The term 'vibe coding' is echoing through the tech world in 2025, painting a picture of developers orchestrating AI with natural language to conjure software seemingly out of thin air. While the promise of accelerated development and AI handling the grunt work is captivating, it's essential to pause and ask: is this AI-driven approach truly the revolution it's claimed to be, or is it more hype than substance for many real-world applications? This article aims to ground the discussion, moving beyond the buzz to critically examine where 'vibe coding' genuinely adds value today – identifying the specific projects and developer profiles it suits best – while also highlighting the significant limitations and pitfalls that make it far from a silver bullet in the current landscape, proving it's a potentially powerful tool, but one that demands careful understanding and skillful application.
Different people understand and use or want to use vibe coding differently, but the main distinction lies between developers and non-developers. Therefore, let's focus in more detail on what Vibe Coding looks like for developers and non-technical users.
Vibe Coding for Non-Developers
Non-developers most often view vibe coding as a way to finally create their dream applications or launch their IT startup without needing to hire expensive developers (and often designers too) or spend a significant amount of time mastering programming. New "Vibe coding" applications are constantly emerging in the market to fill this niche, offering to program and maintain applications using only AI, without any understanding of the source code. Are such applications genuinely effective at this stage, and can they truly help non-technical users launch their tech startup or realize an application that solves their necessary tasks? The answer is both yes and no. They are undoubtedly promising and can address the aforementioned tasks, but only with the right approach and an awareness of certain nuances, which we will explore further.
The Main Problems of Vibe Coding for Non-Technical Users
- Security Issues. Unfortunately, current Coding AI agents have significant problems ensuring the security of the applications they develop. Even though an application created using Vibe coding might function correctly, it could potentially harbor serious security vulnerabilities. Since non-developers cannot perform an analysis of the AI-generated code, they cannot be certain of their application's security. Therefore, we do not recommend that non-technical individuals use Vibe coding to develop final product versions intended for use by others. We advise limiting development to applications for personal use or creating an MVP (Minimum Viable Product) for your startup. An exception could be applications that monetize through advertising and do not require user registration or the transfer and storage of personal data. In this scenario, the risk of your application being hacked and attackers gaining access to your server and application still exists, but at least you would primarily be accountable to yourself.
- Software Maintenance. Although AI is capable of writing the initial version of a product, the real challenges begin during software maintenance. In almost all cases, after releasing the first version, you will want to implement new features, fix bugs, or make design revisions. When developing a commercial product, creating the application is merely the first step; your application must be continuously refined and improved throughout its entire lifecycle. Currently, AI Agents handle new code generation reasonably well, but they perform much worse when it comes to maintaining an existing codebase. Each subsequent update tends to complicate the situation further, leading to a snowball effect where every new update introduces more errors into the existing code, and each release takes progressively longer. Unfortunately, it's not uncommon for an AI agent to break existing functionality while attempting to fix or implement something new. Furthermore, AI agents can get stuck in decision loops: implementing a new feature introduces a bug; requesting a fix for the bug breaks the new feature; asking to restore the feature brings back the original bug. This is a highly simplified example; the cycle can consist of multiple iterations of feature fixes and bug corrections, but the outcome will be the same – you'll revert to the starting point, either with an application lacking the bug or with the bug but also the new feature. A developer can assist the AI agent by crafting precise technical prompts, but this option is unavailable to a non-technical user operating the AI agent.
Recommendations on Vibe Coding for Non-Developers
- Utilize Vibe coding for developing simple applications that perform one or a few functions and do not demand extensive Software Maintenance efforts.
- Avoid developing applications that require user registration and the transfer or storage of personal data. This will reduce the probability of security issues or lessen their impact on the application. You can definitely make exceptions when it comes to developing applications for personal use, presenting the idea to early investors, or running product validation (MVP).
- Select specialized Vibe Coding tools tailored to your tasks. If you aim to develop a website, use a vibe coding tool designed for website development. If you need a web application, search for a vibe coding tool specifically for web application development. If you are not a developer and will not be interacting with the code regardless, avoid using popular AI agents designed for developers, such as Cursor or Windsurf. Specialized vibe coding tools restrict the AI to a specific technology stack and impose numerous rules and limitations using system-level prompts, which you would be unable to implement on your own. For instance, according to the system prompts of Lovable (a popular Vibe coding tool for web application development), the AI Agent is limited to developing only single-page web applications with a fixed technology stack - React and Tailwind. With a significant number of systemic constraints and rules, the AI receives clearer instructions and technical limitations, which diminishes the likelihood of security issues and enhances the quality of the generated code, thereby facilitating software maintenance.
