Can AI code my app?

Let’s be honest, the hype is huge. Type “build me a to-do app in React” into ChatGPT or Gemini, and you’ll get working code in seconds. Paste it into your editor, and voilà, an app appears. No developer, no invoices, no deadlines. Sounds great, right?

But that’s not how real software works.

Most applications are not to-do lists. They involve third-party integrations, complex logic, user authentication, business rules, edge cases, responsive design, and scalability. And no AI tool today can handle all of that without human guidance.

So, AI is impressive. It can write lines of code, generate design systems, and even build entire components from a single prompt. So it’s no surprise that many business owners, especially non-technical ones, are wondering:

“Why do I need a dev team when AI can do it faster and cheaper?”

Fair question. But here’s the thing:

AI can help you start building an app. It just can’t help you finish one that works reliably, handles real users, or scales with your business.

 

Even the companies investing the most into AI (Meta, Microsoft, Google) are keeping their best developers. They're not replacing them with prompts. They’re equipping them with smarter tools. Why? Because high-performing engineers who know how and when to use AI are now more valuable than ever. When Meta restructured in 2025, the focus wasn’t on removing developers, it was on retaining the most capable ones.

At Ncoded Solutions, we incorporate AI into parts of our development workflow, and yes, it’s great for speeding up repetitive tasks and getting quick code suggestions. But when things get complex, when an app needs to be stable, secure, fast, and scalable, that’s where real developer experience still makes all the difference. So, AI is not here to replace developers. It's here to raise the bar.

AI can help you write code, but developers help you build products.

What AI can do well?

Let’s give credit where it’s due. Today’s AI tools can:

• Generate boilerplate code for common tasks
• Translate code between programming languages
• Suggest bug fixes and explain errors
• Help junior devs speed up their learning curve
• Act as a fast, always-available pair programmer

Yes, these tools increase productivity. Yes, they reduce development costs. And yes, hey make software more accessible.

But they don’t understand your product. They don’t know your users. And they don’t know what matters specifically for your business.

Where AI falls short

While AI can write code, it still can’t think like a developer...

It doesn’t ask questions. It doesn’t clarify vague requirements. It doesn’t push back when a feature makes no sense. It just writes what you ask, whether or not it fits your product, users, or long-term goals.

Here’s where it breaks down:

• No understanding of your business logic. AI doesn’t know why you need something, it just guesses what you mean based on patterns. Business rules? Special workflows? Internal terminology? Those all come from conversations with stakeholders, not code generators.

• It can't architect your app. This is crucial. Should you use serverless or monolith? When to optimize for speed vs cost? AI won’t help you make those strategic decisions. It can give you options, but it can’t judge what’s best for your context...

• Missing edge cases and real-world scenarios. AI-generated code often works in the happy path, but what happens when something goes wrong? Users input weird data? Network request fails? Multiple systems interact? Those situations are where real experience matters.

• No accountability. When something breaks, you can’t tell ChatGPT: “Hey, this crashed my app, fix it!” It won’t debug your logs or stay up all night with your dev team before a launch. That’s what developers do, right?

• Security and compliance risks. AI doesn't know the legal, ethical, or security standards your app must meet. It may suggest insecure code or use outdated libraries without understanding the consequences. A good developer catches that. AI doesn’t.

So while AI might look like it knows what it's doing, in reality, it’s just stitching together pieces from public codebases. It doesn’t understand why things work. And in software development, that’s a big problem.

Because your app isn't just a technical project, it's a business investment.

 

Vibe coding 🤔

The rise of AI tools has even inspired a new term among people: vibe coding. It describes the experience of using AI to generate code without fully understanding it, just hoping it works.

Sometimes the LLMs can't fix a bug so I just work around it or ask for random changes until it goes away.

This feels like a bad vibe 😅

It’s a fun way to explore and learn. But when you’re building something serious, something that handles real data, money, users, you can’t afford to rely on trial-and-error AI guesswork. That’s when you need developers who understand the system behind the code.

Accountability

When you're building something serious, a fintech app, a healthcare platform, a booking system, code isn't just about functionality. It's about trust.

If your app crashes or exposes sensitive user data, the worst thing you can say is:

“Sorry, the AI made a mistake… and we’re not sure why.”

