How to Prototype Websites with Figma

December 17, 2024
4 min

Introduction to Figma for Website Prototyping

When you use Figma to create website prototypes, you can create designs that simulate the user experience. This allows you to tweak the prototype and share it with your team for quick and effective feedback. Prototyping is therefore an essential step in validating ideas and improving the usability of your website before moving on to the development phase.

In Figma, designers can easily arrange design elements, allowing them to clearly visualize what the final layout will look like. Additionally, they can add interactivity, such as clicks and transitions, which creates a more realistic user experience. This makes it easy to create fast and effective prototypes, helping teams save time and resources in the design process.

Steps to start prototyping

To create website prototypes with Figma, the first step is to plan the overall layout of your site. Define essential elements, such as headers, footers, and menus, and arrange them on the canvas. Once you have the basic structure in place, you can design the individual screens of your site, ensuring that navigation between them is intuitive and fluid. Figma provides a number of tools for aligning, distributing, and grouping elements so that your layout looks well organized.

The next step is to add interactivity to the prototypes. In this sense, Figma allows you to create links between different screens, simulating real-world website navigation. In addition, designers can create clickable areas on buttons, images, and other elements to make it easier to visualize how users will interact with the website. On the other hand, they can also fine-tune the interactions, adding smooth transitions or animations to make the prototype more dynamic and engaging.

Figma also facilitates real-time collaboration, allowing multiple team members to work together on the same prototype and provide instant feedback. This makes the design process more efficient, reducing the need for lengthy meetings or revisions. With Figma, you can access your prototypes from anywhere, at any time, making remote work and international collaboration easier.

Top features for website prototyping

Figma offers several features that facilitate the creation of website prototypes, making the process faster and more intuitive. In this context, among the main functionalities, the possibility of creating reusable components and integration with plugins that add extra functionalities stand out. In addition, designers create components, such as buttons, menus and icons, that can be reused in different parts of the prototype, ensuring consistency in the design.

Additionally, it allows the use of grids and guides to align website elements, which helps maintain aesthetics and visual balance. Designers use these features to create clean and professional designs, eliminating the need for external tools. Another important benefit is the support for interactive prototyping, allowing you to simulate complex website behaviors, such as drop-down menus and transition animations.

With Figma, you can export prototypes in multiple formats, making it easy to share with your team or clients. The tool also offers a free version with essential features, which allows you to start creating prototypes without any upfront costs. For those looking to expand its functionality, Figma also offers paid plans with additional features, such as creating design libraries and advanced version controls.

Integrating Figma with other development tools

When prototyping websites with Figma, it may be necessary to integrate the design with other tools to continue developing the website. For example, designers can combine Figma with No-Code platforms like Flutterflow and Bubble to turn prototypes into functional websites without resorting to complex coding. These tools NoCode facilitate the development of websites from prototypes created in Figma, allowing you to quickly create interactive pages.

The use of Figma can also be complemented with other design platforms, such as web or framer, which offer specific functionality for creating interactive and dynamic prototypes. Integrating Figma with these tools can improve collaboration between design and development teams, making the process more agile and efficient. Figma's flexibility allows designers to create visually striking prototypes that can be easily converted into functional websites using other tools.

Another advantage of using Figma in conjunction with platforms like Make Integromat is the automation of design and development processes. These integrations allow you to create efficient workflows, saving time and effort in prototyping and deployment.

Testing and tweaking website prototypes with Figma

One of the main advantages of using Figma for website prototyping is the ability to test and tweak your designs before moving them into development. In Figma, you can share your prototypes with users and team members to get feedback and make quick adjustments. The interactivity of prototypes allows users to test the navigation and functionality of your site, providing valuable insights into its usability and user experience.

Additionally, Figma facilitates collaboration by automatically updating all team members with any changes made to the prototype. This makes the review process more efficient, allowing you to quickly improve your design based on feedback. This way, prototypes created in Figma are constantly tweaked, ensuring that the final product meets the needs of your users.

