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Claude: System Prompts (platform.claude.com)

761 points by tosh · 10 days ago · 284 comments on HN

Article summary

The article discusses the system prompts used by Claude, a conversational AI model, to provide up-to-date information and guide its behavior. The system prompts are periodically updated and can be lengthy, with some versions exceeding 3000 words. These prompts are used in Claude's web interface and mobile apps, but not in the Claude API. The updates to the system prompts aim to improve Claude's responses and performance.

Main themes

  • System Prompts
  • Conversational AI
  • Model Performance
  • AI Training
  • Context Window
  • Model Flexibility

What commenters say

  • The length and content of system prompts can negatively affect model performance, potentially taking away from the context window and causing the model to make mistakes.
  • Baking system prompts into the model itself would make it inflexible and difficult to update, whereas having them in context allows for easy changes and caching.
  • The use of system prompts is a form of defense in depth, but it is not a strong enough safeguard against producing harmful content, and other methods such as fine-tuning and out-of-band detection are necessary.
  • The cost of system prompts is not a significant concern, as they are prefix cached and do not affect the API, and the cost to customers is minimal.
  • The system prompt is not the only factor in determining model behavior, and other factors such as internal training and external safeguards play a more significant role.
  • The industry may be relying too heavily on solutions like system prompts and soul documents, and may eventually move towards more mature methods like LoRA and control vectors.
  • Fine-tuning a model to incorporate system prompts is not a viable solution, as it would require retraining the model every time the prompt is updated, and may not have the same effect as selecting input tokens.
  • The use of system prompts is a necessary evil, as it allows for guiding the model's behavior and providing up-to-date information, but it can also lead to performance degradation and increased cost.