Overview of AI Tools for Kotlin Development: From Code Generation to Testing

Online Python Trainer for Beginners

Learn Python easily without overwhelming theory. Solve practical tasks with automatic checking, get hints in Russian, and write code directly in your browser — no installation required.

Start Course

AI Tools for Kotlin Development: Overview of Modern Solutions

Kotlin is firmly establishing itself among the top modern programming languages, especially in the field of Android development and server applications. However, as project complexity grows, so does the need to automate routine tasks. Tools based on artificial intelligence come to the rescue. In this article, we will look at the best AI solutions that help Kotlin developers write code faster, find errors more efficiently, and focus on architecture rather than boilerplate code.

1. JetBrains AI Assistant — Built-in AI for IntelliJ IDEA

JetBrains, the creators of Kotlin, have integrated AI Assistant directly into their development environment. This tool understands the context of your project and offers:

Completion of entire functions and classes based on natural language comments.
Generation of unit tests for Kotlin code (JUnit, Kotest).
Explanation of complex code and refactoring considering Kotlin idioms.
Integration with Git — AI can write commit messages.

The tool is especially useful for teams using Kotlin Multiplatform, as it correctly handles expect/actual declarations.

2. Tabnine — Universal AI Assistant with Kotlin Support

Tabnine is one of the market leaders in code autocompletion. Its key features for Kotlin developers:

Trained on millions of open-source repositories in Kotlin.
Generation of entire blocks: data classes, sealed classes, extension functions.
Smart autocompletion for coroutines — suggests correct dispatchers and scopes.
Works locally (optional), which is important for projects with high security requirements.

3. GitHub Copilot — Powerful but Requires Fine-Tuning

While Copilot handles Java well, its effectiveness for Kotlin depends on context. Recommendations:

Add more auxiliary annotations to the project (@JvmStatic, @OptIn).
Copilot understands Android specifics (Compose, ViewModel) better than pure backend on Ktor.
It often suggests Java solutions that need to be adapted for Kotlin — be careful.

4. Kodee AI — Specialized Kotlin Assistant

Kodee AI is a young but promising startup focused exclusively on Kotlin. Its strengths:

Deep understanding of Kotlin specifics: null-safety, scope functions (let, apply, run).
Generation of DSL code (e.g., for Ktor or Anko).
Automatic migration from Java to Kotlin considering language idioms.
Integration with Gradle — AI suggests how to fix dependency conflicts.