Why vibe coding could be the future of mobile app development

Vibe coding is a genuinely interesting shift in how software gets made. The term, popularised in early 2025, describes a way of building digital products where you describe what you want in plain language and an AI tool generates the code for you. You are directing, not writing. The barrier to entry drops considerably, and people who have never touched a line of code are suddenly building functional prototypes in days rather than months.

A demonstrable product changes the conversation far more than a pitch deck ever can.

For lifestyle brands, wellness founders, and early-stage startups in particular, this matters. The traditional path to a mobile app involved a substantial budget, a technical co-founder or agency, and a development cycle that stretched across many months before anything was testable. Vibe coding compresses that timeline dramatically, and that compression has real strategic value.

But speed is a tool, not an outcome. Getting to a working build faster does not automatically get you to a good product, and the gap between those two things is where most early-stage apps quietly fail. Understanding what vibe coding genuinely changes, and what it does not change at all, is the difference between using this moment well and just moving faster toward the wrong destination.

What Vibe Coding Actually Is and Why It Has Arrived Now

Vibe coding is less a formal methodology and more a description of how AI-assisted development actually feels in practice. You describe a feature, a screen, or a user flow in conversational language. The AI, using tools like Cursor, Replit, or Bolt, produces working code. You review it, refine the prompt, and iterate. The process is closer to creative direction than traditional programming.

This has arrived now because large language models have become good enough at code generation to produce outputs that are actually usable, and because the tooling around them has matured to the point where non-technical users can navigate the process without needing to understand what is happening underneath. A founder who can describe their product clearly can now produce something functional without a developer in the room.

The timing also reflects a broader shift in how software is built. Low-code and no-code platforms have been eroding the technical barrier for years. Vibe coding accelerates that trend considerably, pushing the question of who can build an app well beyond the traditional boundary of engineering teams. According to Forrester, low-code platforms can be up to 10 times faster than traditional development methods. That is a structural change in what is possible at the early stages of a product's life.

How Low-Code and AI Tools Are Changing Who Can Build an App

Until recently, building a mobile app meant either hiring a development agency, finding a technical co-founder, or learning to code yourself. Each of those routes carried significant cost, time, or both. Low-code tools changed the first part of that equation by giving non-technical people a way to assemble functional digital products using visual interfaces. AI-assisted coding has now changed it further, because the interface is no longer visual at all: it is conversational.

This matters most for founders in the early stages of a product who need to demonstrate something real before they have the resources to build it properly. A working prototype, even a rough one, changes the nature of every conversation, whether that is with investors, early users, or potential partners.

We saw this with a trading card platform client who had spent time trying to raise funding with pitch materials but was not making the progress he needed. He decided to build as far as he could using a vibe-coded version of the product, and that put him in a meaningfully stronger position because he had something demonstrable to show people. The deck described the product. The prototype was the product, at least enough of it to make the vision concrete and credible.

The shift is fundamentally about access. The people with the clearest understanding of a problem worth solving are often not the people with development skills. Vibe coding and low-code tools start to reconnect those two things.

Why Getting to a Prototype Faster Is Genuinely Valuable

Speed to prototype is not just a convenience. It changes what is testable, what is fundable, and what kind of feedback you can act on. A prototype in the hands of real users will tell you things that no amount of planning, research, or stakeholder discussion can surface. You find out whether people understand the product, whether they trust it within the first few seconds, and whether the core mechanic actually works the way you imagined it would.

Getting there faster means you can run that test earlier, fail earlier if you are going to fail, and course-correct before the costs are significant. Engineers, according to Playbook UX, spend up to 50% of their time fixing problems that could have been caught at an earlier stage. A prototype that surfaces those problems before full development begins is a cost control mechanism.

There is also a qualitative value to having something real to show. As we found with the trading card platform client, a demonstrable product changes the conversation far more than a pitch deck. Investors, users, and collaborators respond differently to something they can see and touch. The abstract becomes concrete, and feedback becomes specific rather than speculative.

A prototype that surfaces problems before full development is a cost control mechanism.

The risk is treating the prototype as the end point rather than the start of a more considered process. Speed is the advantage. Confusing speed with completeness is where things begin to go wrong.

Before you build anything, write down the three things you most need to learn from your prototype. Design the build around answering those questions, and treat everything else as secondary until you have your answers.

