Beyond Vibe Coding: Why Software Engineering Is Essential in Modern Web Applications

Introduction

Web applications have become an important part of our everyday lives. From online banking and e-commerce platforms to university registration systems, hospital management systems and social media, web applications help individuals and organizations perform tasks more efficiently.

As technology continue to evolve, Artificial Intelligence (AI) tools have made it easier and faster to develop web applications. Developers can now describe what they want in ordinary language and allow AI tools to generate code. This approach is commonly known as vibe coding.

Although vibe coding makes software development more accessible, it raises an important question: Can an application that looks functional actually be considered good software without proper Software Engineering practices?

The answer is no. Building a successful web application requires more than writing code or generating an attractive user interface. It requires proper planning, design, testing, security and maintenance.

1. Understanding Software Engineering in Web Applications

Software Engineering is the systematic application of engineering principles, methods and techniques to the development, operation and maintenance of software.

In Web Application Development, Software Engineering provides a structured approach to building applications that are reliable, secure, efficient, scalable and easy to maintain.

For example consider a university developing an online course registration platform. The application must allow students to log in, view available courses, register for courses and check their registration status.

Simply writing code to create these features is not enough. Developers must also consider:

• Requirements analysis: Understanding what students, lectures and administrators need.

• System design: Planning the database, application architecture and user interface.

• Implementation: Writing organized and maintainable code.

• Testing: Ensuring that registration, authentication and other features work correctly.

• Security: Protecting student records and preventing unauthorized access.

• Maintenance: Updating the application and correcting problems after deployment.
  These activities demonstrates why Software Engineering is essential throughout the development lifecycle.

2. The Relevance of Software Engineering in Modern Web Applications

Software Engineering plays several important roles in developing successful web applications.

A. Improving Software Quality
Software Engineering encourages developers to follow established standards and best practices. This helps produce applications that are reliable, efficient and user-friendly.
A properly engineered application should perform its intended functions without frequent errors or unexpected failures.

B. Enhancing Web Application Security

Web applications often process sensitive information such as names, passwords, financial details and personal records.
Software Engineering promotes secure coding practices, authentication, authorization, data validation, encryption and security testing.
Without these measures, applications may become vulnerable to cyberattacks.

C. Supporting Scalability

A web application may initially serve a small number of users but eventually attract thousands or millions.
Software Engineering encourages developers to design systems that can accommodate increasing users, transactions and data without significant performance problems.

D. Reducing Development and Maintenance Costs

Proper planning, documentation and testing help identify problems before they become expensive to fix.
Well-structured software is also easier for developers to understand , modify and maintain.

E. Improving User Experience

Software Engineering ensures that applications are designed around users' needs.
Through requirements gathering, interface design and usability testing, developers can create applications that are accessible, understandable and convenient to use.

3. Understanding Vibe Coding

Vibe coding is an approach to software development where developers use natural-language instructions to guide AI tools in generating and modifying code, sometimes with the little direct examination of the generated source code.

Tools such as ChatGPT, Github Copilot, Claude and other AI-powered development assistants can generate HTML, CSS, JavaScript, database queries and even complete application structures.

For example, a developer might enter the following prompt: "Create a responsive, product listing, a shopping card and payment functionality."

An AI tool may generate a working-looking application within minutes. This can be useful for experimentation, learning, prototyping and reducing repetitive coding tasks.

However, the danger begins when the developers assume that generated code is automatically correct, secure and ready for production. AI can generate the code quickly, but generating code is not the same as engineering a reliable software system.

4. The Demerits and Dangers of Vibe Coding

Although vibe coding has advantages, relying on it without proper Software Engineering practices introduces several risks.

A. Security Vulnerabilities

AI generated code may contain security weaknesses such as SQL injection, Cross-Site Scripting (XSS), weak authentication and broken access control. For example, an AI-generated login system may appear functional but fail to properly protect user passwords or verify access permissions.

An attacker could exploit these weaknesses to access private information or manipulate application data.

B. Poor Code Quality and Maintainability

AI tools may generate duplicated, unnecessarily complicated or poorly organized code. As an application grows, developers may struggle to understand how different components interact.

This creates technical debt, making debugging, upgrading and maintaining the application more difficult.

C. Incorrect or Incomplete Functionality

AI-generated applications do not always behave as expected. A website may display a registration form successfully but fail to save information correctly in a database.

Similarity, a payment interface may look complete without implementing secure paying processing. Without proper testing, these problems may remain undiscovered until real users encounter them.

D. Data Privacy Risks

Some developers may unknowingly expose sensitive information by entering passwords, API keys, database credentials or private business information into unapproved AI tools.

