dashboards In real time without the need for in-depth knowledge of programming languages.

Are you interested in the subject and want to know how no-code platforms Have they transformed IT jobs? Stay with us in this article, as we will discuss this broad job market and show you what you need to be successful as a no-code programmer.

programming man

How is the IT job market?

IT is the acronym for Information Technology, an area that involves a series of activities related to technology, such as databases, hardware, softwares and networks (home or business), used to handle information. In general, the profession is responsible for helping companies work with their data and optimize their processes. 

Some of the main functions of a professional in this area include:

  • Technical support;
  • Schedule;
  • E-commerce development;
  • Database administration;
  • Security.

The IT sector is present in most companies and is essential for maintaining their operational processes. It is an area in constant growth, even with global crises in the job market.

There are several job possibilities for IT professionals, they can work in:

  • Financial sectors;
  • Companies specializing in technology (such as start-ups);
  • Public and private organizations;
  • Banks and insurance companies;
  • Telephone operators;
  • Industries.
  • Hospitals and clinics.

There is a great demand for qualified professionals in different sectors, however There are not enough people to fill these positions. According to a survey carried out by BrazilLAB and Fundação Brava, in partnership with the Center for Public Impact (CPI), the deficit of professionals in the area is expected to continue growing and could reach the number of more than 300 thousand people by the year 2024 . 

It is no surprise that the IT profession was one of the highest paid in the second quarter of 2023, according to the Brazilian Institute of Economics of Fundação Getúlio Vargas.

What is the future of the IT job market?

We've already talked about what the IT job market is like today, but what are the main trends for the future of programming? Keep reading to find out! 

In the business context, the revolution in new technologies has created a new type of consumer: more demanding. Therefore, a culture of speed began that accompanies this increase in demand and the need for more agile and efficient processes

Information is the most precious data in this new form of society, it is almost infinite and an efficient organization in this case is essential. Regarding data processing, global consultancy Gartner identified several rising technological trends, see some of them: 

  • Data mesh;
  • Cyber security mesh;
  • Cloud-native platforms.

Although this is almost common sense in the IT area, few professionals have enough experience to implement these tools. This is when no-code technology stands out, as it allows people without technical programming knowledge to build and implement new solutions effectively. 

Benefits of using no-code for the IT job market

no-code technology is based on a basic premise: ensure the production of technologies in an accessible and simple way. In it, softwares are created through an interface with models that bring together several actions. 

These platforms are widely used by micro and small entrepreneurs, but are becoming increasingly widespread among large companies such as: 

  • Spotify;
  • Amazon;
  • Google;
  • Goal.

Do you want to know the main benefits of no-code and why these tech giants are implementing it? Continue reading. 

programming-codes

Reduction of steps and time worked

With the no-code, systems and tasks can be automated by applications created from templates ready. This way, professionals in the IT sector are free to focus on activities that require their specific skills. This adds great autonomy to the company's teams and helps the overall efficiency of the business.

Best value for money

Companies can save a lot when they don't have to hire highly specialized developers or purchase third-party applications. The no-code development allows internal teams create and update technological solutions quickly and efficiently.

Furthermore, systems simplification and data integration facilitate the management and ongoing maintenance of applications, which reduces the time and resources needed to ensure operations.

High efficiency

Another benefit is the increase in internal productivity, since excessive dependence on the IT department is reduced, as we mentioned previously. This way, employees in each department can meet their own technological needs.

This autonomy eliminates bottlenecks that often arise when IT requests need to be approved and fulfilled. With the ability to develop their own solutions or adjust existing systems, employees can act more independently and direct the progress of their tasks.

What are the skills of the no-code developer in the IT job market?

Now that you understand how no-code can revolutionize the IT market, you may be wondering what it takes to enter this field. We have separated some essential skills for developing no-code in the job market, see: 

Recognize needs

What are the user's true needs and how to solve them through no-code programming? A good codeless developer is able to observe a demand – in society, in the company or in the IT market – and create, from a few commands, something that can revolutionize the entire area of technology. It is this professional who comes out ahead.

Enjoy studying

To become a successful no-code developer, you need to enjoy learning. Despite being easier than traditional programming, no-code requires knowledge of new platforms, coding styles, and more. Being self-taught can bring you many competitive advantages, use the internet to your advantage and invest in no-code courses accessible. 

Work with little management

Developers work with little supervision, so you need to be very organized and become your own boss. This means that you need to be your own motivator and invest in effective planning of your projects. 

