Encrypted Reasoning Items for Stateless Agents

Encrypted reasoning items let a stateless agent carry opaque reasoning state forward without giving the application plaintext reasoning to inspect. This guide defines a replay envelope that preserves documented items, rejects sequence damage, and keeps durable product work outside the opaque payload.

Encrypted reasoning items are opaque transport

Reasoning models may return reasoning items that can be passed into a later request. Under stateless operation, the application can preserve encrypted content so the provider can use it on the next turn, while the application does not receive a plaintext chain of thought. The correct mental model is an opaque protocol item, not an encrypted diary for local analysis.

Preserve the item type, identifier, encrypted field, and documented ordering exactly enough for the next request contract. Do not decode, summarize, splice, or synthesize replacement bytes. If an application needs an explanation for users or operators, request and store a separate visible summary designed for that purpose.

The OpenAI Reasoning Models guide is the source of truth for current item behavior. Encrypted reasoning items should be wrapped by application metadata such as turn ID, policy version, received time, and digest, but that metadata must never be represented as provider reasoning.

The bundled sequence is synthetic and uses obvious placeholder ciphertext. It tests envelope order and field custody only; it does not exercise cryptography, decrypt provider data, or make a Zero Data Retention compliance claim.

Choose stateless operation deliberately

A stateless Responses API pattern sends the relevant prior items with the next request rather than relying on stored provider conversation state. Teams may choose it for explicit request construction, data-policy requirements, regional architecture, or replay control. The choice creates application responsibilities for integrity, retention, size limits, and failure recovery.

The OpenAI Conversation State guide describes the available state mechanisms and storage choices. Record which mechanism a work item uses so code does not accidentally combine previous response pointers, conversations, and full item replay in an ambiguous way.

The phrase store false describes a request behavior, not a complete data-governance program. Define what your own application stores, why it is needed, where it is encrypted, who can access it, and when it expires. Zero Data Retention eligibility or behavior must be evaluated against current provider terms and account configuration rather than inferred from one field.

Encrypted reasoning items are useful only inside that explicit policy. If the product cannot retain opaque response data, the workflow must either complete within one turn, use another approved state mechanism, or accept that the reasoning continuity cannot be replayed.

Build an application-owned replay envelope

Store a sequence record with schema version, work ID, turn number, response item type, provider item identifier when present, opaque content bytes, byte length, digest, received time, and expiry. Keep tool calls, tool outputs, and visible messages as typed items in the same ordered stream, but validate their inspectable fields separately.

The envelope should distinguish exact provider payload from application metadata. Serialize the former without lossy transformations, and hash the serialized form you intend to replay. If transport encoding changes, version the canonicalization rule so an old digest can still be verified.

Do not use an opaque reasoning identifier as the product's resume cursor. The durable execution guide recommends an application work ID and effect receipts that survive provider retries, model changes, and expired context. A replay bundle can help inference continue while the product ledger decides whether real work may resume.

Reasoning item replay also needs bounds. Limit turns, total opaque bytes, age, and allowed models or configurations; reject a bundle that exceeds policy instead of trimming an unknown item in the middle.

Preserve item order and tool-call pairing

A multi-turn response stream can include reasoning items, function calls, function-call outputs, and messages. Preserve their documented order because later items may depend on context established earlier. Never sort by identifier or group all opaque items together for storage convenience unless the API explicitly defines such a transformation as equivalent.

Validate that each tool output references an expected call and that application execution produced the recorded result. The opaque reasoning item does not prove a call was authorized or completed. Store a safe tool receipt with validator version, work ID, effect status, and result digest outside the provider stream.

The synthetic fixture contains reasoning, call, output, and reasoning in that sequence. It removes visible summary fields from the pass-through copy and asserts that the call identifier remains paired. This bounded case demonstrates the distinction between what is preserved and what is product-owned.

Encrypted reasoning items should fail closed when a required call output is missing. Re-sending a partial sequence and hoping the model reconstructs the effect can cause duplicate work or unsupported answers.

Runnable artifact — The runnable envelope preserves a frozen opaque-item sequence, removes visible summaries from pass-through data, and verifies tool-call pairing.

import assert from "node:assert/strict";
const turns=[
 {id:"r1",type:"reasoning",encrypted_content:"enc:v1:alpha",summary:["inspect request"]},
 {id:"c1",type:"function_call",call_id:"call_7",name:"lookup",arguments:"{\"id\":\"A17\"}"},
 {id:"o1",type:"function_call_output",call_id:"call_7",output:"{\"status\":\"ready\"}"},
 {id:"r2",type:"reasoning",encrypted_content:"enc:v1:omega",summary:["use verified status"]},
];
const store=turns.map(({summary,...item})=>structuredClone(item));
assert.deepEqual(store.map(item=>item.type),["reasoning","function_call","function_call_output","reasoning"]);
assert.equal(store[0].encrypted_content,"enc:v1:alpha");
assert.equal(store[1].call_id,store[2].call_id);
assert.equal(store.some(item=>"summary" in item),false);
console.log(JSON.stringify({workId:"work-A17",passThroughItems:store,applicationOwns:["workId","toolReceipt","retentionPolicy"]},null,2));
console.log("PASS: encrypted reasoning items survive a stateless round trip");

Reject drop, reorder, tamper, and expiry failures

Verify envelope schema, sequence numbers, item allowlist, byte lengths, digests, and expiry before every replay. Check tool-call pairing and terminal state. A missing opaque item may make the next request invalid or change behavior; a missing tool result may hide whether an effect occurred. Neither case should be repaired by manufacturing a substitute.

Reordering can happen through database queries that omit an explicit sequence or through concurrent writes. Use a unique work-and-sequence constraint and commit a complete accepted turn atomically. If concurrent branches are supported, name branch ancestry rather than flattening them into one list.

Tamper detection proves that stored bytes match the recorded digest, not that the opaque content is safe or semantically correct. Encrypted reasoning items still come from an inference boundary and remain subject to the documented request contract. Expiry should lead to a recoverable product state such as restart context, request clarification, or escalate.

Extend the local fixture with mutations for dropped r1, swapped call/output, changed ciphertext, duplicated output, and expired timestamp. Each case should produce a named rejection receipt that an operator can understand without seeing plaintext reasoning.

Keep visibility and observability separate

Operators need to know that a reasoning item was received, stored, replayed, rejected, or expired. They do not need a fabricated explanation of its contents. Log item type, opaque byte count, digest prefix, turn, retention class, and validation result, while keeping payload data out of ordinary telemetry.

For product explanations, rely on visible model output, tool evidence, and application decisions. The AI agent activity-log guide can expose what tools ran, which approvals occurred, and what data sources supported an answer without turning hidden reasoning into an audit artifact.

Measure replay success, envelope rejection by reason, age and size distributions, missing call pairs, expired workflows, and restart outcomes. Segment changes by model and API configuration because opaque item compatibility may depend on the documented request context.

Encrypted reasoning items should never be indexed for semantic search, shown in a debugging panel, or concatenated into prompts as text. They are protocol material whose value comes from exact preservation and bounded forwarding.

Compact product memory without editing opaque state

Product memory and provider reasoning continuity solve different problems. A product may retain accepted user facts, decisions, citations, and effect receipts in a compact durable record. Opaque items may be retained temporarily for a compatible next turn under a separate policy. Do not treat one as a replacement for the other.

The agent context compaction guide recommends source ranges and versioned summary policies for inspectable history. That method cannot summarize encrypted reasoning items because their meaning is unavailable. It can summarize visible conversation and product events while preserving or expiring the opaque sequence independently.

When the opaque budget is exhausted, create an explicit transition. Start a fresh inference context from approved visible facts, ask the user to restate critical intent, or end the workflow safely. Record that reasoning continuity was reset so later analysis does not compare the turn with an uninterrupted trace.

Reasoning item replay should therefore be a short-lived bridge, while durable memory remains a reviewed projection. The two timelines can share a work ID without sharing retention or visibility assumptions.

Release a stateless agent with integrity drills

Test a normal multi-turn tool interaction, changed instructions, tool error, network retry, duplicate delivery, missing output, omitted reasoning item, reordered sequence, tampered bytes, expiry, and unsupported configuration. Verify both the provider-facing request construction and the application-facing recovery outcome.

The Responses API comparison helps place this technique among other state models. Keep the replay adapter behind a domain-turn interface so a future storage or API change does not rewrite business-effect coordination.

Review retention and access controls with the team that owns privacy and security. Avoid labels that imply decrypted inspection or guaranteed compliance. A Zero Data Retention requirement is an account and workflow constraint that deserves current official confirmation, not a checkbox inferred from encrypted content.

Run the bundled envelope validator, then add the five mutation cases described above. Ship only when every failure produces a bounded restart or escalation and no handler attempts to reconstruct the missing hidden state.