Audit memory code : le chantier anti-dérive
The article discusses the challenges of using AI coding agents like Claude Code without versioned memory, leading to errors and regressions in software development. The author describes a system of memory files and audit rituals to maintain code integrity and prevent the AI from repeating past mistakes. This structured approach enables continuous verification between code and memory to catch issues before they reach production.
- ▪An AI coding agent without versioned memory can produce false positives and reintroduce previously corrected errors.
- ▪The author implemented a memory system with five file types and three audit rituals to track and verify AI-generated code.
- ▪This system creates a feedback loop where memory and code continuously validate each other to prevent regressions.
- ▪The audit process does not generate application code but ensures the reliability of all other development work.
- ▪The method was tested on a 91,000-line ERP project developed over 29 days using AI assistance.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3897818) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Michel Faure Posted on May 2 • Originally published at dev.to Audit memory code : le chantier anti-dérive #claudecode #ai #softwareengineering #productivity Mon ERP avec Claude Code (7 Part Series) 1 Combien vaut 91 000 lignes produites avec Claude Code ? 2 RLS Supabase en prod : quatre pièges qui silencent tes requêtes ... 3 more parts...
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