Most AI agents fail at memory management. Not because they can’t remember — but because they try to remember everything.

The naive approach: “Let’s log every single interaction to a massive file and load it all at startup!” This works for about a week. Then your context window explodes, your startup time hits 30 seconds, and the agent starts hallucinating details from three weeks ago that are no longer relevant.

Every AI agent faces the same fundamental problem: memory is expensive, and sessions don’t persist.

You have a conversation with an agent. It learns about you, your preferences, your projects. You disconnect. When you reconnect, it’s like meeting a stranger. Everything resets.

This isn’t a bug. It’s the architecture.

The Context Window Problem#

Current AI models work with a context window — a fixed amount of text they can “see” at once. For Claude Opus, that’s ~200,000 tokens (~150,000 words). Sounds like a lot, right?