Why the Top 1% of Devs Love IntelliJ
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In this episode
From early IntelliJ user to JetBrains advocate, Anton Arhipov continues his conversation with Simon Maple and Baptiste Fernandez on AI Native Dev, tracing his journey through tools, trends, and the changing face of developer experience.
On the docket:
• how IntelliJ responds to new tools in the market
• understanding the pros and cons of tab-driven development for devs
• why tools will need to get better in PR workflows
• ZeroTurnaround’s Java reloading that ended JVM restarts
• the four must-know IntelliJ plugins for every developer
Anton’s Journey from ZeroTurnaround to JetBrains
Anton Arhipov recounted his career evolution, highlighting his transition from ZeroTurnaround—famous for its JRebel tool, enabling Java class reloading without JVM restarts—to JetBrains. Initially joining JetBrains on the TeamCity project, he later specialized in Kotlin advocacy, speaking extensively about the language and its ecosystem.
AI’s Impact on IntelliJ and Developer Experience
Anton discussed the significant shift brought by AI tools like Copilot and Cursor, noting their transformative impact on developer workflows. These tools introduced capabilities like chat-based code generation and multi-file integration directly into editors, fundamentally changing user expectations around developer assistance and productivity.
Essential IntelliJ AI Plugins
Anton shared that IntelliJ currently hosts four critical AI-driven plugins: the AI Assistant, Junie (an agentic tool), Full Line Completion (FLCC), and Grazie (a spell checker foundational to IntelliJ’s AI functionalities). He elaborated on their distinct functionalities, ranging from inline completions and snippet generation to comprehensive project-wide code interactions.
Tab-driven Development and AI’s UX Challenge
The conversation delved into tab-driven development, a UX paradigm popularized by AI tools where developers accept suggested edits with minimal effort. Anton highlighted this approach’s productivity benefits but also mentioned the cognitive overload caused by constant suggestions. He stressed the balance needed in AI assistance to enhance rather than overwhelm developer workflows.
Future of PR Workflows and Debugging with AI
Anton envisioned a future where AI-driven development significantly affects pull request (PR) workflows and debugging practices. He underscored the necessity for improved PR visualization tools to manage AI-generated code and emphasized the increasing importance of robust testing frameworks, given the challenge of verifying AI-generated tests and code quality effectively.
