The SOUL.md Pattern: How to give your AI agent a stable personality that doesn't drift

The SOUL.md Pattern: How to give your AI agent a stable personality that doesn't drift If you've ever deployed an AI agent that worked perfectly in testing and then gradually started behaving differently in production, you've hit personality drift. This is one of the most common and least-discussed problems in production AI agent systems. The agent that was sharp and focused on day one becomes vague and generic by day 30. The customer support bot that sounded like your brand starts sounding like a generic ChatGPT wrapper. After running five agents 24/7 for seven days on a live subscription business, here's the pattern that fixed it for us. What causes personality drift LLMs are stateless. Every session, the model starts fresh. The only thing that carries forward is what you put in the context window. Most agents load a system prompt. But system prompts tend to be task-focused: You are a customer support agent. Answer questions about billing and account access. This works for one sessio