Kotlin AI Agents with Koog Build Agentic AI Apps on the JVMPublished 7/2026
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Language: English |
Duration: 2h 47m |
Size: 1.3 GB
From your first agent to a production Ktor endpoint - tools, RAG, MCP & local models, all in idiomatic Kotlin (Koog 1.0)
What you'll learnBuild production-ready AI agents in Kotlin with Koog - JetBrains' open-source JVM agent framework - from your first agent to a deployed service.
Give agents real capabilities: custom tools, tool-calling, structured typed output, and multi-step graph workflows you design and control.
Run agents for free on your own machine with local models via Ollama - no mandatory API costs to learn and experiment.
Make agents reliable and smart: add persistence, history compression, cross-session memory, and RAG that answers from your own docs.
Connect agents to the outside world with MCP servers, and switch between OpenAI and local models mid-conversation without losing history.
Deploy your agent as a real web service with Ktor, then add observability, guardrails, and basic evaluation for production confidence.
Understand what AI agents really are - the agent loop, autonomy, and how they differ from a plain LLM call - with clear mental models.
Apply your skills across platforms: Koog is Kotlin Multiplatform, so the same agent code can target JVM backends, Android, and iOS
RequirementsBasic working knowledge of Kotlin - you can read and write functions, classes, and data classes. You do NOT need to be an expert.
No AI, machine learning, or data science background required - we explain every AI concept from scratch, in plain language.
That's the core. An OpenAI API key is helpful but optional - you can complete the course for free using local models with Ollama.
DescriptionMost AI agent tutorials assume you'll learn Python. But if you build on the JVM - Android, Spring, Ktor, or any Kotlin backend - switching languages just to add AI features makes no sense. This course takes a different path: you'll build real, production-ready AI agents entirely in Kotlin, using Koog, the open-source agent framework from JetBrains.
Koog was built specifically for the JVM, with a type-safe Kotlin DSL instead of the loosely-typed Python frameworks most courses cover. That means the AI agents you build here drop straight into the applications you already work on, with the tooling, structure, and reliability the JVM world expects. And because Koog 1.0 ships with a stable core, what you learn is built to last, not to break with the next release.
You won't just watch slides. From the very first lecture, you're writing code. We start by demystifying what an AI agent actually is - how it differs from a single LLM call, how the agent loop works, and where autonomy comes from. Then you build your first working agent in just a few lines, and grow it, lecture by lecture, into something you could genuinely deploy.
Along the way you'll learn how to
- Create your own tools and let the agent call them to take real actions
- Get structured, typed output back from a model instead of fragile text parsing
- Design multi-step workflows using Koog's graph strategies, with full control over the flow
- Make agents reliable with persistence, history compression, and cross-session memory
- Build a RAG system so your agent answers questions from your own documents, not just its training data
- Connect to external tools through MCP, and switch between cloud and local models mid-conversation
- Deploy your agent as a real web service with Ktor, then add observability, guardrails, and basic evaluation
A point I care about: you can take this entire course without spending a cent on API fees. Koog integrates with Ollama, so you can run capable models locally and for free while you learn. An OpenAI key is useful for a few lectures, but it's optional, not a paywall.
Everything is built around a single project - a developer assistant called Dev Helper - that grows with you. Each section comes with the full source code at checkpoints, so you can follow along or jump straight to any stage. There are quizzes to reinforce the concepts and a final project to make the agent your own.
By the end, you won't just understand AI agents in theory. You'll have built one from scratch, given it tools and memory, connected it to the outside world, and deployed it - all in Kotlin, on the stack you already know.
If you're a Kotlin or Android developer, a JVM engineer, or someone who's tired of every AI tutorial defaulting to Python, this is the course that meets you where you already are.
Who this course is forKotlin and Android developers who want to add AI agent features to their apps and stay in the language they already love - no switching to Python.
Backend and JVM developers (Spring, Ktor, server-side Kotlin) who want to build and deploy real AI-powered services on the stack they already run.
Developers curious about AI agents who learn best by building - you want working code and real projects, not just theory or slideware.
Engineers who've tried Python AI tutorials but want a type-safe, production-minded approach with the tooling and structure the JVM world expects.
Mobile developers exploring Kotlin Multiplatform who want to bring intelligent, agentic features to Android and iOS from a single codebase.
Anyone who knows basic Kotlin and wants to go from "I've heard of AI agents" to building, deploying, and observing one themselves.
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