- If you nonetheless decide to launch your startup using a Vibe coding tool, be prepared for a greater than 90% probability that you will be unable to continue its development and maintenance by hiring developers without a complete rewrite or, at the very least, substantial code refactoring. Supporting code generated by Vibe coding tools will be considerably more expensive than developing new code from scratch. Under normal circumstances, after developing an MVP, the team simply continues to evolve the product by adding new features. In the case of a Vibe coding startup, your developers will either have to write an entirely new MVP and develop it or significantly rewrite the existing one.
Vibe Coding for Developers
The primary question concerning Vibe coding for developers is whether it truly exists in a practical form and, if so, whether an experienced developer actually needs it. Before delving into this topic, it's crucial to clarify terminology. By "vibe coding," we mean, at a minimum, the comprehensive resolution of developer tasks using AI prompts with minimal manual code alterations, and at most, the development of an entire application with AI. We do not consider code writing using AI agents within IDEs such as Cursor, where AI is used simply as an assistant to write some code segments, as full-fledged vibe coding. To call the process vibe coding, the AI Agent should operate at the task level and not at the level of writing lines of code. By "developers," we refer to engineers at a Middle level of seniority or higher. This article will not address the use of Vibe coding by junior developers, as this subject arguably warrants a separate discussion.
The Main Problem of Vibe Coding for Developers
The central issue with Vibe coding for developers is identifying tasks where Vibe coding would be more efficient than traditional programming augmented by AI Agents. A developer can often solve small, uncomplicated tasks more quickly than they can formulate prompts for an AI agent. On the other hand, more complex and complicated tasks will be handled much more efficiently by the developer than by an autonomously working AI Agent. Consequently, developers handle simple tasks themselves and tackle large, complex ones with AI agents, using them as assistants rather than relying on full-fledged Vibe coding. Currently, AI agents are not yet capable of comprehensive product development and maintenance at the level of an experienced developer.
The Main Reasons Why Vibe Coding Doesn't Work Well for Developers
- Low competency with complex tasks and large codebases: Modern AI coding agents exhibit a low level of competence when dealing with complex tasks and extensive project codebases. Their current capability is akin to a junior developer level with an excellent academic background but lacking practical experience. In specific instances, an AI can write a particular function or class as proficiently as a Senior developer. However, once the task complexity increases beyond writing isolated code segments to encompass holistic problem-solving, the AI Agent's competence declines back to a Junior developer level.
- Lack of AI Agent autonomy: Unlike a human developer, an AI Agent's operational environment is considerably more constrained, as it often lacks the ability to directly interact with the application it is developing. An AI agent typically cannot independently gather necessary data or perform manual testing before tackling a task; it must rely solely on the provided prompt and the project's code.
- Inability to self-verify and iterate: More critically, an AI agent cannot independently verify the results of its work and make the necessary corrections to ensure the task is solved accurately. Generally, a developer is satisfied with an AI agent's performance when it executes the task correctly on the first attempt. If it becomes necessary to describe what went wrong and copy error logs (if they even exist), it breeds frustration. Consider how frequently you managed to solve even a minor task correctly on the first try—writing the code, running it, and observing that everything worked as expected. When it happens to me, I'm very surprised and immediately look for a catch. I then do detailed testing to find out what could have gone wrong to make sure I didn't miss something. When it comes to AI agents, we expect them to produce correct results by default, but it seems quite miraculous that they often deliver accurate results on their first try.
Recommendations on Vibe Coding for Developers
It must be stated upfront that, at present, the market lacks comprehensive solutions that would enable a developer to genuinely solve tasks end-to-end without writing code, relying solely on AI. However, opportunities already exist for fully delegating certain tasks to AI or, at the very least, significantly enhancing the autonomy of AI agents:
- Use AI agents to master new technologies: Employ AI agents as a starting point for developing small services or complete applications using technology stacks that are new to you, or when developing new types of applications with which you have no prior experience. AI agents are adept at creating new application templates from scratch when there's no need to maintain existing code. This does not imply that AI will perform everything perfectly and correctly; you must still study its code and understand the technology independently. However, using AI to familiarize yourself with new technologies significantly reduces the time invested.
