Cursor: What is the AI-Powered IDE?

What is Cursor?

Cursor is an AI-powered code editor launched in 2023 by Anysphere. Built as a fork of Visual Studio Code, it retains the full familiarity of the VS Code ecosystem (extensions, shortcuts, themes) while adding a deeply integrated AI layer. Unlike simple autocompletion extensions like GitHub Copilot, Cursor offers an experience where AI is a full development partner: it can read the entire project, understand the code architecture, and generate coordinated multi-file modifications.

The tool is part of the vibecoding movement, a term popularized by Andrej Karpathy in 2024, which describes an approach where the developer describes what they want in natural language and lets the AI produce the corresponding code. Cursor quickly gained popularity among developers and non-developers alike, promising to democratize software creation. However, this promise comes with significant limitations, particularly visible in larger projects.

For Belgian and European businesses, Cursor represents both a development acceleration opportunity and a risk if used without professional oversight. KERN-IT regularly encounters projects initiated with Cursor by non-developers that, after a promising start, hit a complexity ceiling requiring experienced teams to bring them to completion.

Why Cursor Matters

Cursor has transformed how developers interact with their code, and its impact goes beyond simple productivity gains.

• Deep contextual integration: unlike standard autocompletion, Cursor indexes the entire project and understands relationships between files, dependencies, and overall architecture. This enables suggestions that account for the real project context.
• Prototyping acceleration: for creating prototypes, MVPs, and proof of concepts, Cursor significantly reduces development time by generating complete scaffolds from natural language descriptions.
• Lowered barrier to entry: non-technical profiles (product managers, designers, entrepreneurs) can now produce functional code, disrupting the traditional boundary between designers and developers.
• Multi-model support: Cursor allows switching between different LLMs (GPT-4, Claude, etc.) depending on the task, offering flexibility that single-vendor solutions do not provide.
• Limitation revealer: paradoxically, Cursor highlights the importance of software engineering expertise. Projects that move beyond the prototype stage quickly reveal the weaknesses of code generated without qualified human supervision.

How It Works

Cursor relies on an architecture that combines a code editor (VS Code fork) with a sophisticated AI pipeline. At the core is an indexing engine that analyzes the entire project: source files, configuration files, dependencies, and documentation. This index is transformed into vector embeddings stored locally, enabling the AI to quickly retrieve relevant code portions to respond to a query.

When a developer uses the "Cmd+K" feature to give a natural language instruction, Cursor builds an enriched prompt that includes the active file, referenced files, and relevant context extracted from the index. This prompt is sent to the selected LLM, which generates a response as a diff (changes to apply). The user previews the changes and can accept, modify, or reject them.

The Composer feature goes further by enabling coordinated multi-file modifications. The developer describes an architectural change (for example "add a JWT authentication system") and Cursor generates the necessary modifications across multiple files simultaneously. The integrated chat allows iterative dialogue with the AI to refine results, while maintaining conversation context.

Concrete Example

KERN-IT is regularly called upon to take over projects initiated with Cursor by non-technical teams. A frequent scenario: a startup or entrepreneur uses Cursor to generate an MVP in a few days. The application works on the surface, but as soon as the project needs to evolve toward production — security management, scalability, testing, deployment, maintenance — the shortcomings of unsupervised generated code emerge: lack of clear architecture, massive duplication, security vulnerabilities, absence of tests, and accumulated technical debt.

The KERN-IT team then steps in to audit the existing code, identify reusable components, and restructure the project to professional standards. This "rescue" work has become a KERN-IT specialty: transforming an AI-generated prototype into a robust, maintainable, and secure production application. Internally, KERN-IT developers also use Cursor, but with the expertise needed to validate, correct, and architect the generated code, which makes all the difference between a fragile prototype and a reliable product.

Implementation

1. Installation and configuration: download Cursor from cursor.com, import your existing VS Code extensions and settings. Configure API keys for desired LLMs (or use credits included in the subscription).
2. Project indexing: open the project in Cursor and let indexing complete. For large projects, configure a .cursorignore file to exclude irrelevant directories (node_modules, builds).
3. Supervised usage: use Cursor as an accelerator, not a developer replacement. Systematically review generated code, verify business logic, error handling, and security implications.
4. Define project rules: use the .cursorrules file to define code conventions, architectural patterns, and project-specific constraints.
5. Integrate into a professional workflow: combine Cursor with code reviews, automated testing, and a CI/CD pipeline. AI accelerates writing but does not replace human validation.
6. Know when to call experts: if the project moves beyond the prototype stage, engage professional developers to structure, secure, and future-proof the code.

Associated Technologies and Tools

• Competing AI editors: GitHub Copilot (integrated with VS Code), Windsurf (formerly Codeium), Zed (with AI), JetBrains AI Assistant
• LLMs used: Claude (Anthropic), GPT-4 (OpenAI), custom fine-tuned code models
• VS Code base: compatible extensions, marketplace, themes, debuggers — the entire VS Code ecosystem is available
• Complementary tools: MCP servers for connecting AI to external tools, Composer for multi-file modifications
• CLI alternatives: Claude Code (Anthropic), Aider, Continue.dev for CLI-based AI-assisted development

Conclusion

Cursor represents a major advance in software development tooling, making vibecoding accessible and productive. However, the ease of code generation it offers can create a false impression of technical mastery. KERN-IT supports its clients in the responsible use of these tools: internally, its developers leverage Cursor to accelerate their work without sacrificing quality, and externally, the team steps in to transform AI-generated prototypes into reliable production applications. AI is a formidable accelerator, but human expertise remains essential to ensure the quality, security, and longevity of software projects.