Giving a social media agent persistent memory with an experiential layer
Premsai04_ · reddit · 2026-09-29
The author describes adding persistent memory to SocialPulse, their AI social media engagement agent, to fix the problem that LLM-based systems respond well to the current prompt but don't remember prior interactions. They introduced Hindsight as an experiential memory layer, creating the loop:
Content request → recall past experiences → LLM reasoning → generate recommendation → performance feedback → reflection → retain learning
Responsibilities are separated:
- MongoDB: structured app data (users, posts, metrics, trends)
- Hindsight: experiences and lessons from past content performance
- LLM: reasoning over the current request plus relevant recalled experiences
After a post earns likes, comments, shares and impressions, the system computes engagement rate, asks the LLM to reflect, and stores the resulting learning statement in Hindsight; future content requests recall relevant experiences before generating strategy. The interesting part wasn't storing more information, but making previous experience available before the next decision. The author notes some demo data is simulated, so results shouldn't be treated as production-grade evidence.
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