If such information is mishandled, it may expose users and organizations to data breaches.

E. Dependency and Supply Chain Risks

AI-generated code may recommend incorrect, outdated or unsafe third-party packages. Using unverified dependencies can introduce malicious code or security vulnerabilities into a web application.

A particularly concerning example is slopsquatting, where attackers register packages names that AI tools may mistakenly generate, hoping developers will install them.

F. Lack of Proper Documentation

When developers rely heavily on AI-generated code without understanding the implementation, they may fail to document important design decisions, system functionality and dependencies.

This makes it difficult for other developers to take over the project or resolve future problems.

G. Overdependence on AI

Developers who accept generated code without understanding it risk losing important problem-solving and debugging skills.

Software development requires logical reasoning, critical thinking and the ability to identify problems. AI should support these abilities rather than replace them.

5. The Dangers of Developing Web Applications Without Software Engineering

The risks of neglecting Software Engineering extend beyond vibe coding. Even manually written applications can fail when developers ignore engineering principles.

Consider an online banking application developed without proper requirements analysis, security testing or system design. Such an application could experience:

• Unauthorized access to customer accounts.

• Incorrect financial transaction.

• Loss or exposure of customer information.

• Frequent system failure.

• Poor performance during high traffic.

• Difficulty fixing errors and introducing improvements.
  These problems can lead to financial losses, legal consequences, reputational damage and loss of customer trust.

The OWASP Top 10:2025 identifies major web application security risks, including broken access control, security misconfiguration, software supply chain failures, cryptography failures and injection.

This demonstrates why security must be considered throughout the software development process rather than added as an afterthought.

6. How Developers Can Use AI Responsibly While Practicing Software Engineering

The solution is not to reject AI coding tools. Instead, developers should combine AI assistance with established Software Engineering practices. The following measures can help:
1. Gather requirements: ** Clearly understand the application's purpose and user expectations before generating code.
**2. Design the system: Plan the architecture, database, user interface and application components.
3. Review generated code: Understand what the AI produces instead of blindly accepting its suggestions.
4. Perform software testing: Conduct unit, integration, system, performance and security testing where appropriate.
5. Follow secure coding practices: Validate user input, protect credentials and enforce proper access controls.
6. Use version control: Track code changes and make it easier to identify and reverse problematic updates.
7. Document the application: ** Maintain clear technical documentation for future developers.
**8. Deploy carefully: Test applications in a development or staging environment before releasing them to real users.
9. Maintain continuously: Monitor performance, fix vulnerabilities and update dependencies.

The National Institute of Standards and Technology (NIST) provides a Secure Software Development Framework (SSDF) that encourages organizations to integrate security practices into the software development lifecycle. These principles remain relevant whether code is written manually or generated with AI.

7. The Future of Software Engineering in the Age of AI

AI is changing how developers build software, and its influence will continue to grow. However, the future of software development should not be about replacing Software Engineers with AI tools. It should be about improving productivity while maintaining professional engineering standards.

Developers must understand programming concepts, system architecture, databases, cybersecurity, testing and maintenance, even when AI assists with implementation. An effective Software Engineer should know how to use AI, evaluate its output, identify potential risks and take responsibility for the final application.

AI may accelerate development, but engineering knowledge determines whether the resulting software is suitable for real-world use.

Conclusion

Software Engineering remains essential in Modern Web Applications Development because it provides the principles and practices required to build reliable, secure, scalable and maintainable applications.

Vine coding offers opportunities to accelerate development, encourage experimentation and make programming more accessible. However, using AI-generated code without proper understanding, testing, security reviews and maintenance can expose applications to serious technical and security risks.

The real problem is not the use of AI in software development; it is the assumption that AI-generated code automatically represents quality software.

As future Software Engineers and Web Developers, we must understand that building an application is not just about making it work; it is about making it work correctly, securely, reliable and sustainably. The best approach is therefore to combine the speed of AI with the discipline of Software Engineering.

References

1. National Institute of Standards and Technology (NIST). Secure Software Development Framework (SSDF). https://csrc.nist.gov/projects/ssdf
2. OWASP Foundation. OWASP Top 10:2025. https://owasp.org/www-project-top-ten/
3. Canadian Centre of Cybersecurity. Managing Security Risks in vibe coding. htpps://www.cyber.gc.ca/en/guidance/managing-security-risks-vibe-coding-itsm60043
4. National Cyber Security Centre (NCSC). The vibe coding spectrum: A risk-based approach to AI-assisted software development. https://www.ncsc.gov.uk/