Why I Built Mneme HQ: Preventing AI Agent Architectural Drift
Theo Valmis discusses the limitations of AI coding agents, particularly their lack of memory and continuity across sessions. He identifies this issue as architectural drift, where agents forget previous decisions and constraints, leading to inefficiencies. To address this, he developed Mneme HQ, a tool that stores decisions alongside code to ensure AI assistants have the necessary context during development.
- ▪AI coding agents forget previous decisions and constraints with each new session.
- ▪This lack of memory leads to architectural drift, causing inefficiencies in coding.
- ▪Mneme HQ was created to store decisions in structured files that travel with the codebase.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3920377) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Theo Valmis Posted on May 22 • Originally published at theovalmis.com Why I Built Mneme HQ: Preventing AI Agent Architectural Drift #ai #claudecode #cursor #architecture Originally published on theovalmis.com. Every time you start a new session with an AI coding agent, it has forgotten everything. Not just the small things — the names, the syntax, the last error message. It has forgotten the decisions you made three weeks ago about why you chose Postgres over MongoDB.
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