Vibe Coding:
how AI is transforming software development

In recent months, generative artificial intelligence has begun playing an active role in software development. We’re no longer talking about basic chatbots or text-based assistants: today’s tools are intelligent agents, capable of executing complex tasks, interacting with their environment, and actively contributing to the construction of an application.

This is the context in which the concept of vibe coding emerges — a new paradigm that blends code, natural language, and AI into a seamless operational flow. The developer is no longer just using a tool: they engage in a dialogue with a system, guiding it and being guided in return, shifting their focus from syntax to application logic.

From chat to agents: the evolutionary leap

Interacting with LLMs began as a purely textual experience, based on simple prompts and responses. The real shift, however, came with the transition to agent-based systems — AI models equipped with state, working memory, and the ability to use external tools.

These agents do more than reply. They reason about context, retrieve distributed information, perform structured tasks, and navigate even large and complex codebases. This turning point gave rise to vibe coding: a collaborative workflow between developer and AI, increasingly immersive and productive.

Cursor

Cursor is an advanced IDE based on Visual Studio Code, designed to work in close synergy with large language models (LLMs). Its structure retains the familiarity of VSC, but adds a series of features specifically built to unlock the full potential of artificial intelligence in development workflows.

Features

The integrated chat offers three distinct modes of interaction:

Ask: for brainstorming, suggestions, and generating development tasks.
Agent: ideal for exploring the codebase, understanding data flows, architectures, and solving complex issues.
Edit: focused on precise edits to clearly defined sections of code.

Cursor introduces Cursor Rules, a configurable system of guidelines that shape how the AI agent behaves. These rules can be set globally or per project. Examples include:

apply only the minimal necessary changes;
keep files small and focused (e.g., under 200 lines);
use consistent, self-explanatory naming conventions.

The context of the conversation can be enriched with custom notes, code snippets, documentation fragments, or linked files. Each interaction is automatically saved as a checkpoint, making it easy to revert to previous project states if needed.

Cursor also allows developers to configure their preferred LLMs, including support for custom models through API keys.

Cursor and MCPs: what are they?

MCPs – Model Context Protocols are a framework that enables structured interaction between LLMs and their operating environment. They allow a model to access files, APIs, datasets, and project configurations in a controlled and context-aware manner. Essentially, it’s like giving the AI an interface to "navigate" the project space intelligently.

Cursor is one of the few tools that natively supports MCPs, allowing developers to significantly extend the agent’s capabilities through both public and custom configurations.

Learn more about the MCP concept

Chat: file reference and explanation request

Chat: citation options

Settings: models

Settings: models

Settings: MCP

Settings: MCP

Experience

Cursor offers an assisted yet controlled development experience, where the AI agent not only provides suggestions but actively contributes to both the construction and maintenance of the code. The integration of external tools such as Wisprflow further enhances this interaction, making the overall workflow extremely smooth and goal-oriented.

Advantages

Familiar interface for developers coming from VSC
Fast integration of newly released language models
MCP support for advanced contextual interaction
Precise version control through automatic checkpoints

Disadvantages

The free version is limited for continuous, full-time use
Requires a stable and persistent internet connection
Potential privacy concerns due to reliance on external servers (as with Copilot or ChatGPT)

Replit

Replit is a fully featured development platform accessible directly from the browser. It combines in a single environment all the tools needed for writing code, collaborating, debugging, and deploying — making end-to-end development available anywhere.