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From Leaderboards to Behavioral Profiles: How JetBrains Evaluated Models for Agentic Coding

From Leaderboards to Behavioral Profiles: How JetBrains Evaluated Models for Agentic Coding

JetBrains proposes evaluating coding agents beyond task-resolution rates by analyzing efficiency, patch quality, and execution paths. A comparison of Claude Opus 4.7 and Gemini 3.5 Flash shows that similar final results can conceal major differences in cost, verification, modification scope, and approaches to handling software repositories.

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JetBrains Enables Fully Local Junie on Mac Devices Without the Cloud or Credits

JetBrains Enables Fully Local Junie on Mac Devices Without the Cloud or Credits

JetBrains has launched Junie Local, which runs the Junie coding agent locally on a Mac using the Qwen3.6-27B model, without sending code or prompts to the cloud. It requires a Mac with an M5 processor and 64 GB of memory, along with a download of approximately 20 GB.

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How JetBrains Improved Local Qwen3.6 Execution Inside the Junie Agent

How JetBrains Improved Local Qwen3.6 Execution Inside the Junie Agent

JetBrains explains the changes it made to Junie and the inference engine to run Qwen3.6-27B locally on M5-powered MacBook devices. The experiment shows that the performance of local coding agents depends on context management and the prefill stage as much as it does on token-generation speed.

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AI Coding Agents Establish a Firm Presence in Developer Tools

AI Coding Agents Establish a Firm Presence in Developer Tools

The results of the JetBrains Developer Ecosystem Survey 2026 reveal that 90% of professional developers use AI coding agents at work at least once a week, while 68% use them daily. Claude Code leads the field, while Codex is experiencing rapid growth and adoption of GitHub Copilot and Cursor declined between May and July 2026.

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WebStorm Enables Switching Between AI Agents via the ACP Protocol

WebStorm Enables Switching Between AI Agents via the ACP Protocol

JetBrains has added support for the Agent Client Protocol to WebStorm, enabling developers to use multiple AI agents from within the same development environment, including agents associated with their existing subscriptions. The protocol also enables connecting custom agents and controlling the infrastructure and where data is processed.