It is necessary to know how to work independently and build creative solutions for the business routine before ideas come from leadership.

Knowing how to receive criticism

Receiving constructive criticism is part of every worker's routine and for no-code developers this is no different. In fact, your client or supervisor may have criticisms that lead to building better softwares. 

Don't dismiss opinions and learn to listen and interpret the needs of others in order to implement their requests efficiently on apps and websites.

“Sell the fish”

Last but not least, learn how to sell your idea. Not everyone will understand technical terms or the need for a developer on the team. It's your job explain the benefits of your work, what you can do for the company or client.

How to work with no-code in the IT department?

To implement no-code in the IT department, you first need to follow some tips:

Value automated processes

The first step to implementing a no-code developer in the IT department is understand and show the benefits of codeless programming. You can start by showing interest and talking about your ideas with the person responsible for the sector.

Get to know the no-code platform

Discover no-code platforms of different types, see which big techs use and start there. Seek knowledge in free training or courses that fit your budget. One FlutterFlow course could be a good choice.

Keep an eye out as many software vendors offer specific training programs for no-code developers. There are also free videos and tutorials that can help you at the beginning of your journey.

Present ideas no-code

The next step is to share your ideas with colleagues and superiors within the organization. Be sure to show in a practical way how no-code can be applied to improve efficiency, optimize processes and generate value for the company.

What is the salary of no-code developer? 

According to the Code Source 2023 survey, the average salary of a low-code developer, which includes no-code, in Brazil is R$ 8,256.66.

In addition to formal remuneration, no-code developers can venture out as freelancers or individual micro-entrepreneurs (MEI). Many move towards the mobile environment and discover how to make money creating apps.

So, do you think it’s worth starting to invest in the area? 

No-Code Start-Up helps you on this journey

Now that you know how hot the IT job market is for no-code programmers, how about investing in this sector?

At No-Code Start-Up you will find courses to create incredible applications, startups and e-commerces without using a line of code.

Discover our Bubble training and see how easy it is to be a no-code developer.

Don't miss the opportunity to learn from No-Code Start-Up! 

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Watch our Free MasterClass

Learn how to make money in the AI and NoCode market, creating AI Agents, AI Software and Applications, and AI Automations.

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Learn how to create AI Applications, Agents and Automations without having to code

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If you are looking for a Free AI Agent Course for Beginners, you have come to the right place! After all, we are in the era of automation and artificial intelligence. In this context, companies and professionals are looking, above all, for intelligent solutions to optimize processes. In addition, they are looking to reduce costs and, consequently, improve the user experience.

In this context, AI agents stand out for their ability to automate complex tasks, interact naturally with users and integrate multiple systems without the need for constant supervision.

Continue reading this article and discover how the Free AI Agent Course can transform the way you work with artificial intelligence. Understand why AI agents are so powerful and learn how to start creating your own agent from scratch, using accessible and efficient tools, without needing any programming experience. Enjoy your reading! 

find out how the agents course is structured

From Zero to AI Agent: Learn how it works Free AI Agent Course for Beginners

If you want to learn for free and create your own AI Agent, the first step is to learn about the structure of the Free AI Agent Course for Beginners from NoCode Startup. If you want to start from scratch and develop your own Artificial Intelligence Agent, this content was made for you, in a complete material you will learn: 

  • fundamentals of Artificial Intelligence Agents to build a solid foundation;
  • a step-by-step guide to creating practical agents, even without prior experience;
  • how to use N8N to implement smart automations efficiently;
  • integrations with platforms such as Telegram, enabling the creation of interactive and dynamic agents.

Remember that the AI Agent course was developed so that anyone, even without prior programming knowledge, can create intelligent and scalable solutions. In other words, even if you have never programmed before, you can start without fear!

Why are AI agents so powerful?

Before understanding how to create your own AI Agent, it is essential to understand why these tools have become indispensable in different sectors. Therefore, it is worth reflecting: why is the use of these solutions growing so much? How do they impact the efficiency of processes?

Furthermore, understanding these aspects can reveal new opportunities for optimization and growth.

1. Integration with custom data (RAG)

why are ai agents so powerful rag

One of the main reasons for the power of AI agents lies in the technique known as RAG (Retrieval-Augmented Generation). This methodology allows the AI model to be combined with personalized user or company data. This means that the agent can be trained to access specific information from:

  • PDF files;
  • corporate websites;
  • spreadsheets and databases;

Through this customization, the agent becomes able to perform advanced queries, access specific documents and respond accurately based on the available information. 