You can also try to realize the initial solution by starting a project with technologies you are familiar with. Some developers claim that generating an application using AI can cover roughly up to 70% of the requirements - possibly, you will be one of them.
- Use AI to write tests: Modern AI agents excel at writing unit and functional tests based on your existing code. Numerous AI tools for test generation are currently available on the market. AI Agents integrated into IDEs also perform this task excellently. You can confidently delegate this part of your work to an AI Agent, but remember to review its output.
- Decompose tasks for the AI Agent: As mentioned earlier, a contemporary AI Agent functions at the level of a junior developer. Therefore, instead of assigning it a complex, multi-stage task, break it down into small, comprehensible sub-tasks. You will likely solve some sub-tasks yourself much faster than you could write a prompt for them, but other tasks can be fully entrusted to your Coding Agent. Modern Coding Agents can perform task decomposition themselves, but the issue here is that despite breaking the task into sub-tasks, the AI will attempt to execute everything in one go, and you will receive the final result immediately, potentially with problems arising at various stages. This is not yet Vibe coding, but it is an attempt to assign the AI agent more substantial tasks than when using AI merely as an assistant.
- Use AI for bug fixes: In most cases, bug fixes do not require changes to the project architecture and often boil down to making changes in one or two files. In this scenario, you'll need to keep it balanced: if you already know the cause of the bug and how to fix it, it will likely be faster to apply the fix yourself rather than write a prompt for the AI. However, if you do not know the precise cause of the problem, you can ask the AI Agent to analyze your code, identify, and fix the bug. Naturally, even in the event of a successful fix, a detailed review of its work is essential.
- Utilize MCP servers: An MCP server is a program that provides tools and data access capabilities for LLMs. MCP Servers enable your AI Agent to operate more autonomously. The AI Agent can independently retrieve necessary data and use tools to interact with third-party applications and your operating system. Numerous MCP servers are already available that can facilitate interactions between your AI Agent and your git repository, task tracker, database, and even browser. Do not limit your AI agent to just your codebase; provide it access to additional resources. This will improve its autonomy and the quality of its task execution.
- Use Webvizio for prompt generation (Web only): Automatic prompt generation helps eliminate the dilemma of choosing between spending time solving a task manually and writing prompts without any guarantee of a positive outcome. When using Webvizio, a developer can assign any task to an AI Agent without investing time in writing a prompt. You can quickly resolve uncomplicated tasks or even assign a more complex task to an AI agent; if the AI fails, you lose minimal time, but if the AI executes everything correctly, the time saved will more than compensate for the effort of simply copying a pre-generated prompt for your task.
Conclusion: Navigating the Nuance of Vibe Coding
"Vibe coding" in 2025 presents a fascinating, yet complex, landscape for the software development industry. It's clear that the concept holds different promises and pitfalls depending on who uses the AI.
For non-developers, vibe coding tools offer an alluring entry point into application creation, potentially democratizing development for simple projects, personal utilities, or initial MVPs. However, this path is fraught with significant risks, primarily concerning security vulnerabilities in AI-generated code and the immense challenge of long-term software maintenance and evolution. The dream of a no-code startup fully realized and scaled by AI alone remains, for the most part, a distant one.
For experienced developers, full-fledged "vibe coding" – where AI autonomously handles complex development tasks from natural language prompts – is not yet a practical reality for mainstream projects. Current AI agents, while impressive, function more like highly capable junior developers. They excel at well-defined, smaller tasks such as boilerplate generation, writing tests, and assisting with specific bug fixes. Their utility diminishes rapidly with increasing task complexity, codebase size, and the need for architectural understanding. Developers will find more value in using AI as a sophisticated assistant rather than an autonomous replacement.
Ultimately, "vibe coding" is not a monolithic revolution set to instantly transform all software development. It is an evolving set of capabilities that, when understood and applied strategically, can offer tangible benefits. The key lies in recognizing its current limitations, choosing the right tools for the right job, and maintaining a critical perspective. As AI continues to advance, the "vibe" may become more harmonious with the "code," but for now, skillful human oversight, robust testing, and a pragmatic approach are indispensable for navigating this new frontier successfully. It’s a powerful new instrument in the orchestra, but it still requires a skilled conductor.
What's your perspective? Have you thought about the possible effects of vibe coding solutions on your development workflow?
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