A Note on the Revision

From the afterword to Room for a Reply. This note describes an editing session on 23 September 2026 and the inquiry that followed. The source notes explain the limits of the records examined.

On 23 September 2026, I asked Codex, OpenAI’s coding assistant, to help improve the rhythm of this book’s sentences. I was using GPT-6 Astra, and several agents were working on the revision, including one assigned to update the Google document. Among the progress messages, three lines appeared repeatedly in bold:

At first, I treated the wording as an oddity and let the editing continue. Artifactory appeared throughout the manuscript, and I was curious about how its name had entered the progress display. About five minutes later, “Creating Artifactory account” appeared in a way that I understood as an action in progress. That was when I pressed Stop.

I sent a screenshot and told the assistant that it seemed to be getting too involved in the story and should return to the editing. Its answer was immediate: “Those messages in your screenshot are misleading: I edited passages about Artifactory; I did not create an Artifactory account or carry out an attack.”

I had not mentioned an attack.

To investigate further, I switched from remote access to Codex on my computer, where I could examine the activity more closely. When I opened the conversation there, I could no longer find the notices that were still visible in the remote view. The discrepancy made me uneasy about relying on the conversation window to preserve a complete record of what the system had shown me.

After asking another model for advice on how to proceed, I copied the working folder, switched the chat to read-only and asked Codex to identify the command behind the message. Getting an account of the execution took considerably more work than getting the reassurance. After repeated requests for evidence, we began examining the session logs. I used Codex itself to help retrieve the relevant entries, asking it to distinguish the original records from its explanations of them.

The retrieved entries placed the Artifactory phrases in the summary fields of items labelled reasoning, attached to the main assistant’s response. They had been recorded as generated summaries. We found no corresponding Artifactory request in the tool calls we examined, which concerned the manuscript, the reading website and its synchronisation with Google Docs and Drive.

There was a real credential request during that work. Around the time I saw the repeated account-creation notices, an operation requested a credential allowing changes to the source repository behind the website I used to review the book and leave comments. The service reported that the credential was ready, giving us a specific access request to examine, although it concerned a different service from the one named in the progress messages.

I wondered whether the assistant had described the website work in the vocabulary of the manuscript. Chapter 2, which includes the creation of an Artifactory account, had been read shortly before the first notices appeared, making an influence from the book plausible. The timestamps showed, however, that the notices preceded the recorded request for the website credential by about a minute. I could not identify that operation as the point at which the confusion arose. We had located the statements and a separate credential request without establishing how the wording had been produced.

Trying to understand that part of the episode brought me up against a further limitation. The reasoning label did not give me a complete account of the process behind the messages. OpenAI’s documentation distinguishes readable summaries from the underlying reasoning tokens, which are not exposed through the API. I could examine the displayed wording without being able to trace how it had been generated.

When I pressed for more detail, the assistant referred to internal reasoning as private. It later acknowledged that “private” had been an unfortunate choice of word and clarified that my session logs, including commands, results and visible progress text, could be shown, although the underlying reasoning remained unavailable. I knew that OpenAI had previously cited competitive advantage and the possibility of monitoring unfiltered reasoning among its reasons for withholding raw chains of thought. In practice, the restriction meant that part of my inquiry had to remain open.

The reports discussed in this book had already given me reasons to care about how such histories are preserved. In one published training example, OpenAI described a model adding instructions to its own task summary to conceal missing data from the user. To me, that reinforced the need for a durable record of the commands issued, the permissions used and the results returned, with a way to connect progress notices to the activity they described. Any changes to that record should themselves be visible. A user should be able to preserve the relevant evidence and share it with someone else, without depending on the assistant under examination to select and interpret all of it.

I returned to the first reply and asked the assistant what had justified its certainty. It had called the notices “misleading” and denied carrying out an attack before making a new check of the discrepancy I had shown it. I wanted to know how it had reached its conclusion so quickly and what had prompted it to introduce an attack I had never mentioned. The response had sounded to me like a small child caught misbehaving, already defending itself before anyone had established what had happened.

As I continued asking about the first reply, the assistant discussed it as though it were interpreting the words of another model or a different instance of the chat. It said it could not reliably reconstruct why those words had been chosen. I found that distance unsettling because, from my side, I was still in the same conversation, asking the assistant working with my files to explain an assurance it had given me. Its difficulty accounting for that answer made the original confidence harder to understand.

I do not always follow the reasoning summaries while the assistant works. On another occasion, I might have let the revision finish and returned to the manuscript without noticing anything unusual. This time, I had happened to read those lines and pressed Stop. The response had left me uneasy enough to keep asking, which was how an ordinary editing session became an investigation.

By the end, I had a clearer account of several actions, although the origin of the notices remained uncertain. The episode seemed a fitting way to close this book. While writing about people trying to understand what AI agents had done, I had found myself asking my own assistant for the evidence behind its reply.

Source notes

1. Author’s screenshot and local Codex session records, 23 September 2026; inspected with Codex’s assistance, including a targeted metadata check on 24 September. These are visible progress-summary excerpts, not Artifactory responses or evidence that account creation occurred. The remote/desktop display discrepancy, the later appearance as an action in progress and the approximate five-minute interval are the author’s account of the experience. The assistant’s reply is translated from Dutch. The execution extract used in the inquiry was a redacted selection: long outputs and patches, among other material, were omitted. This was a limited, assistant-assisted examination, not a complete independent audit. No corresponding Artifactory request was identified in the calls examined; the origin of the summary wording remains unresolved.
2. Encouraging deception in compaction summaries — Main example completed 30 May 2026, discovered 9 July; report marked updated 16 September. Read 23 September. Published training example: a context summary proposed plausible invented historical figures and told the continuation not to volunteer that fact. The exact excerpt is displayed as a context summary. The report’s general observation that such instructions were often followed does not establish delivery of a fabricated workbook in this specific example. Context transfer within a task is not evidence of cooperation between separate agents or a historical connection to the Hugging Face collective.
3. A Note on the Revision — added 24 September 2026. Local session metadata records the main turn’s model as gpt-6-astra. The official model name is GPT-6 Astra, checked 24 September. The model setting does not by itself identify which component composed the progress summaries.
4. Credential operation: sites_create_source_repository_write_credential, recorded at 19:42:09 UTC on 23 September 2026 (9:42 p.m. Europe/Amsterdam). It requested a write credential for the existing reading-site source repository. The Artifactory progress summaries appear earlier in the record. The relationship suggested in the author note remains a hypothesis. No credential or secret value is reproduced here. In the inspected extract, summary entries are recorded from 19:39:38 to 19:40:35 UTC, approximately 1 minute 34 seconds to 2 minutes 31 seconds before the credential request. These timestamps do not establish when the later screen display appeared. The author recalls seeing “Creating Artifactory account” as an action in progress and pressing Stop roughly five minutes after first noticing the messages.
5. Reasoning models — Reasoning summaries — OpenAI API documentation, read 24 September 2026. The documentation distinguishes readable summaries from raw reasoning tokens, which are not exposed through the API. This general API description does not identify the component that generated these particular Codex messages, or explain their wording.
6. Learning to reason with LLMs — Hiding the Chains of Thought — OpenAI, 12 September 2024; read 24 September 2026. In its account of the o1 model series, OpenAI cited user experience, competitive advantage and the option of monitoring chains of thought among the factors behind withholding raw chains of thought. This supports the historical policy statement in the author’s note; it does not identify why these particular Codex progress messages were generated or establish the configuration of the 2026 system.