Over the past few months, “vibe coding” has emerged as the buzzword of the software world. Coined by Andrej Karpathy in February 2025, the term refers to using AI tools like Cursor, Replit and Claude Code to generate working code via natural-language prompts. Karpathy described the experience as: “I just see things, say things, run things, and copy‑paste things, and it mostly works.” Initially embraced for throwaway weekend projects, the approach has swiftly entered mainstream usage – some businesses now even list vibe‑coding abilities as a non-negotiable skill. But while rapid prototyping may be appealing, the trend brings serious risks for long-term stability. Here’s why systems built on vibe coding alone aren’t sustainable – and why expert developers are essential.

Why Vibe Coding Gained Traction

• Accelerated development – AI-powered prompts can produce code for basic components, UI elements and utilities in seconds, upping productivity significantly.
• Lower barrier to entry – Non‑technical users can sketch working tools or demos without deep programming knowledge.
• Flow and creativity – The relaxed, ambient approach often associated with vibe coding fosters experimentation and inspiration.

Some companies are already reporting up to 40 per cent improvements in development speed on routine coding tasks when leveraging AI assistance – which isn’t to be confused with relying solely on vibe coding!

The Hidden Caveats

Fragile code structures

Code generated by AI often lacks architectural cohesion. Without thoughtful design, prototypes can devolve into untidy, spaghetti-style code that resists scaling.

Technical debt mounts unseen

Skipping documentation, refactoring and modular structure leads to complexity that will cost time and money to untangle down the line.

Security vulnerabilities slip through

AI models may introduce unsafe patterns – lack of input validation, insecure authentication or dependency flaws – with no one fully reviewing underlying logic.

Debugging becomes a black box

When developers don’t understand the code, tracing bugs or predicting behaviour across modules becomes a daunting challenge for future maintainers.

Collaboration friction

Teams operating under shared standards rely on clarity and consistency. Vibe-coded artefacts often clash with formal processes, leading to misalignment and onboarding friction.

Culture of unaccountability

Calling it “vibe coding” implies relaxed standards. But in a business setting, loose code is a liability.

When Vibe Coding Helps – and When It Hurts

Use Case	Vibe Coding	Expert Engineering
Rapid prototype/MVP	● Good fit	● Still valuable
Internal tools	▲ Possible with review	● Preferred
Production systems	✗ Too risky	● Essential
Security-critical apps	✗ Unsafe	● Mandatory
Long-lived codebases	✗ Unsustainable	● Best practice

Vibe coding excels at quick experiments – but becomes a liability when scaled or used for critical systems. The long-term cost of brittle, poorly understood code far outweighs temporary velocity gains.

Why Skilled Developers Matter More Than Ever

• Architectural foresight – Skilled engineers build for maintainability, scalability and security from the outset.
• Deep debugging expertise – When systems span multiple components, human intuition is critical for root‑cause analysis.
• Security-first mindset – Experienced developers can spot and mitigate vulnerabilities that AI tools overlook.
• Governance and standards – Real engineers embed logging, testing and documentation – elements AI won’t enforce.
• Knowledge sharing and onboarding – Clear code enables teams to collaborate, evolve and adapt without technical debt drag.

Vibe-coded shortcuts expose organisations to cascading failure – bugs, breaches, outages, and spiralling support costs.

The Balanced Approach: AI as Assistant, Not Architect

The future of software development lies in AI‑augmented engineering, not AI‑dominated creation. Use LLMs to offload repetitive work – but combine them with expert oversight:

• Treat AI output as draft artefacts, not deployable solutions.
• Maintain single-threaded ownership of architecture design, readability and security.
• Review and test every AI-generated line to ensure compliance and performance.
• Invest in prompt-engineering skills – precise instructions produce more robust results.
• Embed AI usage into existing processes: code reviews, CI pipelines and documentation cultures.

Teams who treat AI as a tool – not a replacement – stay in control of quality and security.

Partner with Vertex Agility for Secure, Sustainable Development

At Vertex Agility, we empower businesses with agile, on‑demand tech teams skilled in combining AI tools with structured engineering discipline. From prompt‑driven prototyping to production-grade systems, our experts ensure that your code is secure, maintainable and scalable.

If you want the benefits of faster delivery without sacrificing long-term health, talk to us. We help you build healthy, AI‑enabled pipelines – and avoid the pitfalls of uncontrolled vibe coding.

Contact us now to discuss the next steps!