Conclusion

Creating website prototypes with Figma is a great way to plan and test a website design before implementing it. The platform offers a number of powerful features, from creating reusable components to integrating with development tools like Flutterflow, Bubble and Framer. By using Figma to create interactive prototypes, you can improve the efficiency of the design process and ensure a better experience for end users.

If you want to dive even deeper into using Figma and other design and development tools, be sure to check out Figma's YouTube channel and website. NoCode StartUpThere, you will find exclusive content and tutorials to help you turn your ideas into reality!

Known as “Castelo”, he discovered the power of No-Code when he created his first startup entirely without programming – and that changed everything. Inspired by this experience, he combined his passion for teaching with the No-Code universe, helping thousands of people create their own technologies. Recognized for his engaging teaching style, he was awarded Educator of the Year by the FlutterFlow tool and became an official Ambassador for the platform. Today, his focus is on creating applications, SaaS and AI agents using the best No-Code tools, empowering people to innovate without technical barriers.

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

AI Software Development in the Financial Sector

Creating AI-based solutions in the financial context requires robustness, security, and adaptability. Developing this type of software requires an architecture that is prepared to handle large volumes of data, continuous learning, and the ability to provide accurate insights.

In addition, systems need to be able to handle sensitive data, integrate with multiple sources (such as banks, brokerages, and ERPs), and adapt quickly to regulatory changes in the industry. Flexibility and modularity are core elements of any AI architecture for finance.

Integration with Existing Infrastructures

Much of AI’s success in the financial sector depends on its integration with legacy systems. This includes internet banking platforms, CRMs, payment gateways, and compliance tools. Using NoCode platforms such as make up or N8N allows you to create effective connections without the complexity of traditional development.

By the way, if you want to experience in practice how to integrate financial flows with AI, No-Code Start-Up provides a free N8N course with full video on YouTube. It's a great opportunity to explore real automations and understand how to structure secure and intelligent integrations in an accessible way.

With this approach, banks and fintechs can activate intelligent flows based on real data, such as automatic sending of alerts, personalized segmentations and recommendations based on consumer behavior.

Challenges in AI Development for the Financial Sector

Despite the enormous potential, there are challenges that need to be considered. Among the most relevant are:

Data quality: models are only effective if fed by clean and organized data.
Explainability: It is essential to understand how the AI arrived at a particular recommendation.
Cultural resistance: Traditional teams may resist adopting automation and algorithm-based decisions.

As highlighted by Deloitte, the combination of data governance, team training and ethical monitoring of AI is essential to mitigate risks and generate consistent results.

Security and Regulatory Compliance

The financial sector is one of the most regulated in the world. Therefore, all AI applications must comply with standards such as LGPD, GDPR and Central Bank regulations.

The adoption of good practices Data Privacy by Design, end-to-end encryption and role-based access control are just some of the basic requirements. Platforms such as Xano offer robust infrastructure with a focus on security for those who want to develop financial backends with AI.

Digital security illustration with padlock and financial data, symbolizing protection and compliance in AI application

Software Scalability and Resilience

As AI becomes a critical part of operations, it is necessary to ensure that systems are scalable and resilient. This means being able to grow as demand dictates, without compromising performance or security. Cloud computing and the adoption of microservices are essential strategies in this journey.

Companies like Goldman Sachs and Bank of Brazil have already demonstrated, in different contexts, how AI models can be deployed gradually, safely testing hypotheses before scaling to the entire operation.

AI Agents for Finance: Use Cases and Applications in the Financial Sector

1. Automated credit analysis

Companies like Credits use AI to evaluate hundreds of variables — including banking history, spending habits, and public data — to offer personalized credit. This reduces default rates and expands access to credit in a fairer way. According to McKinsey, automation can reduce analysis time by up to 70%.

