Short system prompts improve Claude's adherence and reduce token waste

A user on r/ClaudeAI shared that after eight months of struggling with a massive 3,847-word system prompt covering requirements, coding standards, project context, personality preferences, and error handling, they discovered the root cause: the prompt was too long.

Claude would start strong but gradually forget half the instructions or ignore parts that didn't fit. The user asked Claude itself why it kept forgetting instructions, and the model indicated the prompts were too long.

The fix was to replace the single giant prompt with multiple tiny focused prompts, totaling about 200 words:

• "Write tests first. Use Jest. Cover edge cases."
• "Explain your code changes in bullet points."
• "Ask before installing new dependencies."

After three weeks of testing, the user reports that Claude consistently follows these short prompts, conversations no longer drift into random tangents, and token usage dropped because there's less fluff to process. Notably, they haven't had a single conversation where Claude started refactoring the codebase unprompted.

The takeaway: short prompts force specificity about what you actually want rather than trying to anticipate every scenario, and Claude works better when given room to think instead of a novel's worth of constraints.