2. Ability to execute actions (Function Calling)

why are ai agents so powerful function calling

In addition to RAG, another distinguishing feature of AI agents is the function called Function Calling (or tools), which allows the agent to not only analyze data, but also perform actions on different platforms. For example, among the main functions, the following stand out:

  • access and edit the calendar (schedule meetings, check events);
  • send, read and reply to emails;
  • interact with spreadsheets and databases (consult and update information);
  • perform direct tasks via corporate applications.

This capability turns the agent into a true virtual assistant. Imagine being able to send a simple message on WhatsApp, and the agent automatically accesses different systems, queries databases and sends comprehensive reports, all without direct human interaction.

Learn how to create AI Agents for different businesses

learn how to create IA agents for different businesses

AI agents aren’t limited to basic tasks or simple interactions. In the Free AI Agents for Beginners Course, you’ll master tools like RAG and Function Calling and learn how to create intelligent solutions for different industries, without needing technical experience and without paying anything!

Scheduling agents, for example, can automate appointment scheduling, eliminating the need for direct human interaction. Key application examples include:

  • medical consultations: the agent checks available times, schedules the appointment and sends confirmation to the patient;
  • barbershops and beauty salons: the agent manages the professionals' schedule and allows clients to choose times directly via WhatsApp or Instagram;
  • classes and events: Want to schedule an adventure class or special event? The agent automates the process and confirms details with participants;
  • restaurants and snack bars: the agent acts as an intermediary between the customer and the establishment, optimizing orders and integrating with the restaurant system;
  • e-commerces: manage orders, inventory and customer service in an automated way, using agents integrated with the main sales platforms;
  • veterinary clinics: allow appointment scheduling, vaccination control and automatic notifications for customers;
  • gyms and studios: the agent manages class reservations, waitlists and sends automatic reminders to students.

Understand the Architecture of an AI Agent

Creating an AI Agent is more than just programming a chatbot. It’s about developing an intelligent, autonomous solution that transforms processes!

To do this, it is essential to understand the architecture that supports these agents, ensuring that they are capable of performing complex tasks, interacting with different platforms and delivering accurate and contextualized responses.

Below, learn more about this framework and how each component contributes to the advanced performance of AI agents.

  • Input Layer: where the agent receives information from the user through different channels (WhatsApp, Instagram, email or website), whether in text, voice or specific commands;
  • natural language processing (NLP): responsible for interpreting messages, understanding intentions and extracting relevant information, such as dates, times and user preferences;
  • connectors and APIs (Function Calling): allow the agent to perform real actions, such as checking available times, consulting menus or accessing internal systems, through external integrations;
  • RAG (Retrieval-Augmented Generation): combines natural language generation with external data retrieval, allowing the agent to search for information in databases or on the internet in real time before responding;
  • decision making and automation: After processing the information, the agent performs actions such as scheduling appointments, forwarding orders or sending notifications;
  • real-time feedback: keeps the user informed about the status of the service, sending automatic updates at each stage of the process.

N8N: The most complete tool for creating AI agents

n8n complete tool to create AI agents
n8n complete tool to create AI agents

Creating AI agents goes far beyond just setting up simple bots. There are robust tools on the market that allow you to build complex, interactive, and fully automated agents. Choosing the right tool makes all the difference in the performance and possibilities of your project.

In this way, the N8N stands out for integrating two essential worlds: advanced automation and creation of AI agents. 

Originally designed for complex automation, the platform has evolved and today offers a powerful framework for creating intelligent and scalable agents. Among the main differentiators of N8N are:

  • creation of complex automations and integrations on a single platform;
  • integration with multiple AI models such as GPT, Llama, Claude and Gemini;
  • ability to host the system on your own servers, reducing costs;
  • intuitive interface with support for the “No-Code” concept, ideal for beginners'
  • integration with external tools such as calendars, spreadsheets, emails and databases.

Additionally, N8N offers a visual interface for creating automation flows, making the job easier even for those with no prior programming experience. And best of all, you can take a 14-day free trial with credits included to use OpenAI's resources.

OpenAI: Simplicity and Scalability

OpenAI offers one of the most robust solutions on the market, enabling the creation of powerful AI agents through the use of GPT models (such as GPT-4). 

