We are experiencing a profound transformation in the way software is created. Sequential logic and upfront planning are giving way to a more fluid, iterative—and, why not say it—more human approach. This is the context in which the concept of vibe coding is gaining momentum. Popularized by Andrej Karpathy, vibe coding represents a new way of programming, guided more by intention and experimentation than by rigid plans.
With the rise of generative language models (LLMs) like ChatGPT, Claude, Gemini, and Copilot, we are witnessing a new cycle in software engineering. These are not just tools that complete lines of code—they are platforms that interpret ideas, build functional blocks, adjust syntax, and optimize structures almost instantly. We are moving from design before code to idea-to-code.
From Intuition to Deploy: A New Workflow
What makes vibe coding so transformative is its ability to drastically shorten the distance between concept and execution. Instead of starting with a detailed architecture or extensive diagrams, the developer begins with a command, a sketch, or a question. AI responds with a proposed solution. The process moves forward in rapid cycles of refinement and validation, with the human acting as editor and strategist.
This dynamic will help automate repetitive development tasks—such as boilerplate generation, unit testing, automation scripts, and basic refactoring—freeing developers to focus on what truly matters: architecture, user experience, and solving strategic problems.
Impact of Vibe Coding on Startups and Enterprises
It’s no coincidence that small teams are achieving exponential results. According to interviews shared by accelerator Y Combinator, startups with fewer than 10 people are generating millions in revenue—something unthinkable just a few years ago. The combination of generative AI, cloud environments, and collaborative tools is leveling the playing field, enabling small teams to deliver value on a global scale.
In large enterprises, this new paradigm is already a reality. During LlamaCon 2025—the first conference dedicated exclusively to developers and researchers working with Meta’s Llama AI models—Microsoft CEO Satya Nadella revealed that 20% to 30% of the code in the company’s repositories is now AI-generated, highlighting how quickly AI-assisted development is being integrated into enterprise-scale software engineering workflows.
The global market for generative AI-powered software, which includes vibe coding, low-code, and no-code solutions, is projected to grow from approximately $196.63 billion in 2022 to around $1.81 trillion by 2030, at a compound annual growth rate (CAGR) of 37.3%, according to Grandview Research.
Challenges and Risks of Vibe Coding
Even so, the landscape is not without challenges. Vibe coding is not a magic shortcut to quality, nor a replacement for traditional engineering. It demands greater technical judgment, stronger critical thinking, and deeper awareness of architecture, version control, testing, security, and scalability.
When used irresponsibly, vibe coding can create technical debt that is hard to fix. Code that “works” is not necessarily sustainable. That’s why the developer’s role as solution architect remains essential. AI is powerful, but it still operates on statistical patterns and requires context, clear objectives, and human oversight.
This is not a revolution in the sense of discarding the past—it’s an evolution that expands the possibilities for those who already master the fundamentals of software engineering.
The New Developer Profile: Orchestrator
We are seeing the rise of a new type of developer—someone who blends product vision, technical expertise, and mastery of AI tools. Someone capable of translating business problems into technical solutions with the support of generative assistants, without relinquishing technical responsibility. We are not moving toward less code, but toward better code—faster and with less friction.
Vibe coding does not eliminate development complexity, but it gives us a new way to approach it: with creativity, autonomy, and more powerful tools than ever. AI has not come to replace programmers—it has come to redefine what it means to “program.”
Practical guide: how to apply Vibe Coding in your daily life
Here are some tips for getting the most out of vibe coding:
Start with clarity
– Define your vision objectively
– Use tools like ChatGPT, Claude or Gemini 2.5 Pro to organize ideas, set objectives and map out functionalities
Choose the right tool for you
– Beginners: start with Bolt.new, Replit or Lovable
– Experienced developers: prefer VS Code, Cursor or Windsurf for more sophisticated flows and advanced control
Create a project plan with AI
– Create a README.md or project.md file in the project folder with:
- Description of what will be built
- Planned functionalities
- Future ideas
– Work with AI to simplify this plan and develop it section by section
Write specific Prompts
– Instruct the AI clearly
– Avoid vague phrases. Provide context, objectives and constraints whenever possible
Build in small blocks
– Divide the project into smaller parts
– Implement, test and commit by block
– This approach facilitates debugging and continuous evolution
Rigorous testing
– Never assume that AI code is perfect
– Apply unit tests, integration tests and simulations in different environments
Use advanced vibe coding tools
– VS Code: offers AI integration, intelligent suggestions and efficient debugging
– Cursor: ideal for exploring, editing and generating code with continuous AI assistance
– Windsurf: focuses on productivity with robust support for teams and automation
Technical care and good practice
– Avoid unnecessary abstractions, prefer simple, readable solutions
– Use global variables with caution
– Document and comment, even if the AI generates the code, write comments and keep clear documentation.