Let’s be real, you’ve probably had this situation at least once. You asked ChatGPT something, got a confident answer, and then, when you pushed back with “Are you sure?”, it immediately changed its tone and said:

“Apologies, you’re completely right.”

That’s fine for fun facts or brainstorming. But in software that runs a real business? You don’t want apologies. You want answers.

With traditional, human-written code, every decision can be traced. Every function, every variable, every security layer. Someone made that call, and someone can explain or improve it.

With AI-generated code, that trail can disappear. No context. No logic behind the choice. Just output from a model trained on code it didn’t write, and doesn’t fully understand.

We tried letting AI build a real marketplace

We tested Cursor, one of the most hyped AI coding tools right now. The goal? Build a complete marketplace for handmade pottery, with buyers, sellers, admins, cart, wishlist, reviews, filters, dashboards, etc.

Sounds doable, right?

Here's our prompt:

Build a full-featured online marketplace for handmade pottery using Next.js (frontend) and Express.js (backend). 
The platform must support three user roles: buyer, seller, and admin.

Authentication
- Email-based sign-up and login
- Secure sessions or JWT-based login persistence

Buyer features
- Browse all products on homepage
- Product details page with images, title, description, price, category, seller name, average rating
- Keyword search
- Filters: category, price range, rating
- Sorting: newest, price low to high, rating
- Add to cart and view cart
 -Simple checkout form (name, email, shipping address — no payment integration yet)
- Add to wishlist
- Chat with seller
- Leave 1–5 star review with comment (only after purchase)
- View purchase history

Seller features
- Dashboard
- Create new listing: title, description, price, category, quantity, upload multiple images
- Edit/delete own listings
- View received orders
- Chat with buyers
- View reviews
- Mark items as sold out
- View stats: number of views per listing

Admin features
- Admin login
- Admin dashboard with list of all users (option to block or delete) and list of all listings (option to remove or edit)
- Moderate chats and reviews
- View stats: most viewed listings, most sold items, top sellers

Other requirements
- Pagination for product listings (50 per page)
- Responsive UI
- Basic but clean layout
- Clear error messages on failed login or invalid inputs
- Clean, modular code structure, organised folders, reusable components

Generate all the code necessary to make this marketplace work from start to finish. All features must work.

Here’s what worked:

• Cursor did generate a full project, including pages for buyers, sellers, and admin, with a functioning product catalog and basic layout.

• Product listing display worked well. Products showed images, titles, prices, and ratings. Pagination and sorting (e.g. price low-to-high) functioned correctly.

• Search worked as expected, allowing users to find listings by keyword.

• Leaving a review was functional, the star rating and comment were saved and displayed on the listing page.

• Add to cart worked, and items could be reviewed in the cart before checkout.

• The admin dashboard was quite solid, with an overview of listings, users, and useful stats like most viewed and most sold items.

---

Here’s what didn’t:

• Cursor generated separate pages for each user type (admin, buyer, seller), but misunderstood the concept. These weren’t supposed to be separate routes, they were roles that should have had restricted access and different permissions based on user data.

• Authentication was broken. There was no logic to differentiate between user roles. Anyone could access any page just by knowing the route. That was a serious security flaw.

• Creating listings didn’t work at all. The UI was there, but nothing happened on submit. It required manual developer intervention.

• Many pages (like product details or listing pages) returned 500 or 404 errors by default, and we had to patch them just to get the app running locally.

• Validation was missing. Required fields weren’t enforced, so empty forms could be submitted across the site.

• Filters lacked core logic like min/max price, and input validation was completely absent.

• Chat was non-functional. Instead of enabling buyer–seller conversations, it just showed a generic “Chat” page with no logic behind it.

• Stripe integration was promised, but never actually implemented. Cursor didn’t ask for API keys or even explain that they were needed.

• Responsiveness was half-done. Many layouts broke on mobile, even though responsive design was explicitly requested.

So... Can AI code your app?

It can generate one.

But will it work the way you expect? Will it cover all roles, all edge cases, security, logic, validations, responsiveness, user flow?

Not really... 😕

What you’ll get is a prototype, something that resembles a product, but cracks as soon as you start clicking...

Tools like Cursor can be useful for quick drafts and visualizing early ideas. But turning those drafts into a working, reliable app still takes experience, planning, and iteration.

AI is a great assistant. But it’s not your product team.

If you’ve got an idea, we’ll help you build it the right way. Let’s talk.