Agent Memory Systems

Agent memory is what lets an AI remember past conversations and learn from them. Without it, every chat starts fresh with no history. This skill teaches how to build memory for AI agents using three main types: short-term memory, long-term memory, and special thinking structures that organize everything.

The most important idea is that finding the right memory matters more than storing lots of facts. You need good ways to break information into pieces, turn it into numbers, and pull it back when needed. If you cannot find the memory, it is useless.

We use a clear framework called CoALA to keep things simple. It splits memory into facts, personal experiences, and how-to knowledge. This helps your agent remember who you are, what you did before, and how to solve problems better over time.