2. Fraud prevention

O Bradesco and other institutions have implemented machine learning models that detect fraud based on behavioral patterns. When a transaction deviates from the pattern, the system triggers an automatic block or sends an additional verification to the user. According to Visa, the use of artificial intelligence helps prevent fraud totaling approximately US$14T25 billion.

3. Automated investment management

Robo-advisors like the ones from XP Investments use algorithms that analyze investor profiles, financial goals and market conditions to assemble and rebalance portfolios autonomously. CB Insights highlights that these systems are democratizing access to quality financial services, previously restricted to large investors.

4. AI-powered customer service

O Itau has incorporated AI into its digital channels, allowing customers to renegotiate debts, request second copies of bills or consult invoices using natural language. This reduces response time, improves customer experience and frees up human teams for more complex cases. According to Accenture, up to 80% of first-level banking interactions can now be automated using artificial intelligence.

5. Cash flow forecast

Financial management startups use AI agents for finance that integrate data on accounts payable and receivable, seasonality and market trends to predict cash flow for the coming months with high accuracy. Based on this information, more assertive decisions can be made. Harvard Business Review reinforces that this approach reduces the margin of error in financial projections and improves strategic planning.

The Role of AI Agents for Finance

Among all the applications, the AI agents for finance stand out for their versatility and accessibility. They function as intelligent “copilots”, performing tasks such as:

Automatic generation of financial reports
Sending alerts about targets or deviations
Predictive profitability analysis

Using platforms such as Dify and OpenAI, it is possible to configure these agents with natural language, making them easier to use even for those without technical training. This expands access to data intelligence in the financial sector.

The Future of AI in the Financial Sector

Artificial intelligence in the financial sector is no longer a distant promise — it is present in strategic decisions, customer service, and risk management. The adoption of technologies like AI agents for finance represents a leap forward in digital maturity. As technical challenges are overcome and platforms become more accessible, companies of all sizes will be able to use AI not only to automate, but to evolve.

Organizations that master the use of AI ethically, safely, and strategically will be ahead in delivering value and conquering the market. The future of finance is predictive, integrated, and data-driven — and it starts now. Want to learn how to build your own AI-powered financial agents without coding? Access the AI Agent Manager Training and discover the most practical way to apply all this in your context.

May 13, 2025
5 min

Matheus Castelo

How AI is changing the market: challenges and opportunities

How AI is changing the market can be observed in practically all sectors of the economy, and this change is intensifying every day. Artificial intelligence (AI) is being recognized as a disruptive force that is profoundly reshaping the global market. From simple tasks to complex decisions, it has been integrated into processes in various sectors, transforming the way people work, consume and manage businesses.

Furthermore, when observing the effects of this transformation, it becomes clear how much the job market is being reconfigured: new opportunities arise, some professions lose ground and others adapt or are reborn with the support of technology, which demonstrates how AI is changing the market in a broad and profound way.

How AI is changing the job market

AI is accelerating the automation of repetitive and operational tasks. AI systems are already being used to efficiently perform:

Customer service with chatbots.
Predictive data analysis for sales and marketing.
Automated financial and audit processes.
Inventory control and logistics.

These changes not only reduce operational costs, they also require the workforce to be retrained for new roles, which reinforces how AI is changing the job market with great intensity.

Representation of people and artificial intelligence collaborating in different professions

Professions affected by artificial intelligence

According to PwC's report on the future of work (source), it is estimated that up to 30% of human tasks could be automated by the mid-2030s. This data shows, in practice, how AI is changing the job market and skills requirements.

Some of the roles most impacted by AI include:

Telemarketing operators
Administrative assistants
Data Analysts (some tasks being replaced by generative AI)

On the other hand, new functions emerge, such as:

Prompt Engineers
Automation experts with NoCode
Conversational Experience Designers
Intelligent Agent Managers

Those AI agents, for example, have been increasingly used in companies seeking to automate decisions and perform tasks with minimal human intervention. According to an analysis of the The Verge, large companies such as OpenAI, Google and DeepMind are investing heavily in the development of these systems, which can already act independently in complex corporate processes. They are designed to operate autonomously, learn continuously and integrate with other technologies — which makes them key players in the ongoing digital transformation.

