Retrieval and embeddings · Lesson 1 of 16 · 6 min

Map the retrieval pipeline

A retrieval pipeline separates ingestion, chunking, embedding, indexing and querying. Locate where evidence disappears before changing the answer-generation prompt.

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-retrieval-embeddings-001.json. Separate the recorded facts from your assumptions.
Hint & worked example
A retrieval pipeline separates ingestion, chunking, embedding, indexing and querying. Locate where evidence disappears before changing the answer-generation prompt.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-retrieval-embeddings-001.json
```
Common mistake to avoid: Blame the response prompt for an empty index.
2
Isolate the deciding signal
Select the indexed field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Inspect the indexing boundary because embedded chunks never reached the index.
A successful JSON query isolates indexed.
```
jq .indexed /opt/ai-lab/cases/aiops-retrieval-embeddings-001.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: inspect-index-write, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-retrieval-embeddings-001-decision.txt.
Hint & worked example
Inspect the indexing boundary because embedded chunks never reached the index.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'inspect-index-write' > /home/learner/lab/aiops-retrieval-embeddings-001-decision.txt
```
Common mistake to avoid: Blame the response prompt for an empty index.

Understand the pattern

A retrieval pipeline separates ingestion, chunking, embedding, indexing and querying. Locate where evidence disappears before changing the answer-generation prompt.

Interpret the evidence

Inspect the indexing boundary because embedded chunks never reached the index.

A tempting mistake

Blame the response prompt for an empty index.

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-retrieval-embeddings-001.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "ingested": 120,
  "chunked": 842,
  "embedded": 842,
  "indexed": 0
}

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

$ jq .indexed /opt/ai-lab/cases/aiops-retrieval-embeddings-001.json

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

$ printf '%s\n' 'inspect-index-write' > /home/learner/lab/aiops-retrieval-embeddings-001-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 “inspect-index-write” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Map the retrieval pipeline” justify?Blame the response prompt for an empty index.Make the change now and gather the missing evidence afterward.Inspect the indexing boundary because embedded chunks never reached the index.

Apply it elsewhere

A colleague concludes: “Blame the response prompt for an empty index.” 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: Inspect source documents Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision