The Session You Cannot Take With You | EARENDIL

The original promise of an inference API was wonderfully simple: send some input, receive some output. If you kept both, you had the conversation. You could inspect it, archive it, replay it, or give it to a different model. That abstraction was never completely true. For instance prompt caches live on somebody else's GPUs, tokenization differs between models, and sampling is not reproducible (and quite intentionally so). But the semantic record of a session in the form of a transcript could still belong to the user. A transcript should contain the instructions, messages, tool calls and tool results. Another sufficiently capable model might not continue identically, but it could understand what happened and take over. Inference APIs are frustratingly moving away from that property, at least somewhat. They increasingly return a mixture of text and provider-bound state that is very intentionally non-portable.

reasoning tokens that are billed to the user but returned only as opaque, encrypted blobs, with useless summaries at best web searches where the model sees source material the client never sees compacted context that only the original provider can decrypt subagent instructions and messages hidden from the application running the agents in the form of encrypted payloads file, vector-store, container, and cache references that cannot be resolved anywhere else. response and conversation state that is entirely keyed by IDs that are stored fully on the provider's servers

Each feature comes with a basic justification that's trivial for a provider to come up with, along with good arguments for why this is good for the user. Together all of these things change the ownership reality of an AI session: the transcript on your machine is no longer your session but a partial view of a session whose operational state belongs to an inference provider and not you.

A Practical Test for Session Ownership By a portable session we do not mean that switching from one model to another must produce the same next token. That's a given because models have different capabilities, trained personalities, context windows, and ways of working with tools. And well, it's all quite nondeterministic anyway. Portability means something more modest: const transcript = session.export(); revokeCredentials(oldProvider); session = newProvider.continueFrom(transcript);

The archive should contain enough intelligible information for another model to continue the work. It should not require the old provider to dereference an ID, decrypt a blob, remember a search result, or reconstruct a summary. This gives us five useful tests:

Inspection: Can the user see what the model saw, what tools did, and what agents told each other? Export: Is the session self-contained, apart from ordinary artifacts that can also be downloaded? Replay: Can another implementation reconstruct a semantically equivalent context? Audit: Can a human explain why the system took an action after the fact? Deletion: Can the user identify and remove every server-side copy on which the session depends?

A response ID is not a transcript (as the data is stored on the server), a ciphertext is not user-controlled stated (as the user cannot decrypt it), a list of citations is not the evidence that was placed in the model's context by a search result (as you cannot typically fetch the same data as the model did). Encryption for Whom? The naming and marketing around these features can be misleading. encrypted_content sounds like a privacy feature under the user's control. Usually it is a capsule that the client cannot read and only the provider can open. The provider chooses the keys, decrypts the content for its own models, and defines where the data can be replayed. A better term is provider-sealed state. Provider sealing can have a real privacy benefit. OpenAI, for example, can return encrypted reasoning to a client using store: false, then decrypt it in memory on the next request without persisting the intermediate state. That is better than requiring server-side conversation storage, particularly for Zero Data Retention customers. But, remember, there is not really anything that needs encryption to begin with! This encryption does not hide the data from the inference provider but it hides it from you. Stored Conversations Turn a Transcript into a Pointer OpenAI's Responses API stores responses by default. Its documentation says response objects are retained for at least 30 days by default.