With a simple-to-use API and excellent documentation, OpenAI has become a reference for developers who want to create scalable agents with high processing capacity. Among its main advantages are:

  • pre-trained models with high natural language understanding capacity;
  • easy integration with platforms like N8N;
  • scalability for projects of all sizes;
  • support for techniques such as RAG and Function Calling;

Dify: Open source and total flexibility

Dify stands out for being 100% open source, allowing developers to have complete freedom to adapt the agent according to their needs. Dify's main features are:

  • open source, allowing complete customizations;
  • possibility of hosting on own servers, reducing expenses;
  • broad integrations with databases, APIs and external tools;
  • simplicity in training custom agents with specific data.

But how do you choose the ideal tool? Choosing the ideal tool will depend on your goals and the level of complexity of your project:

  • If you are looking for something practical and scalable, OpenAI may be the best choice;
  • for those who need advanced automations and complex integrations, N8N stands out;
  • If the focus is total freedom of customization and an open source solution, Dify is perfect.

And if your goal is to create complex automations with multiple integration points, N8N is the best choice. Its ability to combine automations with AI and the possibility of self-hosting make it one of the most powerful tools on the market.

Time to get your hands dirty: learn how to create your first AI Agent

time to get your hands dirty learn how to create your first AI agent

If you've followed the Free AI Agent Course for Beginners | From Zero to AI Agent, it's time to put everything you've learned into practice! In this step, I'll guide you through the process of creating your first AI Agent, using accessible and efficient tools, such as N8N, OpenAI and Dify. Ready? Let's go! 

1. Step 1: Defining your AI Agent front-end

The front-end is the interface of your project, the point of contact where the user interacts with your agent. In this content, we will use Telegram for its simplicity and versatility. Although it is possible integrate WhatsApp, this platform's API demands more complex processes.

So, for beginners, Telegram is the best choice. Later, you can explore the integration with WhatsApp.

2. Creating the Agent in N8n

N8N will be the main automation tool in your AI Agent. With it, you can create complex workflows without the need for advanced programming. Follow the steps below to get started:

  • create your free account on N8N with a 14-day free trial and credits to use the OpenAI API;
  • access the N8N panel and configure your credentials;
  • create a new workflow by clicking on “Start from scratch”;
  • choose your first trigger (e.g.: message received on Telegram);
  • add the “AI Agent” node and connect to the OpenAI GPT model.

3. Expanding the functionalities

Now that your basic AI Agent is up and running, it's the perfect time to enhance its capabilities, making it even more efficient and versatile! 

Learn how to add advanced functionality that allows your agent to interact with different types of data, integrate new platforms, and provide a richer user experience.

1. Adding memory layer (WindowBufferMemory

For your AI Agent to have the ability to remember information during a conversation and maintain context between messages, it is essential to add a memory layer.

 The implementation of WindowBufferMemory in N8N allows the agent to store recent interactions, ensuring more accurate responses aligned with the context of the dialogue. To implement, follow the steps below: 

  • In N8N, add the WindowBufferMemory node to your agent flow.
  • configure the following parameters:
    • Window Size: define the number of messages the agent should remember (e.g.: 5 previous interactions);
    • storage method: For temporary storage, use N8N's default storage. For long-term storage, integrate with databases like Redis or Supabase;
  • Connect the WindowBufferMemory node to your AI Agent node so that the agent uses the history when generating responses.

To make the implementation clearer, imagine the following scenario: the user asks “What’s my appointment tomorrow?” and then simply writes “What about Friday?”. 

Even without repeating the full question, the agent understands that the context is still about commitments and provides the correct answer. 

Now that the agent is prepared to store contextual information, you can explore additional integrations and enhance its functionality, creating a more robust and efficient flow.

2. Integration with multiple tools (Function Calling)

To take your AI Agent to the next level, allow it to interact directly with other platforms and perform complex tasks. With Function Calling, the agent not only answers questions, but also performs practical actions across different systems. Key features you can integrate include:

  • Google Calendar: automatically schedule and list events;
  • Spreadsheets (Google Sheets/Excel): add, remove or search data in real time;
  • Email (Gmail/Outlook): send personalized automatic emails;
  • External APIs: perform queries on third-party services, such as weather forecasts, currency quotes or traffic information.