The Gap Between a Working Build and a Good Product

A working build proves that something functions. It does not prove that it works for people. That distinction is where most early-stage products run into trouble, and it is a distinction that vibe coding, for all its usefulness, does nothing to close automatically.

Nearly 60% of app features are rarely or never used, according to Futuristic Bug. That figure points to a systematic problem with how features get decided: they reflect what the builder thought the user wanted rather than what the user actually does. A faster build process does not fix that. If anything, it makes it easier to build the wrong things quickly.

The gap shows up in specific ways. A screen that makes logical sense to the person who designed it confuses someone encountering the product for the first time. A flow that works technically produces anxiety in a user who cannot work out where they are or what comes next. Copy that describes a feature accurately fails to communicate its value. These are design and psychology problems, and they require a different kind of attention.

One useful way to pressure-test any screen is to question every piece of information on it. Consider what the user's emotional state is at that moment. Ask whether each element adds something or just adds complexity. If information can be introduced later in the journey at a point where it actually makes sense, move it there. Showing everything at once is rarely the right answer, and it is a pattern that vibe-coded builds tend to reproduce because the AI has no understanding of the user's emotional context.

When Founder Conviction Overtakes User Evidence

One of the more consistent patterns we see in early-stage product work is a founder who has a strong, clear vision for what they are building, usually because they are solving a problem they have experienced themselves. That personal conviction is genuinely valuable. It sustains the work through difficult periods and gives the product a point of view. But it also carries a risk: the founder's certainty can make it hard to hear what research and user testing are actually saying.

We encountered this on two projects, a fitness and wellness app and a grassroots football product, where founders with real passion for their vision began to discount data emerging from research, focus groups, and surveys. When the evidence does not match the conviction, the evidence tends to lose. The product gradually becomes a reflection of the founder's preferences rather than the user's needs. Signs that this is happening include an excessive drive to perfect every detail before launch, repeatedly rolling back decisions that had already been signed off, and extended periods of indecision about relatively small choices.

In both cases, we flagged the trajectory early. In both cases, the projects exhausted their budgets in design and build without reaching a fully live product. What we were trying to do in challenging those founders was not to dismiss the work they had already done, but to add the dimension that was missing. The competitive analysis, the market mapping, the feature thinking: none of that loses its value when user research is added. It just gets a sharper edge.

If you find yourself resisting feedback from research because it contradicts what you already believe, pause and ask whether the research is wrong or whether your assumption needs testing. The two are very different situations.

How Early Decisions Shape Everything That Follows

The decisions made in the first weeks of a product's build have a disproportionate influence on everything that comes after. Information architecture, navigation patterns, the sequencing of onboarding steps, the technical framework underneath it all: these are not easily reversed once development is underway, and changing them later costs significantly more than getting them right early.

This is where the speed advantage of vibe coding can become a liability if it is not managed carefully. Moving quickly into build means moving quickly past the decisions that most need deliberate thought. The AI will generate something functional. It will not ask whether the structure it has produced is the right one for the people who will use it.

We worked on a proof-of-concept project for a company building an app to share memories with audio attached. Early on, we looked at integrating with Spotify for short audio clips. The problem was that Spotify lacked a robust API for clips, and users would have needed an existing Spotify account, which created unnecessary friction in a product that was supposed to feel light and personal.

We switched to Deezer, which had a stronger API, supported clips without requiring users to be logged in, and gave us access to a larger catalogue. A secondary benefit emerged: when users wanted to hear a full track, there was a natural path to a Deezer subscription, which created an affiliate revenue stream alongside the core product. That decision, made early in the proof-of-concept phase, shaped the product's commercial model as well as its user experience.

Early decisions are rarely just technical. They carry emotional and commercial weight that only becomes visible later.

The Hidden Cost of the Wrong Interaction at the Wrong Moment

Every interaction in a digital product carries an emotional charge. Asking a user to do something, choose something, or give something at the wrong moment in their journey produces friction, and friction in the wrong place produces anxiety, doubt, or abandonment. These effects are rarely dramatic enough to be obviously traceable to a single design decision, which is exactly why they are costly. The product underperforms, but nobody can point to the reason.

We examined a meditation app where the visual design was actually doing its job well. The soft gradients and breathing animations were slowing users down behaviorally before they had read a single word, which is a mark of good emotional design: the interface itself was producing the calm rather than relying on copy to describe it. But the app then asked users to select a goal before they had done anything in the product. Choosing between sleep, stress, and focus requires a decision, and a decision at that moment introduces friction. Friction increases anxiety. That directly contradicted the app's entire reason for existing.

