Claude Code utilizes the CLAUDE.md file to store project rules, which the agent loads at the start of each session. However, relying solely on text-based instructions is insufficient for critical constraints. Research indicates that AI models often suffer from behavioral drift in long dialogues, leading to rule violations even when instructions are present in the context.
Microsoft Research findings show that top-tier models experience a 39% decline in performance during multi-turn dialogues compared to single-turn tasks. Furthermore, data from the StateTrack-Bench benchmark presented at EMNLP 2026 attributes 88.6% of failures in extended sessions to this drift, where the model retains knowledge of a constraint but fails to adhere to it.
For high-stakes operations—such as those involving financial costs, sensitive keys, or unauthorized execution—developers should implement permissions, hooks, or code-based checks. Claude Code supports 'deny' rules to block specific tools, such as browser actions that incur usage credits, and allows the use of shell-based hooks to validate task completion before an agent terminates a session.
Anthropic recommends keeping CLAUDE.md under 200 lines and treating it as a living document that records specific past failures. While text rules are suitable for stylistic guidelines or project structure, critical security and financial safeguards must be enforced through configuration files like .claude/settings.json, which can be shared across teams via version control.
