Claude Certified Architect — Professional glossary
12 terms the exam expects you to know, defined in plain language.
A
- actionable error results(detailed failure messages, specific error details)
- Error results containing specific details that allow automated recovery decisions, unlike generic 'Operation failed' messages.
D
- Detailed Error Response(detailed error messages)
- An error message that provides specific information enabling automated recovery decisions.
- Deterministic Mechanism(deterministic, deterministic mechanisms)
- A programmatic enforcement that guarantees behavior, such as hooks, preconditions, schemas, or tool constraints.
F
- Failure Categories in AI Agents(failure categories, failure categories in this domain)
- Distinct failure types including timeout vs empty result, syntax vs semantic errors, and drift vs overflow.
- Failure Category(failure category, failure categories)
- Distinct types of errors such as timeout vs empty result, syntax vs semantic errors, and drift vs overflow.
P
- Parallel subagents(parallel subagents)
- Subagents that execute concurrently from multiple Task calls in a single turn.
- Probabilistic Mechanism(probabilistic, probabilistic mechanisms)
- A prompt-level encouragement that influences behavior but does not guarantee it, such as prompts or examples.
- Probabilistic Mechanisms(probabilistic mechanisms)
- Mechanisms that encourage behavior but do not guarantee it, such as prompts and few-shot examples.
- Programmatic Enforcement(programmatic enforcement)
- Using code-based controls to ensure behavior in scenarios with financial, legal, or safety stakes.
- Prompt-Level Fix(prompt-level fix)
- Adjusting prompts or examples to solve an issue, suitable for non-critical tasks without financial, legal, or safety stakes.
R
- Right-Sized Solution(right-sized solution, right-sized solutions)
- An appropriate level of complexity that avoids overengineering, such as using a description rewrite instead of a separate classifier model.
- Right-Sized Solutions(right-sized solutions)
- The principle of choosing the simplest adequate fix rather than overengineered infrastructure for AI agent problems.