Day 54: Giving an LLM Long-Term Memory with DynamoDB

One of the biggest limitations of stateless serverless applications using LLMs (like Amazon Bedrock or OpenAI) is amnesia. Every API call starts from zero. Today, I built a persistent memory engine for my AI Financial Agent so it remembers a user's behavior from previous months. The Architecture: I created a DynamoDB table with user_id (from Cognito JWT) as the Partition Key and month_year as the Sort Key. Before calling Bedrock, my Python Lambda fetches last month's summary: def get_user_memory(user_id, prev_month_str): # DynamoDB get_item logic.