What's Happening Now: How AI is Changing the Marketplace in Numbers

The AI market is experiencing exponential growth. The sector is estimated to surpass US$ 500 billion in value by 2027. There is a global race for innovation, with startups, large companies and governments investing heavily in:

Generative models (like ChatGPT)
Robotic Process Automation (RPA)
Artificial intelligence applied to health, education, law and agribusiness

This movement demonstrates how AI is being positioned as a strategic asset for growth and competitiveness.

What are the negative aspects of AI in the job market?

Despite promising advances, important challenges also arise:

Structural unemployment: functions terminated without sufficient time for requalification
Digital inequality: not everyone has access to technological education
Technological dependence: companies become hostages of platforms and algorithms
Ethical and privacy issues: inappropriate use of data and biased automated decisions

These factors require public policies, business leaders and civil society to debate limits, transparency and responsibilities in the use of technology.

People using AI tools in a modern workplace

Opportunities and the future of work with AI

The key is in the conscious adaptation. The future of work will be driven by:

Continuous learning and professional requalification
Mastery of AI tools and NoCode platforms
Creating new business models based on data and automation
Development and management of autonomous AI agents

Increasingly, professionals and companies will need to adopt a stance proactive and experimental, turning AI into an ally.

Recommended courses:

AI and entrepreneurship: new market frontiers

Artificial intelligence is not only transforming the traditional job market, it is also paving the way for new business models. Digital entrepreneurs are using AI to create scalable products such as intelligent assistants, recommendation systems, and data-driven SaaS platforms. No-code tools combined with AI agents are enabling the emergence of lean, highly automated, and highly personalized startups.

A great example is the AI-based micro-SaaS, which solve very specific problems and can be created by a single person. Platforms like Bubble, FlutterFlow and Make, integrated with OpenAI models, make this scenario not only possible, but accessible.

For those who wish to explore this new territory, we recommend SaaS IA NoCode Training, designed to transform ideas into digital products using the power of artificial intelligence.

How AI is changing the market and shaping the future

Artificial intelligence is changing the market in an irreversible way. It is not only a technological revolution, but also a social, professional and economic transformation. The question is no longer “if” AI will impact your work, but “how will you position yourself in this new era”.

The good news is that there have never been so many accessible tools for those who want to learn AI in practice.

See all No Code Start Up training and courses

May 6, 2025
4 min

Matheus Castelo

AI for Lawyers: Automate Legal Tasks Efficiently

Artificial intelligence (AI) is no longer a distant promise. It is already transforming the way solo lawyers and small law firms operate. With affordable tools, it is possible to automate repetitive tasks and focus on what really matters: winning more clients and delivering high-quality service. AI agent for lawyer is the key to this revolution, offering practical solutions to everyday challenges. Each AI agent for lawyers acts as a virtual legal assistant, ready to optimize your routine.

What is an AI Agent and How Can It Help Independent Lawyers?

One AI agent for lawyer is an automated system that performs specific tasks on its own, based on predefined commands and machine learning. For lawyers, this means:

Reduction of time spent on manual and bureaucratic tasks.
24/7 support with virtual assistants who answer common questions.
Greater productivity, with a focus on strategic activities.
Possibility of customizing legal flows according to the area of activity.

These agents can be integrated with various systems and platforms, enabling everything from the automatic drafting of contracts to the management of deadlines and hearings. In addition, they allow for the analysis of documents with greater speed and precision, reducing errors and rework. The great advantage is that, with no-code tools such as Agents with OpenAI Course and Free Dify Course, any lawyer can create their own AI agents without having to program.

