Vibe coding lets anyone make apps with AI, but raises questions about quality and control

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Vibe coding, named Collins Dictionary's 2025 Word of the Year, enables people to build software using natural language prompts instead of traditional programming. Coined by AI researcher Andrej Karpathy, this approach lets AI handle implementation while developers focus on ideas. But as 25% of Y Combinator startups now use AI-generated codebases, concerns emerge about security vulnerabilities and the fundamental shift in what it means to be a developer.

Vibe Coding Transforms How Software Gets Built

Vibe coding represents a fundamental shift in software development where AI handles most of the technical implementation while humans focus on describing what they want to create. The term, coined by Andrej Karpathy—an AI researcher, Tesla's former director of AI, and member of OpenAI's founding team—in early 2025, describes a workflow where developers "fully give in to the vibes" and stop worrying about the code itself

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. The phrase spread so rapidly across developer circles that Collins Dictionary named vibe coding its Word of the Year

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. This intention-driven development approach turns software creation into a conversation where you describe your idea using natural language prompts, and AI tools generate the framework, logic, and user interface.

Source: CNET

Source: CNET

Democratization of Programming Through AI Tools

The movement gained momentum after ChatGPT arrived in late 2022, kicking off an AI boom that demonstrated how powerful natural-language tools could be

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. Now, platforms like ChatGPT, Claude, Gemini, Grok, Cursor, and GitHub Copilot Workspace enable users to make apps with AI through limited free use. More streamlined platforms like Replit and Bolt take this further by generating entire projects inside the editor, allowing users to request changes in plain language and publish working sites without touching raw code

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. This democratization of programming reduces barriers to entry, opening software development opportunities for people without in-depth programming knowledge. Y Combinator data from the Winter 2025 batch shows this shift in action: about 25% of startups had codebases built almost entirely by AI

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Source: TechRadar

Source: TechRadar

Code Quality and Security Concerns Emerge

While vibe coding delivers speed and simplicity, it wasn't designed with long-term security, maintenance, and scalability in mind

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. Studies show that vibe coding can lead to increased complexity and re-work down the track or, in worst cases, low-quality output. A study by OutSystems found 62% of IT professionals using AI in the development process experience growing challenges with security and governance

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. Security vulnerabilities become particularly concerning when developers implement AI-generated code without review. Attackers can exploit simple errors like typos in package names to inject manipulated libraries, and because dependencies are often managed automatically in vibe coding environments, the attack surface of an enterprise increases significantly

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. Sam Dhar, former engineering leader at Adobe and Amazon Alexa and now leading AI Platform at Galileo AI, emphasizes that someone must evaluate what was produced and make careful decisions. "Only someone who has that knowledge and experience can truly effectively use AI to be able to build things that are production-ready," Dhar explains

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The Shift in Developer's Role and Required Skills

Vibe coding fundamentally redefines what it means to be a developer. The more automated code generation becomes, the more quality assurance becomes a key responsibility

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. Developers are shifting from execution to oversight, becoming AI strategists who ensure AI-generated code remains ethical and secure. This requires nuanced understanding of how to work with and prompt generative AI, as well as awareness of its limitations. The skills required now include effective prompting techniques that yield stable and reproducible results. Ethical considerations also come into play—who deals with consequences if AI-generated code violates license terms or infringes intellectual property when trained with publicly accessible source codes

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? Dhar describes real software as a pyramid of decisions, from tiny user interface choices like button color and shape to high-level questions about target users and scalability. In his view, not every decision can be spelled out in one giant prompt to a model

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What Developers and Organizations Should Watch

While vibe coding allows for creative freedom and faster prototypes, this value is only felt long-term if supported by clear quality controls

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. Organizations jumping on the bandwagon are proposing vibe-led workplace processes from vibe-working to vibe-automation with varying degrees of success. For beginners, vibe coding removes the need to understand syntax but not the need for basic computer literacy. Newcomers still need step-by-step guidance for basic actions like creating a project, opening the correct file, pasting code, and previewing results

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. As AI takes on the technical burden, developers must not rely blindly on AI tools but rather maintain human authority to strategically leverage strengths and compensate for weaknesses. The future of coding requires balancing the speed and accessibility of no-code and low-code approaches with rigorous oversight to prevent time saved now from creating inefficiencies later.

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