Should AI agents remember why things happened, not just the result?
In , the final result may not be the only useful thing to keep. The harder question is when an AI agent should remember why something happened, not only what happened.
In multi-step agent work, the cause behind an event can shape the next decision. This raises the need for a that stores a instead of only saving the raw output.
Key points
- may need to track the reason behind a result, not just the result itself.
- The main question is when causality matters more than the event alone.
- A could store a instead of only raw output.
- Better causal memory may reduce tokens by keeping the useful path without carrying the full history.