Vibe coding makes it possible to build software faster than ever, but getting an app to work is only half the job. AI coding tools can generate functional features quickly, but they don’t automatically account for security, data protection, operational readiness, UX, cost, or AI-specific risks.

This whitepaper series explores 10 common pitfalls of AI-assisted development, from leaked secrets and access control issues to prompt injection, dependency risks (such as hallucinated packages), unexpected costs, poor UX states, and risks outside the code itself.

Rather than arguing against vibe coding, it provides a practical way to identify what AI can handle and what still requires deliberate human review before shipping.

What You’ll Learn

• The key risks and blind spots of vibe coding.
• Common security, data, cost, dependency, and operational pitfalls in AI-built applications.
• AI-specific risks including prompt injection, unsafe agents, and over-permissioned tools.
• Common UX issues in AI-generated interfaces and how to address them.
• Practical checks to identify risks before shipping AI-built software.

Applicable Use Cases

• Building and launching AI-assisted prototypes and MVPs.
• Reviewing AI-generated applications before production.
• Establishing security and operational guardrails for vibe coding.
• Identifying risks across code, infrastructure, UX, and third-party services.
• Building safer and more reliable AI-assisted development workflows.