Anton Arhipov
IntelliJ IDEA expert | Kotlin and Java development tools specialist
About
Anton Arhipov is a developer tools expert who specializes in IntelliJ IDEA and Kotlin development. He has presented at Devoxx conferences, sharing his deep knowledge of development environments and productivity techniques with software engineering audiences.
His presentations focus on practical techniques for developers, including comprehensive tips and tricks for maximizing IntelliJ IDEA's capabilities, advanced debugging strategies, and building domain-specific languages with Kotlin. Anton's teaching style emphasizes hands-on skills that developers can immediately apply to improve their daily workflows and code quality.
Through his conference talks, Anton helps development teams unlock the full potential of their tools, enabling them to write better code more efficiently and troubleshoot complex issues with greater confidence.
What Anton Talks About
IntelliJ IDEA tips and tricks for developer productivity
Advanced debugging techniques with IntelliJ IDEA
Building domain-specific languages with Kotlin DSL
Java and Kotlin development best practices
Maximizing IDE capabilities for software engineering teams
Talks7
Spec-Driven Development with AI Agents From High-Level Requirements to Working SW
Spec-Driven Development with AI Agents: From High-Level Requirements to Working Software AI coding agents are powerful, but they often feel unpredictable. Without structure, they can jump into implementation, miss requirements, or generate code you can’t easily track. Spec-driven development is a practical approach that brings order to this process. The method is simple: start with clear, high-level requirements, refine them into a detailed development plan, then break that plan into a task list with trackable steps. The AI agent works from these artifacts-requirements.md, plan.md, and tasks.md-instead of ad-hoc prompts. Each step becomes explicit, reviewable, and repeatable. In this talk, I’ll show how to apply spec-driven development and explain my intuition for this approach. We’ll walk through an example: documenting requirements, generating a plan, creating tasks, and guiding the AI through execution one step at a time. Along the way, you’ll see techniques for controlling workflow, reviewing changes, and avoiding “black box” code generation. If you’ve tried coding with AI tools but found them chaotic, this session will give you a framework to make them reliable partners.

Kotlin - the new and noteworthy

Devoxx Greece 2025 - Kotlin DSL in under an hour
More Talks
Debugging with IntelliJ IDEA
IntelliJ IDEA Tips & Tricks
IntelliJ IDEA Tips & Tricks
Debugging with IntelliJ IDEA
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