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CCAR-F · Study Guide

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Domain 5

Context Management & Reliability

6 build exercises to practice the concepts in this domain.

5.1Intermediate45 minutes

5.1 — Build a Persistent Case Facts Context Manager

What you will learn

  • A case-facts block is carried verbatim so amounts, dates, and ids survive summarisation.
  • Trim tool results to the fields you will need before they pile up.
  • Repeated summaries drop numbers, dates, and identifiers.
  • Put the key findings at the start of a long aggregated input.
  • The API is stateless. Every request must include the history it needs.
Open lesson 5.1
5.2Intermediate40 minutes

5.2 — Build an Escalation Decision Engine

What you will learn

  • Escalate when the customer asks for a person, when policy has a gap, or when the agent cannot proceed.
  • Do not escalate on tone, or on the model's own confidence score.
  • A frustrated customer with a resolvable issue is not the same as an explicit request for a human.
  • Several matching customers means ask for another identifier, not pick one.
  • Put the escalation criteria, with a few examples, in the system prompt before you add machinery.
Open lesson 5.2
5.3Advanced50 minutes

5.3 — Build a Structured Error Propagation System

What you will learn

  • An upstream error names the failure type, what was tried, partial results, and other approaches.
  • A timeout is not the same event as a successful query with no rows.
  • Do not swallow the error, and do not abort the whole workflow for a local failure.
  • Retry a transient failure locally before you tell the coordinator.
  • The synthesis should say which parts of the question are uncovered.
Open lesson 5.3
5.4Advanced60 minutes

5.4 — Build a Context-Resilient Codebase Explorer

What you will learn

  • Degradation is an attention problem. Raising the token limit does not restore specificity.
  • A scratchpad file keeps findings outside the conversation.
  • A subagent is a fresh context, not only a way to run work in parallel.
  • A state manifest lets a crashed run continue.
  • Inject a summary between phases so the next phase does not rediscover the repo.
Open lesson 5.4
5.5Advanced50 minutes

5.5 — Build a Confidence-Calibrated Review Router

What you will learn

  • A 97% overall accuracy can hide a 40% error rate on one document type.
  • Track accuracy by document type and by field.
  • Calibrate raw confidence on a labelled set before you trust a threshold.
  • Sample high-confidence items too, not only the ones the model doubted.
  • Spend a limited review queue on the least certain items first.
Open lesson 5.5
5.6Advanced60 minutes

5.6 — Build a Provenance-Preserving Synthesis Pipeline

What you will learn

  • A claim mapping carries the claim, source URL, document name, excerpt, and publication date.
  • Those fields have to survive every later summary.
  • When sources disagree, keep both values and say where each came from.
  • Dates tell a trend apart from a contradiction.
  • Render financial comparisons as a table, news as prose, and technical findings as a list.
Open lesson 5.6