How to create responsive apps web in FlutterFlow is a question for many people nowadays. After all, most projects are used on Web and Mobile.
In this video I explain in detail all the innovation of Web Apps in FlutterFlow.
You will learn all about Flutter and its revolution in cross-platform web creation apps, examples of Web Apps in FlutterFlow and when to use FlutterFlow for your web project.
In addition, we will get inside the tool and learn about a practical Web App project in FlutterFlow.
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.
The market is changing – fast. Artificial intelligence is no longer a trend, it has become a necessity. Companies are cutting costs, optimizing operations and looking for specialists to implement AI in their daily lives. And this is exactly where the AI profession comes in. AI Manager Course.
NoCode AI Manager Course: What it is, Who it is for and What its Objectives are
THE AI Agent Manager Training It is aimed at anyone who wants to enter the field of artificial intelligence in a practical way, without needing to know how to program.
The main objective is to train professionals capable of delivering automation and real solutions for companies using NoCode tools.
It is ideal for both those who want to offer services and those who want to open their own AI agency.
The training proposal is clear: enable you to bill more than R$14,000 per month working with intelligent solutions — a market that is only growing.
The training is structured in complete knowledge trails, with content organized by theme and level of mastery:
Topics covered:
Fundamentals from Zero to Advanced
Mastering Automations with AI
Creating and Selling AI Agents to Companies
Applied Prompt Engineering
Using NoCode tools like n8n, Dify, Make, OpenAI and more
Integration with WhatsApp, CRMs and payment gateways
Ready-to-clone and apply templates
When you sign up, you get:
8 complete formations, including SaaS AI and technical courses from NoCodeStartUp;
Access to exclusive community, active and with direct support from instructors;
1 year full access, including the Make paid plan;
NoCode Match, a hub of real opportunities in the AI and automation market.
Differences between AI Manager Training and Other Courses
Unlike many generic courses, this training was designed as a complete ecosystem of learning and practical application, with total focus on generating results for the student.
100% classes structured, edited and with step-by-step teaching methods
Mentors present, community engaged
Trail with beginning, middle and end, organized with teaching methodology
Real opportunities and networking with companies and devs
Masterclasses with experts who already apply AI in agencies and companies
What is the cost of the AI Manager Course and Access Conditions?
The promotional value of the training is R$ 1,497 in cash or in up to 12 installments of R$ 157.53 on the credit card.
Full access for 12 months
7-day money-back guarantee
Updates included at no additional cost
FAQ: Main Questions About the AI Manager Course
Do you need prior knowledge? No. All content is designed for absolute beginners in AI and NoCode.
How long do I have access? You will have 1 year of access complete to the platform and updates.
Can I ask for a refund if I don't like it? Yes. You have 7 days warranty to test and cancel without bureaucracy.
I'm a PRO student. Do I already have access? Yes. NoCodeStartUp PRO subscribers have unlimited access to the training.
What are the extra costs for tools? The only initial cost for teaching purposes is US$ 5 to use OpenAI API.
How long will it take for me to see results? In the first few days, you can create and test your first AI agent.
What do I get when I purchase? Immediate access to all tracks, bonuses, community, templates, Masterclass and tools.
How to Become an AI Manager?
To become an AI manager, the ideal is to start with training that combines practice and theory in an accessible way.
The NoCodeStartUp course focuses exactly on that, teaching how to create automations with AI without requiring prior programming knowledge.
You'll learn everything from the fundamentals to delivering real solutions using platforms like n8n, Make, Dify, Zapier, and OpenAI.
How Much Does an AI Manager Earn?
According to the market itself and reports from students, an AI manager can earn above R$10 thousand per month, working with consultancies, creating personalized agents or recurring services via intelligent automation.
Which Course Should I Take to Work with AI?
If you are looking for a practical, up-to-date course, with a strong connection to the market and no programming requirements, AI Agent Manager Training is one of the most complete currently.
It combines technical content with real-world application so you can start working quickly.
Invest in Yourself: Become a Professional AI Manager
If you are looking for a way to stand out in the digital market, enter the technology area without having to program and act with something that is growing rapidly, this course is a smart shortcut.
The AI Agent Manager Training provides a clear path, real support and applicable tools for you to work with AI in a professional manner.
It is applied learning with a total focus on solving real problems using artificial intelligence.
Artificial intelligence (AI) is reshaping the way the financial sector operates, from risk analysis to the automation of complex processes. More than a trend, AI has become a strategic tool for financial institutions that want to increase their efficiency, reduce costs and offer personalized experiences. Within this scenario, the use of AI agents for finance has been gaining ground as a practical and accessible application for companies of all sizes.
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.
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 toVisa, 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.
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.
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.
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.
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.
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