Users report that during extended conversations, the AI loses track of specific topics, examples, and…

Question

Users report that during extended conversations, the AI loses track of specific topics, examples, and preferences they mentioned earlier in the session. Your current implementation uses a sliding window that keeps only the most recent 25 message pairs to stay within context limits. What's the most effective approach to maintain awareness of earlier conversation content while managing context size?

Accepted Answer

A. Replace the sliding window with a hybrid approach: summarize older messages while keeping recent messages verbatim.

Answer

B. Implement vector similarity search over the full conversation history, retrieving relevant past messages for each user query.

Answer

C. Increase the window size to 50 message pairs to retain more conversation history before truncation.

Answer

D. Add a separate API call each turn to summarize messages being dropped, prepending this running summary to the conversation.

Question 225