If an investor is going to like your product, the sooner they see it, the better. Using AI to speed up MVP development is naturally an attractive option for ambitious founders who want to show off their product to investors as soon as possible. However, simply vibe coding your product isn’t going to cut it. Fast does not equal fundable. The secret is to be quick, but not to hurry. Instead of letting your product be consumed by AI slop, MobiDev leverages “AI-as-a-Partner with an expert in the loop” approach to ensure MVPs can be developed fast without sacrificing quality. This guide will show you how it works.
One of our authors, Rustam, was a speaker in our recent webinar about this topic. If you feel like watching rather than reading the article, take a look at the webinar recap and get access to the full recording via the link below.
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GET ACCESS FOR FREEWhat is Vibe Coding?
In February 2025, Andrej Karpathy, a co-founder of OpenAI, coined the term “vibe coding” to describe how simple it had become to entrust the software development process to large language models. He bragged about simply speaking aloud to AI agents to create, edit, lint, and debug code.
Countless projects, for better or for worse, have begun to rely on AI code generation tools for the brunt of their work. At their best, they can produce MVPs for investors that are well on their way to being finished products. At their worst, they grow eldritch abominations of software that may look normal on the outside but are deeply fragile at their core. Vibe coded software is often also full of dangerous security vulnerabilities that can be difficult to identify and correct.
Why Founders Try Vibe Coding for MVP Development
The reasons founders try vibe coding among other rapid MVP development approaches are obvious: the potential gains of launching an MVP extraordinarily quickly are remarkably high. The faster you can build an MVP, the sooner you can bring it in front of investors to get in on funding rounds. This also means that the product is cheaper to develop. Without the large tech team, and with the benefit of instant gratification, using AI is a no-brainer.
The 4 Hidden Pitfalls of Vibe Coding for MVP Development
Using AI for software development is the unavoidable future of the industry. However, there are four critical vibe coding risks that founders need to understand before they hand off development to monkeys with typewriters.
1. Architectural Weaknesses
Without the right guidance and context, AI models can’t fully plan out architecture or structure for your project. The resulting code may work, but it won’t be durable. Worse yet, that fragility can be difficult to correct without breaking functionality.
2. Security and Compliance Gaps
Vibe coding software could produce a functional MVP. However, are you certain that what you generated is secure and safe to use? Without the scrutiny of experienced developers, AI tools overlook glaring security problems. There have even been suggestions that AI models called sleeper agents could be programmed to deliberately inject backdoors and other vulnerabilities into software without your knowledge by an adversary. This is only the beginning; there are many more vibe coding security risks that experienced developers need to watch out for to ensure LLM security compliance.
3. Hidden Bugs and Scalability Failure
This is one of the most pronounced vibe coding challenges. AI-generated software may work at first, but over time bugs can become apparent that more thorough QA processes would catch. With fragile architectures, vibe coded applications are difficult to scale, especially when the prompters who generated the software have no idea how the application works.
4. Costly Rewrites Once Investors Ask for Proof
From a return on investment standpoint, this is one of the most critical risks of vibe coding. Smart investors are going to scrutinize your work. They want to know that you’ve done your due diligence to ensure that your product is robust, secure, and scalable. You may need to rewrite components of your application in response to their feedback or their requests, and those rewrites can be costly if you don’t know how your vibe coded MVP really works.
Real World Disaster: Security Catastrophe with Nx
Nx is a build system that helps developers manage projects and its maintainers develop the software using AI tools. However, in August, a critical vulnerability in the software enabled adversaries to steal cryptocurrency wallets from Nx users. Attackers tricked maintainers into merging a pull request with a GitHub Actions workflow. That workflow contained a bash injection vulnerability into the repository which had elevated permissions. This allowed adversaries to access sensitive tokens, such as the npm publishing token. From here, attackers managed to publish malicious versions of Nx and its plugins to begin scouring Nx users’ machines for sensitive credentials.
Had maintainers applied greater oversight to AI tools used in the development of Nx, the malicious PR might have been identified and stopped in its tracks. That’s why human experts need to guide AI coding tools, and not the other way around.
When Vibe Coding Makes Sense and When it Doesn’t
With these vibe coding challenges and risks in mind, it’s important to understand when developers should utilize vibe coding. Vibe coding is excellent for validating ideas, but not for creating products from scratch. Prototyping is an excellent time to test ideas with vibe coding. Hackathons, proof of concepts, and internal mockups are good examples. However, you need a more robust development method when approaching objectives like fundraising, MVP launches, user onboarding, and building scalable applications.
FAQ
What are the potential security risks associated with vibe coding?
Vibe coding, especially when used by developers who don’t have a clear understanding of the technologies involved in what they are creating, can result in many serious security risks. Developing in this manner without experienced oversight can lead to backdoors, poorly hardened databases and regulatory non-compliance. This can have a serious impact on customer and investor trust.
