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Vibe coding

As explained in Introduction to Generative AI, Second Edition

Vibe coding is a software-development practice in which a person describes desired behavior in natural language and accepts AI-generated code with little or no code review.

Vibe coding is an AI-heavy approach to software development in which a person describes desired behavior in natural language and accepts generated code for much or all of a project, often with little or no review. section 6.6 section 5.2

The practice extends ordinary coding assistance: a developer can describe a function in a comment or docstring, receive a reasonable first attempt, and iterate more quickly. Agentic tools such as Claude Code, Cursor AI, Replit Agent, and Windsurf can take actions directly rather than merely suggest completions. section 6.6

Vibe coding can make software creation more accessible, but it shifts important responsibility toward verification:

  • Generated code may contain subtle vulnerabilities when users lack the expertise or incentives to audit it. section 5.2
  • Hallucinated package names can enable slopsquatting, in which attackers register malicious dependencies resembling commonly suggested names. section 5.2
  • Unreviewed snippets such as file-upload handlers may omit safeguards against remote code execution, privilege escalation, or data leakage. section 5.2
  • These weaknesses can remain unnoticed during development and become embedded across systems as AI-assisted coding spreads among technical and non-technical users. section 5.2

From prompt to insecure dependency

A user can ask an LLM to create an application and install the dependencies it suggests without checking their origins. If a suggested package name is hallucinated and an attacker has registered it, the application may unknowingly incorporate malware. section 5.2

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Explains the workflow and security consequences but stops short of implementation guidance or a code-review procedure.
Examples
Uses agentic coding tools, hallucinated package names, and insecure file-upload handlers as concrete examples.
What you can do after
Evaluate/understand how AI-assisted coding accelerates development while introducing review, dependency, and application-security risks.
How it connects
Connects large language models with software development, code review, cybersecurity, package dependencies, and malware.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.