Building AI-powered Applications with Kotlin

How do you add AI capabilities to a Kotlin application responsibly? In this course, Building AI-powered Applications with Kotlin, you'll gain the ability to add production-grade, LLM-powered features to Kotlin/JVM applications responsibly.
How do you add AI capabilities to a Kotlin application responsibly? In this course, Building AI-powered Applications with Kotlin, you'll gain the ability to add production-grade, LLM-powered features to Kotlin/JVM applications responsibly. First, you'll explore the architecture of an AI-powered Kotlin application - model providers, prompts, tools, memory, and retrieval - and configure a secure, coroutine-ready Kotlin project that sends typed chat requests through a clean client adapter.
Next, you'll discover how to make those features reliable and responsive: designing reusable prompt templates, parsing structured JSON output with kotlinx.serialization, streaming responses with Flow, and implementing permission-aware tool calling with validated inputs and bounded execution.
Finally, you'll learn how to ground answers in your own documents with retrieval-augmented generation, manage conversation memory within token budgets, and harden everything with prompt-injection defenses, fallback behavior, and a lightweight evaluation harness. When you're finished with this course, you'll have the skills and knowledge of AI application development in Kotlin needed to ship LLM-powered features - chat, structured extraction, streaming, tool use, and document Q&A - safely and reliably in real applications.
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