Why Your Long AI Prompts Fail (And How to Fix It)

Have you ever given a long document to an AI, only for it to completely ignore the instructions you put in the middle? You're not alone. This is a well-documented phenomenon known as the "Lost in the Middle" effect.

The "Lost in the Middle" Problem

Research has shown that LLMs (Large Language Models) are much better at recalling information at the very beginning or the very end of a prompt. Information buried in the middle often gets less attention, leading to hallucinations or ignored constraints.

How Splitting Fixes Accuracy

When you split a long text into smaller parts, you are effectively providing multiple "beginnings" and "ends." This forces the AI to pay closer attention to every section of your data. By processing information sequentially, the AI maintains a higher level of focus on the specific content of each part.

Best Practices for High Accuracy

• Small Chunks: Keep your parts under 10,000 characters for maximum precision.
• Repeat Instructions: If you have critical constraints, include them briefly in each part.
• Verify as You Go: Ask the AI to summarize each part before moving to the next.