To set up these integrations, follow the steps below:

  • in N8N, add the node corresponding to the service you want to integrate (e.g. Google Sheets or Google Calendar);
  • In AI Agent, use the Function Calling function to enable the execution of automatic actions when certain commands are detected;
  • Create specific prompts to activate each tool, ensuring that the agent understands the user's requests. Practical examples:
    • “schedule a meeting for tomorrow at 2pm.”
    • “add the client João Silva to the contact spreadsheet.”
    • “send a confirmation email to [email@example.com].”

In this way, the agent becomes not only an intelligent assistant, but also an executor of complex tasks, expanding its functionalities and delivering a much richer and more dynamic experience to the user.

3. Implementing sentiment analysis

You can also enhance your AI Agent’s communication by empowering it to interpret the emotional tone of user messages and adjust its responses accordingly. This ability creates a more humanized, empathetic, and contextualized interaction. 

To do this, follow the steps to implement sentiment analysis:

  • in N8N, add the Text Analytics node or use external APIs like Google Natural Language or IBM Watson;
  • connect the node to the main flow of the agent, right after receiving the user's message;
  • configure the node to identify emotions such as happiness, anger, sadness, or neutrality;
  • In the AI Agent node, create branches in the flow to adapt the agent's responses based on the identified sentiment.

If the user types, “I’m very frustrated with the service,” the agent might respond with more empathy: “I’m sorry to hear that! I’ll do my best to help you resolve the issue as quickly as possible.”

This way, the agent becomes more attentive, improving the user experience and strengthening the bond of trust.

4. Transforming audio into text (Speech-to-Text)

You can also expand your AI Agent’s accessibility by enabling it to understand voice messages. Speech-to-Text functionality allows the agent to transcribe audio into text and interact normally with the user. 

To enable audio transcription in N8N, follow these steps:

  • add Telegram Get File node to capture the audio file sent by the user;
  • connect the node to OpenAI's Whisper API or Google Speech-to-Text to perform audio-to-text transcription;
  • send the transcribed text to the AI Agent node so that the agent can process and respond to the command normally.

With voice message understanding enabled, the user can send an audio message saying: “Schedule a meeting with Pedro tomorrow at 10 am.”
The agent transcribes the audio and executes the action on the calendar, ensuring a fluid and efficient interaction.

This functionality expands the agent's possibilities of use and creates a more dynamic service experience.

5. Automatic notifications and real-time alerts

How about taking your AI Agent to a new level of efficiency with RAG (Retrieval-Augmented Generation), allowing it to search for data from external sources before generating responses? With this technique, the agent provides updated information and contextualized responses. To do this, follow these steps to configure RAG:

  • in N8N, add the integration node with databases, external documents (PDFs) or public APIs;
  • In the AI Agent prompt, instruct the agent to query external sources before generating a response to the user;
  • test the agent with questions that require consultation in external databases.

By adding this automation, your AI Agent gains the ability to send personalized reminders like “You have a meeting scheduled for tomorrow at 9am.”, important announcements like “There’s been a change to Friday’s event.”, and strategic promotional messages like “Unmissable offer! Up to 30% off today.”

With RAG, the agent stops being just a text generator and becomes an intelligent, real-time query tool, ideal for corporate, educational and financial sectors.

 6. Implementing RAG (Retrieval-Augmented Generation)

Finally, you can take your AI Agent to the next level of efficiency by implementing RAG. To set up RAG on N8N, follow these steps:

  • add the integration node with databases, external documents (such as PDFs) or public APIs;
  • configure the AI Agent prompt to instruct it to perform external queries before formulating the response to the user;
  • take practical tests with questions that require searching for data in real time, such as:
    • “What was the revenue from the last quarter?” (consulting a database);
    • “What is the dollar rate today?” (using financial APIs).

This feature is especially useful in corporate, educational, and financial environments where decision-making depends on accurate, timely data.

4. Testing and adjustments

Now that your agent is up and running, it’s time to test it and tweak any details to improve its performance. You can use a testing checklist to check if your agent is working properly:

  • Is the agent receiving messages correctly?
  • does it respond based on the prompt instructions?
  • Can you create and list events in the calendar?
  • Are the answers clear and accurate for the user?

If the agent is returning incorrect information, adjust the prompt to better guide responses. You can also use N8N's execution history to identify failures and test the agent with different commands to validate its flexibility.

Conclusion 

By now, you’ve probably realized that creating AI Agents isn’t just a technological trend, right? Quite the opposite, it’s a real opportunity to explore new markets, automate processes and, above all, boost business in a strategic and efficient way.

