Given the current hype, the question is legitimate. Yet the answer is straightforward: no. This is far from the first time web development has faced such a shift, and the scenario has already played out three times in the past:
- The copy-paste era: assemblers, integrators, and tinkerers stitching together snippets retrieved from Stack Overflow without always understanding what was running under the hood.
- The rise of CMS platforms: the surge of WordPress, Joomla, or Drupal, promising anyone could deploy a complete website in just a few clicks.
- The no-code / low-code wave: visual tools marketed as the heralded gravediggers of traditional programming.
Every time, approaches that lack deep technical expertise inevitably run into the same triad of issues: gaping security vulnerabilities, severe performance bottlenecks, and the inevitable "upgrade wall"—the exact moment when evolving the system becomes impossible without breaking everything.
The prototype illusion put to the test of time
For shipping a POC (Proof of Concept), testing an idea, or building an ephemeral product to validate user demand in the short term, vibe coding excels. It is fast assembly, visually striking on the surface. But the moment a system is expected to endure, the varnish cracks, and rigorous software engineering becomes indispensable once again.
The direct result: no major product operating at massive scale has been entirely built on vibe coding.
When looking at disciplined software engineering, consumer-facing or infrastructure benchmarks are everywhere: Doctolib, Leboncoin, BlaBlaCar, Stripe, or Spotify.
When looking at pure AI or vibe-coded software? Virtually nothing.
The rare exceptions—frequently touted as success stories—behave more like statistical anomalies whose business model relies on a direct dependency on AI itself (such as PDF.ai, Photoroom, Interior AI, or Photo AI). Yet this setup creates a severe economic issue: the more traction the product gains, the more its infrastructure expenses scale linearly (or even exponentially) with the sheer volume of API calls.
Conversely, durable software architecture adheres to the classic principle of economies of scale: upfront investment is heavy for the initial users, but the marginal unit cost plummets as the user base expands.
Why system hardening still demands real brainpower
Transitioning from a working demo to an enterprise-grade product requires tailored architecture that raw automation simply cannot design:
- Real-time multi-user synchronization.
- Large-scale relational database management with strict handling of access conflicts and data integrity.
- Implementation of intricate business logic: complex billing workflows, granular permission matrices, automated dunning, and regulatory compliance.
Left to its own devices, vibe coding constantly runs into blind spots:
- ORMs configured with default settings, causing N+1 query problems and severe database bottlenecks.
- Immediate risks of massive data leaks.
- Catastrophic security practices (exposed secrets, API tokens, and mismanaged environment variables).
- Nightmare debugging sessions when tracking down silent failures.
- Cascading regressions at the slightest attempt to add new features.
- Technical debt so crippling that scaling often leaves no choice but to scrap the entire codebase and start from scratch.
The running shoes analogy
To capture how these two approaches coexist, consider how someone gears up when taking on a new sport:
- People often start with an entry-level pair of shoes: affordable and sharp-looking. They do the job just fine for a trial season, especially when it is still unclear whether the hobby will stick. That is the exact role of vibe coding: validating user interest without taking on heavy upfront debt.
- If the commitment lasts, they invest in high-performance gear engineered for durability: an ergonomic design built to withstand wear, absorb shocks, and allow for resoling, swapping laces, and treating the leather.
Vibe coding assembles quickly to test. The engineer architects robustly to last.