From "Who Wrote This?" to "Provenance, Actioned": Making AI-origin code obvious during review
The article discusses the importance of making AI-origin code more transparent during code reviews. It introduces the concept of 'actionable provenance' which provides context about code changes, helping reviewers understand the origin and reasoning behind edits. By implementing features like drag-and-drop and confidence scoring, the process of reviewing AI-generated code can be made more efficient and effective.
- ▪Actionable provenance provides immediate answers to reviewers about code origins and context.
- ▪Recent UX improvements allow for easier integration of provenance information during code reviews.
- ▪By 2026, AI is expected to be a primary tool in development, necessitating better review processes for AI-generated code.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3940098) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Praveen Posted on May 29 From "Who Wrote This?" to "Provenance, Actioned": Making AI-origin code obvious during review #devops #security #discuss #news TL;DR: The most useful provenance is actionable provenance. Instead of storing prompts like a dusty audit log, surface them where decision-makers work: the code review.
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