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Software testing after Vibe Coding: why the era of AI development makes QA even more important

Vibe Coding speeds up development but increases risks

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Today, more and more software products are being created using AI tools and an approach already known as Vibe Coding. A developer, entrepreneur, or startup team formulates an idea based on intuition, quickly generates code using AI, and ends up with a working product: a website, a CRM system, a Telegram bot, a mobile app, or a SaaS service.

At first glance, this looks like the ideal development model: fast, cheap, and without lengthy design phases. But this approach has a significant drawback–the requirements for technical documentation become significantly lower. Many decisions are made “on the fly,” without a detailed description of the logic, system behavior scenarios, and edge cases.

As a result, the product may indeed “work,” but the question remains: does it work correctly? This is precisely why software testing after Vibe Coding becomes no less important, and in many cases – even a more critical stage of development.

Why AI code requires additional testing

Modern AI tools are capable of generating large amounts of code very quickly. However, the speed of generation does not guarantee the quality of the architecture, logic, or system stability.

In practice, the following issues often arise after Vibe Coding:

  • functions behave erratically;
  • logic is inconsistent across different parts of the system;
  • hidden errors appear in complex user scenarios;
  • business logic is disrupted;
  • the interface behaves unpredictably;
  • the system works correctly only in an “ideal” scenario;
  • exceptions and non-standard user actions are not handled;
  • issues arise with integrations, access roles, APIs, and notifications.

This is particularly noticeable in complex projects involving:

  • a large number of screens;
  • different user roles;
  • CRM logic;
  • payment integrations;
  • process automation;
  • database operations;
  • complex user scenarios.

AI is capable of quickly creating functionality, but verifying the correctness of that functionality remains an engineering task.

Software testing after Vibe Coding: why the era of AI development makes QA even more important

Why manual testing is becoming particularly relevant again

Despite advances in automation and AI, it is manual testing that allows us to understand how user-friendly, logical, and aligned with business expectations a system truly is.

Automated tests check the code. Manual testing checks the product.

It is the QA specialist or analyst who is able to identify:

  • illogical interface behavior;
  • awkward user scenarios;
  • business logic conflicts;
  • errors in the sequence of actions;
  • issues with how the user perceives the system;
  • unstable operating scenarios.

This is especially important after Vibe Coding, because many decisions are made without a full-fledged design phase.

Reviewing the requirements before testing

One of the key challenges at Vibe Coding is that projects are often launched without a comprehensive technical specification. Therefore, before testing begins, it is necessary to effectively reconstruct the project documentation:

  • describe the business logic;
  • define the user flow;
  • create wireframes and mockups;
  • define the expected system behavior;
  • define user roles;
  • describe usage scenarios;
  • prepare a list of functionality requirements.

Only then does testing become systematic and objective.

Without this, QA turns into a chaotic check of individual screens rather than a comprehensive validation of the product.

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Preparation of use cases and test scenarios

Once the system logic has been restored, the following are prepared:

  • user cases;
  • test cases;
  • checklists;
  • user behavior scenarios;
  • failure scenarios;
  • error scenarios;
  • edge cases.

This approach allows us to test not only the “main happy path” but also the product’s real-world operating conditions.

For example:

  • what happens if the internet connection is lost;
  • how the system behaves when a form is resubmitted;
  • how API errors are handled;
  • what the user sees when data is incorrect;
  • how roles and access rights work;
  • what happens under high loads;
  • how the system behaves on mobile devices.
Software testing after Vibe Coding: why the era of AI development makes QA even more important

What to check after vibe coding: a basic checklist

Business Logic Testing

  • correct operation of core functions;
  • alignment with business logic;
  • accuracy of calculations;
  • correctness of statuses and scenarios.

User Interface Testing

  • responsiveness;
  • correct display;
  • functioning of buttons and forms;
  • UX logic;
  • intuitive navigation.

User Scenario Testing

  • registration;
  • authentication;
  • order placement;
  • request creation;
  • notification functionality;
  • file uploads;
  • filter and search functionality.

Integration Testing

  • CRM;
  • payment systems;
  • Telegram;
  • email notifications;
  • API;
  • external services.

Security testing

  • access roles;
  • data protection;
  • error handling;
  • form security;
  • authentication functionality.

Performance testing

  • loading speed;
  • performance under load;
  • system stability;
  • performance on low-end devices.

Website testing after Vibe Coding

Websites and corporate portals

Even simple websites developed using AI often contain form errors, SEO issues, unstable responsiveness, and malfunctions on mobile devices.

Testing helps verify the correctness of the interface, performance speed, application forms, integrations, and user scenarios.

Software testing after Vibe Coding: why the era of AI development makes QA even more important

Mobile app testing after Vibe Coding

Mobile Apps

Mobile apps are particularly susceptible to UX errors and unstable logic. It is essential to test performance across different devices, operating systems, and usage scenarios.

It is important to test:

  • push notifications;
  • authentication;
  • offline scenarios;
  • camera functionality;
  • geolocation;
  • interface performance.

Testing CRM and ERP systems after Vibe Coding

CRM systems and ERP 

CRM and ERP systems contain a large amount of business logic, roles, automations, and integrations. After AI development, it is particularly important to verify:

  • the correctness of business processes;
  • access rights;
  • manager workflows;
  • statuses;
  • funnels;
  • automated actions;
  • integrations with messaging apps and telephony.
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Testing SaaS services after Vibe Coding

SaaS platforms and online services

SaaS products must be stable, scalable, and secure. Testing allows us to verify:

  • system stability;
  • multi-user operation;
  • subscriptions;
  • billing;
  • APIs;
  • fault tolerance;
  • data security.

Testing Telegram bots after Vibe Coding

Telegram bots and AI assistants

Telegram bots are often created very quickly using AI, but this is precisely where many hidden logic errors arise. It is important to check:

  • dialogue scenarios;
  • error handling;
  • AI response functionality;
  • CRM integrations;
  • command validity;
  • user state management;
  • load and stability.
Software testing after Vibe Coding: why the era of AI development makes QA even more important

Testing 2D/3D configurators after Vibe Coding

Online 2D/3D Configurators

Configurators are one of the most complex categories of systems because they combine:

  • visualization;
  • business logic;
  • calculations;
  • parameters;
  • specification generation;
  • user scenarios.

After Vibe Coding, it is particularly important to test:

  • the correctness of combinations;
  • cost calculation;
  • the operation of the 3D scene;
  • element compatibility;
  • PDF and specification generation;
  • WebGL performance;
  • interface responsiveness.
Software testing after Vibe Coding: why the era of AI development makes QA even more important

Why testing is becoming a standalone service in the AI era

The pace of digital product development will only continue to accelerate. AI truly speeds up development exponentially. But along with this, the number of the following is also increasing:

  • logical errors;
  • unstable solutions;
  • ill-conceived scenarios;
  • technical debt;
  • architectural issues.

Therefore, in the coming years, the market for QA and technical audits will only become more in demand.

Companies will increasingly face a situation where a product has already been created using AI tools, but before launch, it must be:

  • verified;
  • stabilized;
  • documentation restored;
  • logic formalized;
  • real-world use cases tested.

Conclusion

Vibe Coding is transforming the approach to software development. Creating digital solutions is becoming faster and easier. But at the same time, the importance of testing, analytics, and systematic quality assurance is growing.

It is testing after Vibe Coding that allows you to turn a “product that sort of works” into a reliable system that you can actually use, scale, and trust with your business processes.

AI can accelerate development. But confidence in product quality still requires an engineering approach, analytics, and comprehensive QA.

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