An immutable data store keeps existing records unchanged after they are written. Updates are represented as additional entries, allowing the system to reconstruct earlier states and see the exact sequence of events that produced the current result.
Agent runtimes can use an append-only log to preserve prompts, events, outputs, failures and causal links. This improves replay and auditing, but the system still needs retention, access controls, integrity checks and a strategy for handling sensitive data.
ELI5
An immutable data store keeps old records unchanged and adds a new record whenever something changes. It works like a notebook written in ink: you add the next event instead of erasing the earlier page.
For example, if an agent changes a decision from approved to rejected, the store keeps both the original approval and the later rejection with their times. That history makes it easier to audit what happened or rebuild an earlier state, although access controls and retention rules are still needed for sensitive information.
Why is an append-only log useful for AI agents?
It preserves execution history so developers can trace failures, replay work and audit which inputs produced an output.
Can information in an immutable store ever be corrected?
Corrections are usually appended as new records that supersede earlier data while retaining the original history.
