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CCDV-F · Domain 6 of 8 · 3 lessons · about 65 min

Domain 6: Prompt and Context Engineering

Managing what Claude sees: context windows, compaction and subagents, prompts for applications, and handling output defensively. 11% of CCDV-F.

This domain is 11.0% of CCDV-F, about 6 of the 53 questions. It is about the two ends of every call: what goes into the model, and what you do with what comes out.

The vocabulary: context engineering is deciding what information is in the context window at each step, and keeping it relevant as a conversation or agent run grows. Compaction replaces old turns with a summary. The system prompt carries standing instructions separate from the user's messages. Structured output asks for a fixed format, such as JSON matching a schema, so your code can parse it.

The recurring test: never trust the context or the output by default. Prune what no longer helps, isolate noisy work in a subagent, put instructions where they belong, and validate every response before your code acts on it, however confident it sounds.

What the exam guide tests

The official CCDV-F guide lists 3 skills for this domain. Exam questions are written against them, and so are the lessons: each row says where it is covered.

Lessons

1. 6.1 Context engineering: keep the window small and on taskHow to keep an agent's context window useful: measure it, prune tool output, clear and compact old history, and isolate noisy work in subagents.22 min
2. 6.2 Prompt engineering for applications: prompts that run on real dataHow to write prompts an application runs thousands of times: clear rules, examples, the right placement, clean inputs, and changes tested on real cases.22 min
3. 6.3 Output handling: structure it, check it, doubt itHow to get Claude's output in a fixed JSON shape, parse it defensively, check it against schema and business rules, and verify confident answers.21 min

Practice question

From the CCDV-F bank, tagged to this domain. Every answer option is explained. Nothing is stored, nothing to sign up for.