Vibe Coding: Programming with flow – even during parental leave

What is vibe coding?

Vibe coding is a modern approach to software development based on agentic coding. Developers work together with AI-supported tools - known as agents - that understand the project context, generate code, analyze errors and suggest solutions. By interacting with the AI in natural language, developers can describe desired functions or problems that need to be solved. This approach significantly reduces the effort required for manual coding, accelerates the development of new software and makes complex projects more efficient to implement.

Vibe Coding describes the practical application of this method - especially in situations where the time available is limited. It enables productive work sessions that are optimally supported by the use of modern tools such as Cursor, GitHub Copilot, Tabnine or Replit.

How does Vibe Coding work in practice?

Vibe coding only works thanks to agentic coding, a method in which agents work actively alongside the project. These agents understand the project context, generate code, analyze errors and suggest solutions. They act like a co-pilot that proactively supports the entire workflow. 
 

LLMs and MCPs

Large Language Models (LLMs) such as those from OpenAI or Google form the basis for agentic coding. These models are specialized in understanding language and interacting in a natural way. With the help of so-called Model Context Protocols (MCPs), the agents can retrieve information from external sources such as databases or other systems and thus understand the current project status.

MCP is an open protocol that standardizes how applications provide context for LLMs. It works similarly to a USB-C connector for AI applications: While USB-C provides a standardized connection between devices and accessories, MCP enables a standardized interface to connect AI models to various data sources and tools.

Tools such as Cursor or GitHub Copilot expand the possibilities by making coding more efficient and productive through AI-supported suggestions and error analysis. Particularly exciting, however, is Replit, which is specially optimized for cloud use. For example, it enables the direct hosting of created websites or the provision of databases - a huge relief for developers working on more complex applications. 
 

Conclusion

Our colleague enjoyed getting to grips with the various tools - including the hurdles that arose, but also the successes that quickly became apparent. By the end of his parental leave, he actually had a functioning app. As the available models and technologies are developing at breakneck speed, it is definitely worth getting to grips with the topic of AI-supported programming - whether in your free time or in your day-to-day work. 
 

Links to the tools:

• Cursor: AI-powered code editor with a focus on contextual code suggestions and productivity enhancement. Learn more
• GitHub Copilot: AI pair programmer that makes real-time code suggestions directly in the IDE. Learn more
• Tabnine: AI-based code completion that provides contextual suggestions for various IDEs. Learn more
• Replit: Cloud-based development environment with real-time collaboration and AI-supported code generation. Learn more