AI Agents Need Receipts
An assistant remembering a change is useful. A record showing what changed—and whether it worked—is better.
Body
‘I remember fixing that’ is a comforting sentence. It is less comforting when a service still does not work. Memory can point us toward an answer; evidence lets us check it.
For an AI agent, that difference becomes practical as soon as it edits a file, adjusts a service or interacts with a device. What did it observe? What was it allowed to change? What result did it verify?
Keep the result, not just the recollection
EMO’s operating loop ends with recording evidence. Its design calls for an account of the observation, decision, permission and checked result, rather than relying on the model to remember the conversation.
A useful record could show a configuration before and after an approved edit, together with a test result. The change and its purpose stay connected, even when the conversation is no longer fresh.
A habit that crosses disciplines
MMG works across intelligent systems, digital operations and technical production. The same question belongs in each: what shows that the intended outcome happened? A successful soundcheck and a confirmed source citation are different kinds of evidence, but both are more useful than an unchecked claim.
This is a design principle, not a promise that every prototype records everything perfectly. The goal is to build systems whose work can be inspected. An agent can keep its memory; we would also like the receipts.