The Rise (and Risk) of Vibe Coding – What’s Worth Knowing

The term “vibe coding” has gained traction among developers and hobbyists, circulating on LinkedIn, TikTok, Twitter and on Slack channels. The idea is simple: write software by intuition, mood and with AI tools, moving fast and focusing on outcomes over process. The concept has appeal, especially when compared to the sometimes tedious, process-heavy reality of enterprise software engineering. However, the approach does have distinct limits when teams, customers, and data are involved.

What does vibe coding mean?

Vibe coding involves using AI tools or low-code platforms to generate much of the application’s code from natural language prompts.. The approach is fast, and the main goal is getting something working right away, even if the code isn’t production ready.

Where did vibe coding come from?

The notion of vibe coding came to life in 2025 and is credited to Andrej Karpathy. It describes the act of letting AI take the lead in writing code, simply “embracing the vibes” and skipping the details. The term quickly caught on in both hobbyist and professional circles.

On TikTok and similar platforms, vibe coding is about building whatever matches your mood or aesthetic, often with little planning or testing: a quick affirmation app or a portfolio site set to your favorite colors. The emphasis is on instant feedback and personal satisfaction, not process.

Why is vibe coding popular?

Vibe coding has become popular because it solves many frustrations that developers face in their daily work. For an experienced engineer looking to try ideas without red tape, or a newcomer using AI tools for the first time, vibe coding lowers the barriers to starting, iterating, and shipping projects

Speed

Traditional software projects are time-consuming and filled with checkpoints: requirement gathering, architecture planning, documentation, QA, reviews, and multiple rounds of approval. Vibe coding eliminates most of these steps –, delivering a prototype or even a deployable app within hours or days. Developers are able to focus on features and results, at least in the short term.

Low barrier to entry

AI-assisted coding makes it possible for those with limited experience (or limited patience) to build software that works. There’s less need for detailed knowledge of syntax, frameworks, or design patterns. People who previously struggled with traditional tutorials now publish projects after a weekend of experimentation. For non-programmers, it’s an opportunity to participate and create, using natural language.

Creative satisfaction

Developers often describe vibe coding as “fun.” There is immediate feedback, visible results, and the freedom to try ideas without fearing failure. In community spaces, it’s common to see creators proudly sharing projects that are functional, playful, and sometimes surprising. This encourages others to experiment and lowers the stakes around making mistakes.

What is vibe coding good for?

Vibe coding is well-suited to small-scale, personal, or low-stakes projects where speed and creativity are more important than maintainability or robustness. Typical examples include:

• Hackathons and prototypes: Hackathons are built for quick delivery. Vibe coding enables teams to ship something “good enough” in a matter of hours. If the prototype is compelling, it serves its purpose, even if the code isn’t production-grade.
• Personal tools and scripts: If you’re the only user or the risks are low, it makes sense to prioritize results. Automation scripts, utilities, or pet projects can all be built by vibe coding without worrying about strict standards or documentation.
• MVPs for indie startups: Small startups and solo founders often need to validate an idea before investing heavily. Vibe coding allows rapid experimentation and feedback from early users. Once an idea gains traction, there’s time to rebuild with more structure.
• Artistic and creative coding: Many artists and hobbyists use coding for self-expression. In these cases, the focus is on interactivity, aesthetics, or novel effects. The code may be messy or inefficient, but if it produces the desired outcome, it’s a success.

The risks of vibe coding in production

Vibe coding is tempting for professionals seeking speed, but its risks are significant in environments where reliability, security, and maintainability are mandatory.

Lack of testing

By definition, vibe coding deprioritizes systematic testing. This introduces unknowns into the software: bugs may only appear under certain conditions, and regressions become more common as changes are made. In a team or production environment, skipping unit tests and integration checks creates unpredictability.

Security issues

AI-generated code, and by extension, vibe-coded projects, are notorious for introducing vulnerabilities. A few common ones include:

• Hardcoded credentials: Some vibe coders see nothing wrong with pasting example code containing real or placeholder secrets. These can end up in production or public repositories. Attackers routinely scan codebases for just such mistakes.
• Missing validation: AI models tend to skip sanitizing user input, opening the door to injection attacks. Developers focused on functionality may not spot these vulnerabilities.
• Insufficient access control: Quick-and-dirty code rarely implements proper authentication or authorization, making sensitive actions accessible to anyone.

Documentation and maintainability

Vibe-coded projects rarely have documentation or a clear structure. While this may not matter for a one-person side project, it creates real problems for teams. New contributors have no reference, and even the original author may forget design decisions after a few months. Code reviews, bug fixes, and future enhancements become time-consuming or risky.

Suboptimal results

The vibe-coding approach is ineffective, even for mid-sized projects. For instance, the AI code editor Cursor currently struggles to navigate a codebase that resembles a typical enterprise system autonomously. While AI can still offer valuable assistance, it requires guidance from someone who understands the overall context – most likely a software engineer.

Scalability and architecture

What works for a prototype may collapse under real-world load. AI-generated code can be inefficient or lack consideration for edge cases. Vibe coding rarely considers performance tuning, caching, distributed system patterns, or failover strategies. As a result, applications that succeed with a handful of users may become unstable as usage grows.

Team coordination

In a team, vibe coding can introduce a whole new mess. If each developer relies on their own style, prompting methods, and/or AI models, the codebase quickly becomes inconsistent. Standards, reviews, and shared conventions are key to sustainable engineering. Without them, collaboration is difficult and technical debt increases.

Vibe coding gone wrong – real-life examples

• Early in 2025, dozens of apps created with the Lovable AI app builder shipped to production with hardcoded database credentials in the client-side code. Attackers found and exploited these secrets, gaining access to user data and admin panels.
• A solo SaaS founder (@leojr94_) documented how he launched a product built entirely with AI assistance, only to have malicious users discover embedded OpenAI API keys. The resulting unauthorized usage cost him thousands of dollars and forced the app offline.
• Multiple startups that “vibe-coded” their MVPs reported that, after initial success, their codebases became so tangled and undocumented that adding new features or onboarding developers became prohibitively difficult. In several cases, teams opted to rewrite entire applications from scratch rather than untangle the rapidly accumulated technical debt.

Why organizations still need real engineers

The conclusion is clear: vibe coding is perfect for side projects, hackathons, or fast iteration, but it is no substitute for professional engineering when real users, money, or data are at stake.

AI code assistants and vibe-driven workflows are not going away; if anything, they’ll become a bigger part of the coding space. But the risks of “just vibing” with code only grow. The industry consensus seems to be the following: use vibe coding to brainstorm, prototype, and unlock creativity, but always follow up with real software engineering, testing, documentation, security, and solid architecture, before shipping anything to production.

Most organizations can benefit from a hybrid model: embrace the creativity and speed of vibe coding for ideation and prototyping but rely on experienced engineers and proven processes to deliver safe, scalable, and maintainable products. Creativity is essential, but so is discipline. And when the stakes are high, professionalism (not just “the vibes”) must prevail.

If you are interested in software development projects with agile teams and experienced developers, contact us using this form.