Lawyer using AI agent to automate legal tasks in the office

Real Examples of Legal Automation with AI Agents for Lawyers

1. Automatic Generation of Petitions and Contracts

With tools like make up integrated into the Google Docs, it is possible to automate the creation of petitions. Imagine filling out a form and having the document ready in minutes.

2. Personalized Legal AI Agents

Much more than a simple chatbot, a AI agent for lawyer is able to continually learn from interactions, refining its responses and becoming more effective over time. Using ChatGPT integrated into the Dify, you can create an agent who not only answers common questions about labor rights or procedural deadlines, but also identifies service patterns and suggests improvements in responses. This agent can be trained with data from your own office, offering a highly personalized and efficient service, constantly evolving according to your client's needs.

3. Review and Analysis of Legal Documents

AI tools allow you to perform automatic readings, generate summaries and highlight important points in contracts and processes.

Legal document automation with AI agent assisting lawyers

AI Solutions for Lawyers: What You Need to Know

Dify: Creates tailor-made legal assistants.
make up: Automates service flows and document generation.
Agents with OpenAI: Develop custom agents for specific tasks.
N8N Course: Powerful tool for creating complex legal automation flows.

Relevant Tools in the Lawyer AI Agent Market

Document Review and Analysis

Kira Systems – extracts and analyzes complex contracts.
Luminance – automated review with AI, used in due diligence.
LegalSifter – reviews contracts and suggests improvements based on AI.

Automated Legal Research

JusIA – legal questions, analyze references and create document
LegalAI – write objections, initial petition with AI.
CaseText – AI-powered legal research (English).
LexisNexis – global AI-powered legal research platform.
Westlaw – advanced legal research, powered by AI.

Legal Document Automation

LawGeex – automatically reviews contracts, with AI.
DocuSign CLM – complete automation of contracts.

Legal Chatbots and Customer Service

DoNotPay – chatbot that solves simple legal questions (English).
IBM Watson Legal – AI solutions and chatbots for the legal sector.

Office and Process Management

ProJuris – Brazilian legal software with AI and automation.
Advbox – automation of flows and digital legal management.

Predictive Analysis and Jurimetrics

Data Lawyer Insights – jurimetrics applied to Brazilian law.
Tech Preamble – predictive analysis and jurimetrics for lawyers.

Building an AI Legal Agent Using N8N and Dify

To create a more robust lawyer AI agent, you can integrate the N8N, Dify and ChatGPT. Check out this guide:

Map Your Office's Needs: Define what functions the bot needs to have: answer questions, send documents, schedule appointments.
Create FAQs and Flows: List frequently asked questions and response paths. In Agents with OpenAI Course you learn how to model these flows.
Configure Dify: In the dashboard, create your bot based on the questions and answers, adjusting the behavior.
Use N8N for Integration: Connect Dify to other platforms like WhatsApp, Google Calendar or Docs. In N8N Course you learn how to create these integrations.
Automate Repetitive Tasks: Use N8N to trigger automatic responses, save data, and send alerts.
Test and Improve: Put the bot into action, collect customer feedback, and optimize the system.

With this integration, your legal chatbot will not only answer questions, but also perform automatic tasks, increasing your level of service and productivity.

Will AI Replace Lawyers? No, But It Will Replace Those Who Don’t Use AI

Artificial intelligence is here to be an ally, not a replacement. Today, thousands of lawyers are already using AI agents to optimize their day-to-day activities. Each AI agent for lawyers is designed to assist in specific legal tasks, without replacing human critical reasoning and strategy. For example, law firms are automating the generation of standard contracts, reducing document production time by up to 70%. Lawyers are also using AI agents for lawyers to review large volumes of documents in due diligence processes, finding critical information in minutes. In addition, legal chatbots, such as AI agents for lawyers, allow you to serve customers 24/7, answering simple questions and directing them to specialized assistance when necessary.

Learn How to Create Your Own AI Agents and Multiply Your Results

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