The same structural error appears across a wide range of product categories. Onboarding flows that ask for commitment before delivering value. Forms that request information before explaining why it is needed. Navigation that offers too many options at the moment when a user most needs to be guided. In a vibe-coded build, these errors are easy to generate and easy to miss, because the AI has no model of the emotional state the user is in when they arrive.

Map the emotional state of your user at each step of onboarding before you design any of those steps. A user arriving at a wellness app in a moment of stress needs a fundamentally different first screen than one who is already calm and curious.

Choosing the Right Technical Approach Before You Start Building

One of the questions that often gets resolved too quickly in the excitement of starting a build is whether the product actually needs to be a native app at all. The assumption that a mobile product means an app store download carries real consequences for adoption, particularly in the early stages when you need people to engage with minimal friction.

On a project we ran for a company building a surveying tool for performance coaches, the original plan involved audience members downloading a native app to participate in live surveys. We felt that was too high a barrier for what was essentially a simple touchpoint. Someone sitting in an audience, asked to download an app they have never heard of to answer a quick question, will often just not bother.

We proposed a different approach: the presenter creates the survey in a native app, a QR code appears on screen, and anyone scanning it lands on a fully branded, mobile-responsive web page. The experience feels native without the friction of the app store, and survey completion rates were significantly higher as a result.

The broader question of native versus web-first, or hybrid frameworks versus progressive web apps, has meaningful implications for app development time, cost, and user experience. Web-first approaches launch considerably faster than native mobile apps, according to Agile Soft Labs. That speed advantage is worth examining honestly before committing to a native-first path.

Why Design Thinking Becomes More Critical, Not Less

There is a tempting logic to the idea that if building is easier, design matters less. If anyone can produce a functional product in a few days, the need for careful, considered design thinking is reduced. The opposite is true. When building is harder and slower, the friction of development acts as a natural filter. Poor design decisions get caught because there is time to catch them. When building is fast, that filter disappears, and poor decisions ship.

The discipline of emotional design, thinking carefully about how the product makes people feel at each step and engineering interactions that produce the right emotional state, does not become less necessary when AI can generate the code. It becomes the primary variable that separates products that work from products that function. A vibe-coded build can produce a technically sound screen in minutes. It cannot decide whether that screen should feel energising or calming, whether the copy should reassure or excite, or whether asking a particular question at that point in the journey will help the user or unsettle them.

When emotions are built into the design process from the beginning, every decision has a reason behind it. The colour choices, the micro-interactions, the sequencing of information: these stop being aesthetic calls and become deliberate responses to the emotional state the product needs to produce. That level of intentionality is exactly what generative tools cannot replicate, and it is exactly what users feel, even when they cannot articulate why one product feels trustworthy and another does not.

1. Define the emotional state you want users in at each key moment before designing those moments.
2. Review every screen for whether the interaction itself produces that state, not just whether the copy describes it.
3. Test with real users early, focusing on how they feel rather than what they say they think.
4. Revisit the first 30 seconds of experience repeatedly, because that is where trust is formed or lost.

Conclusion

Vibe coding is a real and useful development in how digital products get made. It lowers the barrier to a working prototype, gives non-technical founders a route to something demonstrable, and compresses the time between an idea and a testable version of it. Those are genuine advantages, and the founders and teams who use them well will move faster and learn faster than those who do not.

But the core challenges of product development have not changed. Getting to a build quickly does not automatically get you to the right build. The emotional experience of using a product, how it makes people feel in the first thirty seconds, whether it builds trust or erodes it, whether it calms or creates friction, is still shaped by design decisions that require human judgment. AI tools have no model of a user's emotional state. They cannot decide whether a question asked at onboarding will feel helpful or intrusive. They cannot tell you whether your founder conviction is being confirmed by evidence or substituting for it.

The projects that go wrong do so in recognisable ways: building faster than the design thinking can keep up with, letting conviction override research, making early technical decisions without considering their downstream effects on user experience. The projects that go well tend to treat the speed that vibe coding offers as an invitation to test and learn more, not as a reason to skip the thinking.

If you are building a digital product and want to think through where design and behavioural psychology fit into your process, let's talk about your product.

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