Why IntelliJ IDEA 2026.1’s AI‑Powered Spring Runtime Debug Is a Game‑Changer

AI Fully Integrated

IntelliJ IDEA 2026.1 adopts an open AI ecosystem, natively supporting Codex, Cursor, and any AI agent compatible with the ACP protocol. Users can also plug in custom models via API keys, allowing any preferred model—local, cloud‑provider, or internal—to become part of the development workflow.

Java 26 Support

IDEA 2026.1 adds early support for Java 26, including preview features such as pattern matching (fourth preview) and lazy constant loading (second preview). This lets developers experiment with new language capabilities immediately, reducing the lag between JDK release and IDE readiness.

Spring Runtime Debug

The standout feature is Spring Debugger, which shows the live state of a Spring application without pausing the JVM. Previously developers relied on breakpoints, manual inspection, and configuration guessing; now they can view bean injection, active configuration, environment details, and protected endpoint status directly while the program runs.

At present only beans injected into Spring components are visible, but the feature is slated for further expansion.

Dependency Source Visibility

All library source code is now downloaded automatically in a non‑intrusive way, giving developers immediate access to full context when browsing code, tracing calls, or troubleshooting issues.

Command Completion Enhancements

Command completion now embeds AI capabilities, allowing code explanation, documentation generation, and code modification directly from the suggestion popup.

All suffix templates can be invoked with ...

Command completion also supports .properties configuration files.

Gradle Official Best Practices

JetBrains, together with Google, published over 30 best‑practice recommendations for Gradle, helping developers avoid the pitfalls of overly flexible build scripts and providing a reliable reference for AI‑generated configurations.

Editor Interaction Improvements

Smoother cursor animations.

More natural text selection.

Cleaner UI appearance.

Git Worktree Support

Enhanced Git worktree integration lets developers keep the main branch on main, spin off an isolated worktree for urgent fixes, and launch another worktree for AI agents to run tasks—all without interference.

AI Direct Database Operations

Codex and Claude agents can now interact with connected databases directly from the IDE, enabling natural‑language queries, data inspection, schema viewing, relationship analysis, and even data modification.

"Codex and Claude Agent in the IDE can directly support the databases you are connected to."

Kubernetes Integration

A new welcome page streamlines cluster operations: connecting to clusters, switching contexts, applying configurations, viewing resource trees, inspecting logs, and debugging—all from within the IDE, reducing context‑switching for Java‑backed cloud‑native applications.

Choosing Claude, Codex, or Gemini

Claude excels at long‑context code understanding, refactoring, and complex bug analysis. Codex shines for command‑line workflows, scripting, and rapid verification. Gemini is best for processing ultra‑long documents, multimodal inputs, and aggregating diverse sources.

Effective Multi‑Model Workflow

Rather than committing to a single AI, developers can assign tasks: use Gemini for document ingestion, Claude for deep code work, and Codex for automation. IDEA’s open AI ecosystem is designed to support this collaborative, multi‑model development flow.

Domestic Integration Tips

Chinese developers often struggle with managing multiple API keys, quotas, and configurations. The Code80 project offers a unified entry point: a single API key that routes to Claude, GPT, Gemini, etc., and provides ready‑made installation scripts for Claude Code, Codex CLI, and Gemini CLI.

FAQ

What’s the most valuable update?

Spring Runtime Debug, because it eliminates the need for breakpoints and lets developers see live application state instantly.

What’s the core direction?

The IDE is evolving from a simple code editor into a full development platform, consolidating AI, database, dependency, Git, and Kubernetes capabilities into a continuous workflow.

What does AI integration really mean?

IDEA now allows any AI model to become part of the professional workflow, moving beyond a fixed set of vendor‑provided assistants.

How to pick an AI model?

Claude – complex code understanding and long‑term collaboration.

Codex – command‑line tasks, scripting, and rapid execution.

Gemini – long documents, multimodal data, and multi‑source synthesis.

Conclusion

IntelliJ IDEA 2026.1 is not just adding AI features; it is weaving AI into the core development loop, unifying code editing, debugging, dependency inspection, database interaction, build automation, and cluster management. The Spring runtime debug exemplifies how these changes directly improve daily developer productivity.