Inference requests and APIs · Lesson 15 of 16 · 7 min

Build an API evidence bundle

An API evidence bundle needs request IDs, status, timing, versions and a redacted contract example. It should explain the failure without exporting credentials or user prompts.

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learner@clairos:~ $

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-inference-apis-015.json. Separate the recorded facts from your assumptions.
Hint & worked example
An API evidence bundle needs request IDs, status, timing, versions and a redacted contract example. It should explain the failure without exporting credentials or user prompts.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-inference-apis-015.json
```
Common mistake to avoid: Add credentials so every reader can reproduce the call directly.
2
Isolate the deciding signal
Select the authorization_included field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Share the bounded metadata bundle without adding authorization values.
A successful JSON query isolates authorization_included.
```
jq .authorization_included /opt/ai-lab/cases/aiops-inference-apis-015.json
```
Common mistake to avoid: Using a different case or an unrelated signal as the justification.
3
Record your operational decision
Choose the justified code: share-redacted-bundle, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-inference-apis-015-decision.txt.
Hint & worked example
Share the bounded metadata bundle without adding authorization values.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'share-redacted-bundle' > /home/learner/lab/aiops-inference-apis-015-decision.txt
```
Common mistake to avoid: Add credentials so every reader can reproduce the call directly.

Understand the pattern

An API evidence bundle needs request IDs, status, timing, versions and a redacted contract example. It should explain the failure without exporting credentials or user prompts.

Interpret the evidence

Share the bounded metadata bundle without adding authorization values.

A tempting mistake

Add credentials so every reader can reproduce the call directly.

All names, measurements, prices, versions, and thresholds in this exercise are fictional training data. The evidence supports this bounded scenario, not a claim about a live provider.

Worked example and expected result

$ cat /opt/ai-lab/cases/aiops-inference-apis-015.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "included": [
    "request_id",
    "status",
    "timing",
    "model_revision"
  ],
  "authorization_included": false
}

Exit status: 0. The command completed successfully in the training fixture.

$ jq .authorization_included /opt/ai-lab/cases/aiops-inference-apis-015.json

false

Exit status: 0. The command completed successfully in the training fixture.

$ printf '%s\n' 'share-redacted-bundle' > /home/learner/lab/aiops-inference-apis-015-decision.txt

(no output; exit 0)

Exit status: 0. The command completed successfully in the training fixture.

Try a variation

Name the assumption that would have to change for “share-redacted-bundle” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Build an API evidence bundle” justify?Add credentials so every reader can reproduce the call directly.Make the change now and gather the missing evidence afterward.Share the bounded metadata bundle without adding authorization values.

Apply it elsewhere

A colleague concludes: “Add credentials so every reader can reproduce the call directly.” What should you do?Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Inference API checkpoint Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision