Retrieval and embeddings

Review chunk boundaries

Review chunk boundaries through a bounded evidence-first AI operations workflow in the training lab.

Retrieval and embeddings
8 min Admin Lesson 94 of 180
cat /opt/ai-lab/rag/index-status.jsonaiops rag inspect review-chunk-boundariesjq . /opt/ai-lab/rag/index-status.json
Lesson 94 of 180 0/180 lessons 0/18 missions 0/11 briefings Retrieval and embeddings · 8 min
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AI operations terminal Training lab
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learner@aiops:/home/learner $ AI operations lab: type a command, press Enter
Instructions 8 min

Click any instruction for the command details, the why, and the common mistake to avoid.

Inspect the retrieval and embeddings baseline

Type this exactly: cat /opt/ai-lab/rag/index-status.json

cat /opt/ai-lab/rag/index-status.json
Run the rag review

Type this exactly: aiops rag inspect review-chunk-boundaries

aiops rag inspect review-chunk-boundaries
Confirm the evidence

Type this exactly: jq . /opt/ai-lab/rag/index-status.json

jq . /opt/ai-lab/rag/index-status.json
Lesson support

What to notice while you play.

Objective

Use commands and observable output to explain review chunk boundaries without changing a real model or service.

Hint

Start with cat /opt/ai-lab/rag/index-status.json. Then run aiops rag inspect review-chunk-boundaries before collecting the final evidence.

Why it matters

Review chunk boundaries is an operator skill because AI behavior must be connected to versioned configuration, runtime state, and inspectable evidence.

Common mistakes
  • Skipping the baseline fixture before reasoning about review chunk boundaries.
  • Treating one simulated output as proof of root cause instead of one bounded piece of evidence.
Reference

Commands in this lesson.

aiops models

Inspect the simulated model catalog, manifests, and version comparisons.

aiops prompts

Review versioned prompt metadata and deterministic prompt diffs.

aiops evals

Run and inspect bounded evaluation fixtures without model execution.

aiops rag

Inspect retrieval documents, chunks, index status, and reviewed results.

aiops traces

Read deterministic request traces, summaries, and latency evidence.

aiops guardrails

Review simulated guardrail policies, checks, and audit summaries.

aiops cost

Estimate cost and capacity from fixed training metrics.

aiops incidents

Review incident timelines, evidence bundles, and operator notes.

jq

Query JSON fixtures with a small declarative path subset; no expression execution occurs.