How easy is it for a developer to build a basic Android app in 2026 using AI?

I have been writing code since 2003. I started with C++ 98 and, at the beginning of the 2010’s, I worked my way up to Java and Objective-C which, by the end of the 2010’s and the start of the 2020’s, had become Swift and Kotlin. So I was there for all the improvements, but nothing even compares with what I experienced in the last few days.

I heard a lot of talk in the last years about how AI is replacing developers and how this process will lead to the extinction of this noble profession. So I decided to put this theory to the test. I downloaded latest version of Android Studio and started working on a brand new Android application. To be honest I am not a complete beginner when it comes to mobile applications since during the 2010’s I did work on a lot of iOS applications so I was somewhat familiar with the mobile ecosystem. But I had never worked on a native Android app before. I was totally new to this development environment and did not know what to expect.

The Android Studio experience

Since I had worked in Java for a few years in college I though it would be a good idea to take a short introductory course in Kotlin. So coming from Java, Kotlin looked very familiar, it looked a lot like the transition from Objective-C to Swift. You have the usual OOP functionality that you would expect, like variables, functions and classes, but you also have a lot of other new features like higher order functions. So Kotlin was a nice surprise for me, but the actual shocker was still to come.

It seems that Android Studio has Gemini AI support built directly into the IDE. It is as simple as prompting the AI for whatever you need done and it will do it for you, no questions asked. And I’m not just referring to code here, which by the way, is generated close to perfection. It will generate icons, app descriptions, change logs and even a privacy policy for your app! So basically anything you would ever need for creating and publishing a basic Android app. I am always mentioning this “basic” attribute and I will shortly explain why.

The Good News

And you are probably now curious about how well Gemini does when prompted to generate code that should work in the context of an actual production-grade application. And the short answer is: OK. Actually, a lot better than I was expecting. The last time I used AI for coding was some time ago when I need to convert a bunch of Python code snippets into C# code and AI offered quite a mixed performance for this task, so I wasn’t expecting much. But it seems that the Gemini integration from Android Studio really does a decent job of understanding the entire context of the application as long as the app does not get too large.

Gemini generates correct code that is correctly corelated with the user prompt more than 90% of the time. It understands most prompts with ease as long as you keep a coherent terminology throughout your prompts. I is also able to understand and execute larger prompts as long as they are clear enough. This is extremely impressive in my opinion and it really feels like you have your own junior developer that is able to execute any command you can imagine. No wonder IT companies are not hiring junior developers anymore.

The Not so Good News

But it’s not all perfect as you would expect since AI may introduce errors, bugs or even duplicate code. You need to always check the changes carefully and make sure that the AI does not remove working code that may break existing features, since it really has a bad habit of doing that sometimes. Also, sometimes it implements the feature but it doesn’t always work quite right so you need to manually test its changes to make sure there are no hidden bugs. So basically, the developer testing part needs to be done by the developer.

Things really start to slow down once the project reaches a certain size. The AI cannot comprehend the entire complexity of a large project and all the dependencies that this implies so it becomes less effective. If you intend to use AI for larger projects I suggest to use it only for localized changes and leave the architectural changes for the actual human developers. Than being said, I have to mention that I managed to create a fully functional nutrition and workout logging application from scratch with the help of AI in just 4 days. Such an application used to take me at least a month to develop so I guess AI is a win in my books.