Why AI agents forget everything (and how we fixed it)

If you've built an AI agent or assistant, you've hit this wall: the moment the session ends, it forgets everything. The user comes back the next day. The agent has no idea who they are. No memory of their preferences, their history, what they were working on. The user has to re-explain themselves from scratch. Every. Single. Time. This isn't a model problem — it's an infrastructure problem. Models don't have long-term memory. They have context windows. When the window closes, everything in it disappears. What we built AmPN is a hosted memory store for AI agents. Your agent stores memories via our API. When a new session starts, it retrieves the relevant context with semantic search — so it picks up exactly where it left off. from ampn import MemoryClient client = MemoryClient ( api_key = ' your_key ' ) # Store a memory client . store ( user_id = ' alice ' , content = ' User prefers concise explanations and works in Python ' ) # Retrieve relevant context results = client . search ( user