JetBrains proposes a three-level framework for reviewing AI-generated code from overview to file risk to high-risk snippets

What changed

JetBrains Research and Lund University researchers published a framework on October 6 for reviewing AI-generated code. Based on participatory design with 17 practitioners and a follow-up survey of 43 software professionals, the work frames the central problem as trust calibration and proposes a three-level workflow: start with an overview, stratify risk at the file level, then drill into code snippets that deserve the most attention. It is a conceptual research framework, not a newly shipped automated review feature in JetBrains IDEs.