EVERYTHING
According to AIN.ua, the landscape of mobile application development is evolving rapidly due to the integration of artificial intelligence. Software engineer Mykola Shurda notes that this change is not merely a matter of new languages or frameworks but a fundamental shift in how software is conceived and built. The distinction between different operating systems is becoming increasingly blurred as AI tools take over the heavy lifting of platform-specific implementation.
The limitations of traditional cross-platform tools
Before the rise of generative AI, the industry attempted to bridge platform gaps using technologies like React Native, Flutter, and Kotlin Multiplatform. While these tools offered some relief by allowing shared business logic or UI components, they often failed to provide a seamless experience. Developers still had to navigate complex platform-specific APIs, native animations, and performance optimizations.
Historically, the development cycle was frequently dictated by technical constraints rather than product goals. Teams often spent significant time answering "Who will build this and on what stack?" instead of focusing on the user experience. This technical bottleneck determined the cost, timeline, and priority of features in a project backlog.
A shift from coding to orchestration
The introduction of AI agents represents a departure from writing code manually. Instead of creating another wrapper for cross-platform compatibility, AI allows engineers to act as orchestrators. Because AI can generate the specific code required for different environments, the developer's role is no longer limited by their mastery of a single programming language.
This shift impacts the industry in three primary ways:
- Lower barriers to entry: Developers who understand application logic—such as data storage and server communication—can now port that logic across platforms without spending years learning every technical nuance.
- Increased velocity: Routine tasks like project setup, writing boilerplate code, and creating repetitive screens are completed significantly faster.
- Role transformation: Developers are becoming product architects who break down complex problems into smaller parts, distribute them to AI agents, and verify the final output.
Practical applications in modern workflows
Shurda highlights that this transition is already visible in daily operations. For instance, a web developer proficient in Angular or Vue can now complete tasks for Android and iOS within a single sprint without undergoing extensive retraining. By leveraging AI agents to handle the "technical translation" of code, engineers can maintain a unified vision for a product while ensuring it functions natively on every device.
While manual coding skills remain relevant, they are no longer the primary tool for daily production in high-velocity environments. The future of development lies in managing systems and verifying results rather than executing every line of code by hand.