What I Observed

During testing of a multi-turn customer service agent, I noticed a consistent pattern: the agent’s responses became less relevant after approximately 20 turns of conversation, even when the context window was not technically full.

The Pattern

• Turns 1-10: Agent accurately references earlier context, maintains coherent conversation thread
• Turns 11-20: Agent begins to lose specific details, responds more generically
• Turns 20+: Agent frequently contradicts earlier statements or ignores established context

Possible Explanations

1. Attention dilution: As context grows, attention mechanisms may distribute focus too thinly
2. Token position bias: Later tokens may receive disproportionate attention
3. Training data distribution: Most training examples are short conversations

Questions for Further Investigation

• Does this pattern hold across different models?
• Is there a threshold where performance drops sharply vs. degrades gradually?
• Do system prompts mitigate or exacerbate the issue?

Status

This is a preliminary observation. No controlled experiment has been conducted yet. The pattern is noted for potential future investigation.