CCAR-P Practice Question: Developer Productivity and Operational Enablement
An engineer is onboarding to a codebase that calls Claude and needs to understand, at a glance, which model, temperature, and max_tokens values a given feature uses. The team wants this discoverable without reading application source. What is the most effective practice?
⚠ Common exam trap
The trap here is accepting a familiar but weak documentation habit, such as code comments, when the requirement is a durable and reviewable source of truth.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Store model and sampling parameters in a versioned configuration file that the application loads at startup.
Parameters that drive model choice, cost, and behavior belong in a versioned configuration file rather than scattered through code or held in memory. This makes them discoverable at a glance, reviewable in pull requests, and changeable without a code deploy. Comments, debug logs, and tribal knowledge each fail at least one of those properties, which is why configuration-as-code is the standard practice for developer enablement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Store model and sampling parameters in a versioned configuration file that the application loads at startup.
Why this is correct
Externalizing model and sampling parameters into a versioned configuration file makes them discoverable without reading application code. Engineers can inspect one file to see which model and limits a feature uses, and changes are reviewable through normal pull requests. It also decouples tuning from code changes, so adjusting temperature or max_tokens does not require a code deploy, improving both clarity and iteration speed.
- ✗
Rely on code comments near each API call to document the chosen parameters.
Why it's wrong here
Comments drift as code evolves and are invisible to anyone browsing configuration or dashboards. They also cannot be validated at runtime, so a stale comment can mislead an engineer into thinking a model or limit is current when it is not. Comments are useful context but a poor source of truth for parameters that affect cost and behavior. A versioned configuration file is discoverable, reviewable, and enforceable.
- ✗
Ask each engineer to memorize the parameters for the features they own.
Why it's wrong here
Tribal knowledge does not scale and disappears when engineers change teams. It also cannot be reviewed or validated, so inconsistencies go unnoticed until they cause incidents or cost surprises. Onboarding engineers specifically need a discoverable artifact, not institutional memory. Externalizing parameters into a versioned configuration file makes the information durable, reviewable, and independent of any individual's recall.
- ✗
Log the parameters at debug level so they appear in application logs when needed.
Why it's wrong here
Debug logs are transient and only visible after a request runs, which means an engineer cannot inspect a feature before executing it. Logs also vary by environment and retention policy, so they are unreliable as documentation. The team wants at-a-glance discoverability, which logs cannot provide. A versioned configuration file gives a stable, reviewable source of truth accessible without running the code.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Anthropic exam blueprint
This CCAR-P practice question is part of Courseiva's free Anthropic certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CCAR-P exam.