Six Things Your Financial Model Needs to Survive an AI Session Restart

AI assistants lose critical context between sessions, forcing users to re-explain financial models from scratch each time — a problem that conversation-based memory features do not adequately solve. The core issue is that a financial model has a precise structure, including dependencies, conventions, and item types, that cannot survive the lossy compression of chat summaries. To avoid this, key model context must exist outside the conversation in persistent, readable form before a new session begins. Essential elements include the model's purpose and intended audience, unit and sign conventions, working language, and a clear map of which lines are inputs versus computed outputs. A dedicated versioned file read at session start — rather than relying on AI memory — is proposed as the practical solution to ensure consistent, accurate agent behavior across sessions.