Developer Explores What AI Agents Should Actually Remember in Long-Term Memory Design
Bh0nu0077 · reddit · 2026-09-30
A developer shared experiments on adding long-term memory to an AI agent, centered on the question of what an agent should actually remember. Example: after a user asks for fitness creators in Hyderabad for a protein powder campaign, a follow-up "find me more creators" shouldn't require the full brief again—the agent should recall previous accept/reject decisions and let them shape new recommendations.
The workflow: user request → campaign understanding → memory retrieval → creator matching → recommendation → user decision → memory update, built with Hindsight as the memory layer and n8n for orchestration.
Five open questions: what to store as long-term memory, whether accept/reject decisions count as memories, how to retrieve relevant memories, how to stop old campaign context leaking into new ones, and how to evaluate whether memory actually improves the agent. A working prototype exists; the author wants feedback on memory architecture.
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