Whether to improve the customer service, optimize internal flows or create scalable SaaS solutions, agents offer versatility and scalability for professionals and companies.

The best thing of all is that with No Code tools Like N8N, anyone can start this journey, even without prior programming experience. The combination of techniques such as RAG and Function Calling allows you to create powerful agents, capable of acting in different sectors and solving complex problems.

Now is the time to learn for free and get your hands dirty! In the Free AI Agent Course for Beginners, you start from scratch and create your own intelligent agent, ready to automate tasks and generate business opportunities.

If you want to delve even deeper into this content and master the best strategies for developing efficient and monetizable agents, access the full course Free AI Agent Course for Beginners 2025 | From Zero to AI Agent available on our YouTube channel.

Start your journey now by creating smart solutions that can transform your career and generate new income opportunities.

The WhatsApp API is one of the main solutions for companies that want to scale their customer service and communication automation. 

WhatsApp, being one of the most popular messaging apps in the world, allows direct and efficient interactions with customers. However, when it comes to automation and integration, using the WhatsApp API becomes essential.

So, there are two main options for this integration: the Official WhatsApp Business API and the Unofficial APIs. But which one should you choose? 

In this article, we’ll explore the differences, advantages, disadvantages, pricing models, and costs to help you make the best decision for your project. Keep reading and find out which WhatsApp API makes the most sense for your business!

Types of WhatsApp available on the market: discover the options

types of whatsapp available in the market

Before we talk about WhatsApp APIs, it is important to understand the three main types of WhatsApp available:

Personal WhatsApp

WhatsApp Personal is the traditional version of the app, used by billions of people around the world. Intended for individual users, it does not include business-oriented features or automation.

WhatsApp BusinessVersion 

Version aimed at small and medium businesses. This version has features such as a product catalog, automatic messages and business profiles, but still relies on manual interactions. 

Furthermore, it allows the simultaneous use of two numbers on the same device, one in the personal application and the other in the Business application, in a completely legal manner and in line with Meta's guidelines.

WhatsApp Business API

Unlike previous versions, WhatsApp Business API is not an application, but a cloud-based solution that allows WhatsApp integration to different systems, enabling automation and personalization of interactions.

Companies that manage a large volume of messages use this API to optimize communication with customers, ensuring efficiency and scalability. With this solution, it is possible to:

  • automate the sending of messages and notifications;
  • to create chatbots for customer service;
  • integrate WhatsApp with CRMs, ERPs and other business platforms;
  • use artificial intelligence to personalize interactions.

How does the WhatsApp Business API work?

The WhatsApp Business API acts as a bridge between different systems, allowing softwares to communicate automatically. Since it is not an application installed on the cell phone, the entire operation takes place in the cloud, ensuring scalability and reliability for companies that need high-performance communication.

Although initially aimed at developers, today there are several solutions that simplify the implementation of the WhatsApp Business API, making it accessible to companies of different sizes.

Now that we understand the concept, let's explore the differences between the Official WhatsApp API and Unofficial WhatsApp APIs.

Official API vs. Unofficial API: Know the main differences

official api vs unofficial api differences

Businesses can choose between two types of WhatsApp API for integration:

  • Official WhatsApp Business API (provided directly by Meta or licensed companies);
  • Unofficial APIs (provided by third parties, without any connection to Meta, but within the law).

Next, we will understand the main differences between them.

Official WhatsApp Business API

The Official WhatsApp Business API is provided by Meta (Facebook) itself or by licensed companies. Meta recently began offering this service directly to end users, without the need for licensed intermediaries. 

This API can be integrated directly via Facebook's Business Manager (BM), ensuring security and compliance with Meta's policies. Among the main features of the Official API:

  • integration via Facebook Business Manager;
  • mandatory use of pre-approved message templates to start conversations;
  • billing based on conversations initiated;
  • restriction on sending messages outside of Meta's rules;
  • lower risk of blocking, as long as you follow the guidelines/

Please note that Meta does not allow unrestricted sending of messages. To start a conversation, it is mandatory to use approved message templates, ensuring that the contact complies with WhatsApp policies. The template categories are:

  • marketing: promotions, coupons and offers;
  • utility: order confirmations, delivery tracking;
  • authentication: sending verification codes;
  • service: user-initiated messages at no additional cost.

After the first template is sent, the conversation can continue normally for up to 24 hours without the need for a new template.

And how does billing work on the Official API?