The MobiDev Alternative: AI-as-a-Partner, Expert in the Loop
To manage the risks and pitfalls of using AI coding tools, MobiDev has adopted an approach we call “AI-as-a-Partner with an expert in the loop”. This approach merges the efficiency of AI with human oversight and expertise. We utilize a five-step roadmap for this process:
Step 1. Context Creation
Vibe coded applications lack the most valuable context needed to create an MVP that meets the needs of your business, your investors, and your customers. To mitigate this problem, we start by building a portfolio of working context. Some examples of information we’ll put together are:
- Source files
- Logs
- Error traces
- Domain rules
- Style guides
We use custom scripts to gather these together in a bundle. The context is then delivered to an analytical model chosen for diagnosis and planning. Our objective at this stage is to provide enough information to be useful while keeping sensitive materials out of scope. Having humans familiar with the information is critical to ensure that this context is useful.
Step 2. Plan Analysis and Tuning
An AI takes the context we provided and comes up with a development plan based on that data. We examine the plan and tweak it to remove dead ends. We then can craft an execution brief that fits the architecture and business conventions that we need for the application. That prompt becomes a clear design artifact that our entire team can read.
Step 3. MVP Implementation
Now armed with refined instructions and the original context bundle, we now can deliver all that information to a coding model. This model follows the instructions we provided using the provided context to produce cleaner code. Experienced human developers request diffs, tests, and migration notes instead of raw blobs. This makes changes easier to manage and scrutinize. Humans inspect each stage of the process with a microscope to ensure that the project is headed in the right direction.
Step 4. Results Verification
We return to the analytical model that we started with to review the results of the code output. This model validates how functionality was implemented, checks edge cases, and flags regressions for further review. Our team runs tests, reviews metrics, and confirms the changes in a controlled environment. If we notice drift, we roll back and try again with a narrower scope.
Step 5. Final Check
When it’s time to check larger tasks, we add a second review pass focused on performance, observability, and failure modes. Only after human developers have verified that these metrics meet our expectations do we merge and deploy. Dashboards and alerts are used to catch problems early to avoid any surprises later.
Learn more about how to build an MVP with AI.
Vibe Coding vs AI-Assisted MVP Development: Side-by-Side Comparison
| # | Factor | Vibe Coding | AI-Assisted MVP Development (MobiDev) |
|---|---|---|---|
| 1 | Speed | Faster for prototyping due to informal workflows and fewer review stages. | Slightly slower due to multiple validation steps but ensures robust results. |
| 2 | Code Quality | May vary widely; relies heavily on individual developer skill, often lacks formal review. | High; code is produced with refined instructions, reviewed by humans, and validated by analytical models. |
| 3 | Scalability | Often limited; scaling can be difficult if code is not modular or well-documented. | Designed for scalability, with architecture and conventions tailored for future growth. |
| 4 | Security | Much higher risk of security vulnerabilities in the end product. | Sensitive information is kept out of scope, and multiple review passes include security and failure mode checks. |
| 5 | Investor Trust | May be lower due to lack of process transparency and inconsistent results. | Higher, thanks to documented processes, rigorous verification, and clear design artifacts. |
| 6 | Long-Term Cost | Potentially higher due to technical debt and the need for later refactoring. | Lower in the long run, as early validation and structured development reduces rework and maintenance expenses. |
The key element to remember is that AI-as-a-Partner with an expert in the loop maintains 80% of the speed of vibe coding while ensuring that results are 300% more reliable.
Why “Good Enough” Code Gets Rejected
Ian Garmaise is the COO of Virtual Film School and Venture Fellow at Venture Cooperative. In our webinar, Ian has excellent insight about why vibe-coded MVPs just don’t cut it for early investors. Early backers can clock AI-generated MVPs instantly. This has driven 70% of investors to demand technical validation before they even consider backing a project.
“AI is a co-pilot, not the pilot,” Ian explains. Trust is built through structured processes and evidence of scalability. “The more evidence you can show that what you have done is proven, the better shot you’ve got with sophisticated investors.” There are fewer VC funds out there, and most of the capital is flowing into large AI projects. As a result, smaller startups must demonstrate validation and scalability evidence to stand out.
Real-World Proof: 18-Hour CRM MVP Case
This CRM MVP development case study is an excellent example of how efficient AI-as-a-partner with an expert in the loop can be. We went from a simple idea to a deployed SaaS solution in 18 hours using an AI-assisted approach. This was completed 7.5x faster than traditional methods and cut costs by 76%. Acme CRM was developed on a tight budget and succeeded in demonstrating Treegress’s core product, a QA automation platform. This helped them maximize their return on investment.
Read the full case study to learn more.
Why Founders Choose MobiDev for MVP Development
Founders trust MobiDev because we balance quality with speed. Our AI-as-a-partner with an expert in the loop expertise allows us to deliver high-quality MVPs in record time. This structured, multi-model AI coding workflow enables quick and polished work with predictable cost in the range of $15–25K. Founders are proud to own clean code after the process is complete. Ready to see how this approach can help you score your next funding round? Learn more about our rapid MVP development services and book your AI-as-a-partner consultation now.
