Vibe Coding vs Custom Development: The Honest Comparison | Simple Automation Solutions

Software Development

Vibe Coding vs Custom Development: The Honest Comparison

Vibe coding compresses development time. It also creates technical and security debt when used in the wrong context. Here is where each approach belongs.

SAS

Simple Automation Solutions

··⌛ 9 min read

Prototypes
ideal use case for vibe coding
Security paths
never vibe-code authentication or payments
Read before committing
treat AI code as a draft not a delivery
Hybrid approach
most professionals use both

Vibe coding — prompting AI to write most or all of the code for a software project, with the developer as curator rather than primary author — has moved from a viral demo trend to a legitimate development approach for specific use cases. It is also genuinely dangerous in others. Here is the honest assessment.

What vibe coding actually means

The term ‘vibe coding’ was coined by Andrej Karpathy in February 2025 to describe a programming approach where you describe what you want in natural language, accept the AI-generated code without fully reading it, and iterate based on whether the running output matches your intent. In practice, most developers in 2026 sit on a spectrum between pure vibe coding and AI-augmented development where AI handles specific subtasks while the developer maintains deep understanding of the codebase.

When vibe coding works

  • Prototypes and proofs of concept: exploring whether an approach works in principle, not shipping to production
  • Solo personal projects: when you are the only person who needs to maintain the code and it has no security requirements
  • Throwaway scripts and automation: a script to process a one-off CSV, automate a local workflow, or generate test data
  • Exploring unfamiliar frameworks: generating boilerplate and basic examples to understand how a framework behaves

When vibe coding is dangerous

  • Production applications with real users: shipping code you do not understand creates a maintenance and security liability that compounds over time
  • Security-sensitive code: authentication, authorisation, payment processing, data encryption — AI frequently produces code that looks correct but contains subtle vulnerabilities
  • Code others need to maintain: AI-generated code can be syntactically correct but architecturally incomprehensible to anyone trying to maintain it
  • Complex systems with emergent behaviour: without understanding the code, debugging emergent issues is nearly impossible

Vibe coding vs custom development compared

Dimension Vibe coding Custom development
Speed to working prototype Very fast (hours to days) Slower (days to weeks)
Code quality Highly variable; often poor architecture Consistent with team standards
Maintainability Often poor Designed for maintenance
Security Frequently contains vulnerabilities Security-conscious with proper review
Cost (initial) Very low Significantly higher
Cost (lifetime) Potentially very high (rework, security incidents) Lower lifetime cost per feature delivered
Best for Exploration, prototypes, personal projects Production systems, commercial products, team codebases

The practical hybrid approach

1
Use AI for boilerplate and pattern generation

Generate component scaffolding, CRUD operations, test structure with AI. Low-risk because these follow well-understood patterns easy to review.

2
Read and understand before committing

Treat AI-generated code as a draft, not a delivery. Read it, understand it, modify where needed, and only commit code you can explain.

3
Never vibe-code security paths

Authentication flows, payment processing, and authorisation should be written deliberately, with full understanding.

4
Review AI code in pull requests

AI code is not exempt from review because of its source. Treat it identically to any other code.

5
Test AI-generated code more thoroughly

AI code often contains edge case failures. Test with more exhaustive cases than you would for code written by an experienced developer.

The honest verdict

Vibe coding is a tool, not a methodology for production software.

Used appropriately — for prototyping, exploration, and AI-augmented development with human understanding — it compresses development time meaningfully. Used inappropriately — shipping AI-generated code without understanding it, particularly for security-sensitive or user-facing production systems — it creates technical and security debt that eventually costs more to address than the time it saved.

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Frequently asked questions

Can a non-developer build a production application with vibe coding?+

For simple, low-risk applications: possibly. For applications with security requirements, complex business logic, or real user data: the risk of shipping code you do not understand is proportional to the consequences of it failing. Non-developers building production software should have the resulting code reviewed by an experienced developer before launch.

Will vibe coding replace software developers?+

It will change what developers spend time on — reducing time on routine implementation and increasing time on architecture, product thinking, code review, and verification. The skills that become more valuable: system design, security understanding, testing, and the ability to reason about code quality.

Is vibe coding code reviewable?+

Yes, technically. The practical challenge: AI-generated code is often architecturally inconsistent — implementing the same pattern differently in different parts of the codebase. This makes review slower, not impossible. Code review discipline is more important with AI code generation, not less.

SAS
Simple Automation Solutions
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