Andrej Karpathy coined the term "vibe coding" in early 2025 — the practice of describing what you want in natural language and letting AI write the code. By 2026, it has become the dominant workflow for prototyping, internal tooling, and even production features. Here is the honest assessment: what it is great for, where it falls apart, and how development teams should actually use it.
What Vibe Coding Actually Looks Like in Practice
Tools like Cursor, GitHub Copilot Workspace, Windsurf, and Claude Code support multi-file agentic coding where you describe a feature and the AI plans, implements, and iterates across your entire codebase. Speed gains are real:
- CRUD features that took a day now take 30 minutes
- Boilerplate and scaffolding is effectively free
- Test generation is fast and thorough
- Refactoring large codebases is dramatically faster
- Unfamiliar frameworks become accessible immediately
Where Vibe Coding Breaks Down
- Security: AI-generated code regularly introduces SQL injection, XSS, and IDOR vulnerabilities. Every line needs security review.
- Architecture: AI is excellent at implementing within an architecture. It is bad at designing one.
- Domain-specific correctness: Financial calculations, medical data processing, and legal logic require domain experts to verify output.
- Technical debt: AI generates code quickly but does not clean up the debt it creates. Without deliberate refactoring, vibe-coded codebases degrade fast.
How We Use AI Coding at SoftUs Infotech
- Architecture first, always: Senior engineers define the system architecture and boundaries before any AI code generation
- AI for implementation sprints: Feature implementation using Cursor with thorough PR review focused on security and correctness
- Automated security scanning: Every AI-generated PR runs through Semgrep and CodeQL before human review
- Test-first for critical paths: Write tests for critical business logic before asking AI to implement
- Weekly tech debt sessions: Dedicated time to refactor AI-generated code before it calcifies
The Productivity Reality
Our engineers report 60–70% productivity improvement for feature development with AI tools. Junior developers gain the most — they can implement senior-level features using AI as a pair programmer. The teams that struggle are those that use AI coding without changing their review and architecture practices to match the new speed.
Vibe coding is not the end of software development — it is the end of tedious software development. The craft has moved up the stack from writing every line to designing systems and ensuring correctness. That is not a demotion. It is an upgrade.
