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The core claim: columns are necessary, not sufficient
Chiu calls the part of a record that lets you answer, later, who decided something and under what conditions it was allowed “decision provenance.” His central line: “The columns are necessary and they are not sufficient, and none of the three ways they fail is fixed by adding more columns.”
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The three failure modes, as his examples show them:
- Omitted values: something that shaped the run was never written down.
- Values mutable outside your code: the setting lived somewhere that can change after the fact.
- Values no longer available: the evidence existed once and has since been deleted or overwritten.
The example: three runs, identical headers, different outcomes
Chiu says he ran the same probe three times against the same model and binary. One run passed 67 percent of cases. The other two passed 8.3 percent each. The header fields he had listed were identical across all three. These are his own probe results, not a published or independently reproduced measurement.
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He traces the gap to things the record did not capture or could not pin down:
| What the record held | Why it could not explain the difference |
|---|---|
| Sampling parameters (not sent by his code) | They came from a model configuration file that could change when the model was re-pulled. |
| Model field | It stored a tag, not a digest, so it did not identify the exact weights. |
| Context length and server version | The effective values were not recorded. |
| Scratch directory of the outlier run | Already deleted, so the artifacts could not be inspected. |
He also reports four follow-up runs under different machine conditions, including a cold start. Ten header fields showed zero drift. A server-side environment variable pinned the context length, and three models with declared context lengths of 40960 and 262144 still produced the same effective number. Again, these are his observations rather than product specifications.
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Rules the essay draws from this
Absence is not a default
If a provenance field cannot be read, record null or a visible “not recorded” state. Do not backfill with what you can observe today. In Chiu’s words: “An old report with no digest does not mean it ran the weights I have now, and filling that cell with today’s digest would turn a gap into a false statement.”
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Record what the system did, not what it was asked to do
“The second rule is that the record has to hold what the system actually did, not what it was asked to do.” His example is context length: store the value the runtime actually granted, and note any mismatch with the value the caller requested. The mismatch is itself a finding.
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Make uncontrolled settings visible
Where his code did not set sampling values, his report marks them as inherited from the backend, and therefore not controlled by the repository and not reproducible from it. A blank would imply they did not matter.
Use provenance to judge comparability, not performance
Provenance exists so you can tell whether two records are comparable. Chiu’s test strips the provenance block from the reports and requires the remainder to stay byte-identical, which keeps provenance from leaking into scoring.
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Record the decision context, not just the outcome
For policy decisions, he describes his own implementation as storing whether the policy mode was advisory or enforced, whether the operation was actually blocked, and a status that can express pass, fail, unknown, or conflict. Without the mode and the blocked flag, “fail” could mean either a stopped action or a note nobody acted on.
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When the record stops being written
A second failure is quieter: the writer stops. Chiu reports that his weekly metrics table went unwritten for seven weeks over the summer, and that he found the gap on September 22 by auditing the ledger. He backfilled the entry as “no record” rather than estimating it. This is his personal publishing workflow, not evidence of how often this happens elsewhere. The lesson is that an empty stretch is ambiguous (nothing happened, or nothing was recorded?) unless a separate mechanism detects a stopped writer.
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Three checks you can run
These are the author’s proposals. He says explicitly that he has not run the stop and split tests against another stack, so treat them as starting points.
- Stop test. In a test environment, disable the process that writes records. Measure how long it takes for anything to report the failure. If the answer is “never” or “someone happens to notice,” the record’s silence is not evidence of inactivity.
- Split test. Interrupt a multi-step run so it retries. Check whether the record still shows one task as one unit of work, or whether the retry creates a second record that breaks attribution.
- Six-week reconstruction. Pick a decision from six weeks ago and answer who made it and under which version of which rule, without asking anyone who was there. The essay’s opening describes the failure case: a team debugging a silent failure who could not say what a given call had cost or who had issued it.
A review checklist for your own records
| Question to ask | Failure it catches |
|---|---|
| Is “unknown” distinct from a default value? | Gaps silently filled with plausible values |
| Does it hold requested or effective values? | Runtime overriding what the caller asked for |
| Can the source of a setting change outside the recorded artifact? | Config files, mutable tags, re-pulled models |
| Would a stopped writer be detected? | Weeks of silence read as normal |
| Does a retry stay one unit of work? | Broken attribution after interruption |
| Does a decision store advisory vs. enforced and blocked or not? | Ambiguous “fail” results |
What the essay does not establish
The essay names no vendor or exact model, and its percentages are individual run results, not an industry statistic. Chiu is candid about generality: “I have hit this once, in one field, so the general form is a hypothesis worth testing rather than a law.” He also says his open-source reference implementation evaluates configuration and writes decisions, but excludes provider credentials, secret-manager resolution, and agent execution. He therefore does not claim a shipped answer for credential rotation in a running session.
The Bottom Line
Test your records by asking them a question after the fact. If you cannot say what actually ran, under which rule version, and whether a missing entry means “nothing happened” or “nothing was written,” more columns will not fix it. Store absence explicitly, store effective behavior, and make a stopped writer loud.
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