What is Vibe coding?
Building applications primarily by prompting AI coding assistants (Cursor, Lovable, Bolt, v0, Copilot, Claude Code) rather than writing code by hand. The model translates natural-language intent into running code; the human reviews and ships.
Full explanation
Vibe coding is the dominant pattern for solo founders and indie developers in 2025-2026. The model produces 80-95% of the code; the human handles product decisions, UX, and the security review the model often skips. The productivity gain is real and large; the predictable failure mode is that the model trains on the canonical-but-buggy patterns in its training corpus, so vibe-coded apps ship the same handful of canonical bugs (missing auth checks, FormData-trusted user IDs, middleware-matcher mismatches, inline secrets) at high frequency.
Example
A founder asks Cursor: 'Add a /api/orders/[id] endpoint that returns the order.' Cursor produces a route handler that takes params.id and queries the database — but skips the ownership check that compares the order's user_id against the authenticated session. The route ships with a Broken Object-Level Authorization bug. This is a vibe-coding failure mode: the model is correct on the happy path, wrong on the security path, and the human reviewer rarely catches it.
Related
FAQ
Is vibe coding less secure than hand-coded apps?
On average, somewhat — yes. The bug shapes are predictable and the human review is faster, so canonical bugs ship more often. The right defense is automated security review on every PR (Securie's specialists are tuned exactly for AI-generated code's failure modes), not slowing down the AI-coding workflow.
What about teams with senior engineers reviewing AI output?
Senior reviewers catch more, but every team faces the 600-line-diff problem — at some point, the human reviewer skims rather than reads carefully, and a security bug in the skimmed section ships. Automated review backstops this gap.