The pricing for the Official WhatsApp API is based on conversations initiated and varies depending on the message category:

  • marketing messages: about R$ 0.36 per conversation started;
  • utility messages: approximately R$ 0.04 per conversation initiated;
  • authentication messages: around R$ 0.015 per conversation initiated;
  • client initiated messages: at no additional cost.

Other important points about billing include the 24-hour validity for each conversation initiated by the company, which means that if it is necessary to continue the interaction after this period, a new paid template will be required. 

Additionally, starting in April 2025, authentication and utility messages sent within this 24-hour window will no longer be charged.

Unofficial APIs

Unofficial APIs are solutions offered by third parties, with no direct relationship with Meta. Although they are not licensed, many of these APIs are completely legal and follow security standards. The main characteristics of Unofficial APIs include: 

  • simplified integration via QR Code;
  • allows sending messages without the need for pre-approved templates;
  • fixed price per integrated WhatsApp number;
  • greater flexibility for shipping and automation;
  • higher risk of ban in case of spam or inappropriate use.

Unlike the Official API, which requires template approval and follows strict rules, Unofficial APIs allow messages to be sent freely, without category restrictions or prior approval. This allows for more dynamic contact with customers, ideal for companies that need freedom in communication.

And how does the billing work? Unofficial APIs?

The pricing of Unofficial APIs varies depending on the provider. Some operate with fixed monthly plans, while others charge per connected WhatsApp number.

  • some companies offer plans starting from R$99 per integrated WhatsApp number;
  • others offer packages for multiple numbers, reducing the cost per account;
  • There are open-source options, which can be used free of charge, but require their own infrastructure.

Despite the freedom offered by Unofficial WhatsApp APIs, it is essential to consider the risks involved. Since there is no direct link to WhatsApp, these APIs are more prone to blocking, especially when used for mass sending without the proper consent of users.

Furthermore, Meta support and warranty are not available, which means that any technical issues or blockages will depend solely on the API provider.

Sending messages without the recipients' authorization can also result in restrictions, compromising the company's continued communication with its customers.

So which API to choose?

which whatsapp api to choose

Choosing between the Official WhatsApp API and Unofficial WhatsApp APIs depends on your business needs. While the Official API provides greater security and compliance, Unofficial APIs offer more freedom and predictable costs.

Evaluate your options based on your message volume, need for automation, and level of risk you are willing to take.

To learn more about automation and other efficient strategies for integrate chatbots, automatic notifications and artificial intelligence to your business, explore more at our YouTube channel and in the NoCode StartUp website.

Artificial intelligence is transforming the way we interact with technology, and AI agents are one of the most powerful advancements in this area. However, to make these agents truly effective, it’s essential to train them with data specific to your business.

In this article, we will explore how to create an AI agent using the RAG technique (Retrieval-Augmented Generation) to train models with custom information. You will learn three practical ways to implement this in your own project. 

Ready? Happy reading! 

What is an AI agent and how does it work with RAG?

What is an AI agent and how does it work?

Before we get into the practical part, it is important to understand the concept of an AI agent and how it can be improved using RAG.

Basically, an AI agent is a system that can interpret commands, process information, and generate responses autonomously. To do this, it needs three fundamental elements:

  • AI model: the agent is based on models such as GPT, Llama or Claude, responsible for interpreting and generating text based on learned patterns;
  • Base prompt: these are the instructions that define how the agent should behave and structure its responses;
  • memory: essential for AI to remember previous interactions. Some agents have both short-term and long-term memory, allowing the conversation to continue.

In addition to these features, an AI agent can be even more efficient when using the RAG (Retrieval-Augmented Generation) technique, as we mentioned earlier. This means that, instead of relying exclusively on the model's prior knowledge, it can query external databases, such as documents, PDFs, Notion pages, or spreadsheets. 

In this way, an agent trained with RAG becomes an expert in specific content, ensuring more precise and contextualized responses.

Method 1: Creating an agent with Dify

method 1 creating an agent with dify

Now that you understand the basics, let's get to the practical part: how to create an AI agent trained with your own data!

One of the easiest and most effective ways to create a RAG-trained agent is by using Difyi. This tool allows you to integrate knowledge bases into your assistant quickly and intuitively.

To train your agent at Dify, follow the step by step below:

  • access the “Knowledge Base” tab within the Dify platform;
  • upload your documents, such as PDFs, HTML files, spreadsheets or web pages;
  • Dify processes the files and transforms them into numeric vectors, converting the textual content into a format that AI can interpret efficiently.

