AI systems foundations

Read an inference contract

Read an inference contract through a bounded evidence-first AI operations workflow in the training lab.

AI systems foundations
9 min Beginner Lesson 5 of 180
cat /opt/ai-lab/foundations/system-map.txtaiops models inspect read-an-inference-contracthead -n 3 /opt/ai-lab/foundations/system-map.txt
Lesson 5 of 180 0/180 lessons 0/18 missions 0/11 briefings AI systems foundations · 9 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 9 min

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

Inspect the ai systems foundations baseline

Type this exactly: cat /opt/ai-lab/foundations/system-map.txt

cat /opt/ai-lab/foundations/system-map.txt
Run the models review

Type this exactly: aiops models inspect read-an-inference-contract

aiops models inspect read-an-inference-contract
Confirm the evidence

Type this exactly: head -n 3 /opt/ai-lab/foundations/system-map.txt

head -n 3 /opt/ai-lab/foundations/system-map.txt
Lesson support

What to notice while you play.

Objective

Use commands and observable output to explain read an inference contract without changing a real model or service.

Hint

Start with cat /opt/ai-lab/foundations/system-map.txt. Then run aiops models inspect read-an-inference-contract before collecting the final evidence.

Why it matters

Read an inference contract 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 read an inference contract.
  • 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.