How to Give Your AI Agent Persistent Memory Across Runs

Most AI agents have a memory problem. You build a LangChain agent, a CrewAI crew, or a custom AutoGen workflow. It runs perfectly. Then the process ends and it forgets everything — user preferences, past decisions, what it already tried. Every run starts from zero. The problem with context window stuffing The common workaround is jamming previous context into the prompt. This causes three problems: You pay for the same tokens every single run As the prompt grows, the model's attention dilutes Eventually you hit the token ceiling and lose the oldest (often most important) context What agents actually need is an external memory layer that persists between runs. A simple solution: two REST calls Here is the pattern that works: Store a memory after something important happens: curl -X POST https://memstore.dev/v1/memory/remember \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{"content": "User prefers concise responses and works in Python"}' Recall rel