This process is known as embedding, in which the tool structures the data on a vector basis, allowing the AI to search and retrieve the most relevant information whenever a question is asked.

Additionally, Dify makes it easy to create virtual databases by organizing knowledge into chunks of information. This way, when a user asks the agent a question, the agent quickly identifies which chunk of text best fits the desired answer.

With Difyi, you can create specialized agents for different purposes, such as:

  • customer support assistants, who access FAQs and technical manuals;
  • customer service chatbots, which answer questions about products and services;
  • sales agents, which use strategic information to personalize approaches.

The best part? Dify automates this entire process behind the scenes, making implementation simple and practical.

Method 2: Creating an agent with OpenAI Assistants and RAG

method 2 creating an agent with openai assistants

Another efficient way to train an AI agent with RAG is to use OpenAI Assistants. This solution allows you to create custom assistants, define specific behaviors, and incorporate documents so that the AI can query and respond accurately.

Unlike Dify, which automates much of the process, OpenAI offers greater control over the agent’s settings. To create your assistant using this tool, follow the steps below:

  • access the OpenAI platform and go to the “Assistants” tab;
  • create a new wizard, defining a name, description and specific instructions;
  • choose an AI model, such as GPT-4 Turbo, to ensure more complete and contextual answers;
  • Upload files that he will use as reference, such as technical manuals, internal documents, or knowledge bases.

When documents are added to the platform, OpenAI transforms this content into a vector database. This way, the agent can consult the information whenever necessary, without relying solely on the model's pre-trained knowledge. 

This allows it to provide more personalized and up-to-date responses without requiring a complete AI re-processing. Additionally, OpenAI manages all the infrastructure needed to store and retrieve this information, making it easy to implement for those who don’t want to set up their own database.

One of the main advantages of this approach is its ease of implementation, as OpenAI takes care of the technical part, making the process simple and intuitive. In addition, the model guarantees high accuracy, combining the power of GPT-4 Turbo with specific information about your business, making the assistant much more effective. 

If your goal is to create a specialized AI agent without having to set up an advanced technical environment, OpenAI Assistants can be a great choice.

Method 3: Creating an agent with N8N and Supabase

method 3 creating an agent with n8n and supabase

The third way to create an AI agent trained with RAG is by using the integration between N8N and Supabase. This approach allows greater control over the data and optimizes the search for relevant information within the vector database.

While tools like Dify and OpenAI Assistants simplify the process, using N8N in conjunction with Supabase offers more versatility and reduces operational costs by allowing the framework to be fully configured and managed within your own environment.

To create an AI agent trained with this combination, follow the steps below:

  • configure the vector database in supabase to store the reference documents;
  • upload the files that the agent will use as a knowledge base, such as manuals, FAQs or technical ebooks;
  • integrate Supabase with N8N to enable AI to query data and provide contextualized answers;
  • develop automated flows in N8N to structure agent interactions with users;
  • optimize agent responses by ensuring that they can access the most relevant blocks of information within the database.

But why use N8N and Supabase? with RAG?

Unlike other solutions, this approach allows for an advanced level of customization and control over the vector database. When a user asks the agent a question, it fetches the most relevant vector of data from Supabase, ensuring that the answer is based on the stored documents.

Additionally, N8N allows you to connect the AI agent to different applications, such as Whatsapp, Slack and Google Drive, expanding the possibilities of use and automation. This flexibility makes the model ideal for companies that need a highly specialized agent.

Among the main advantages of this implementation, the following stand out:

  • greater control over datas, allowing adjustments and customizations as needed;
  • cost reduction, as Supabase replaces paid solutions for vector storage;
  • advanced automation, with intelligent flows and integrations in N8N;
  • scalability, allowing the knowledge base to grow according to business needs;
  • greater efficiency, as the agent accesses information directly from the vector database, without relying solely on the AI model.

If you are looking for flexibility and cost reduction, N8N + Supabase is a powerful solution for training specialized AI agents with RAG.

Conclusion

Training an AI agent with your own data is an essential strategy for obtaining more accurate responses aligned with the context of your business. With RAG, you can transform internal files and documents into structured knowledge for AI, optimizing processes and improving the user experience.

If you want to dive deeper into the topic and learn how to create your own AI agents, check out the complete N8N course at NoCode Startup and take your automation to the next level!

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