AB-620 Exam Questions & Answers

Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Configure run after is the control that routes execution to an error-handling action when the external-service action fails, times out, is skipped, or reaches another selected status. By configuring the notification action to run after failure and timeout, the flow no longer terminates silently and can send a message containing sanitized error context. The handler can then set a deliberate flow status, record a correlation ID, and provide the operator with the failed action and remediation path. This design should be paired with an appropriate retry policy based on whether the external operation is safe to repeat. For non-idempotent writes, automatic retry may create duplicates and should generally be disabled or protected with an idempotency key. Error notifications must not include tokens, secrets, or unrestricted payloads. Testing should deliberately produce an authorization failure, timeout, and service error to prove that each status enters the handler and that the notification itself has a fallback if its connector is unavailable. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Implement error handling in agent flows.

A . Use a Microsoft Graph connector to index the partner's travel advisory content. Microsoft 365 Copilot connectors---formerly called Microsoft Graph connectors---index non-Microsoft enterprise content into Microsoft Graph, making it available for semantic knowledge grounding and citations. Microsoft Learn: Copilot connectors

D . Add the internal policy documents as a knowledge source. The SharePoint PDFs and policy documents should be connected as agent knowledge so generative answers can retrieve and summarize the relevant content. This is scalable and avoids manually maintaining document-specific topics. Microsoft Learn: SharePoint knowledge sources

B violates the requirement to avoid manually authored Q&A topics. C could produce ungrounded responses from unapproved public sources and would not satisfy the airline's accuracy, security, or compliance requirements.

Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Flow run history provides the chronological record needed to identify which executions succeeded, failed, timed out, or behaved differently. Opening the failed run details then exposes the action-level inputs, outputs, status, duration, connection errors, and failure message that explain the inconsistent result. These two views support evidence-based diagnosis without changing the flow before the cause is known. Updating the trigger, increasing a timeout, or changing connection behavior are potential remediations only after the failure pattern has been established. The Analytics summary is useful for aggregate trends but lacks the full payload and step sequence of an individual run. The Activity tab's Error column can help locate failures, but the question asks for the two complete diagnostic actions and the detailed run inspection is the more direct evidence. Reviewers should compare a failed run with a successful run using the same input, check transient versus deterministic errors, and redact or restrict access to sensitive data captured in run history. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Monitor agent flows.

Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The approved solution preserves the reusable prompt template and changes the model configuration that actually executes it. Applying the established template retains the required tone, structure, and repeatable instruction set. Selecting an approved model in the prompt configuration ensures that prompt-driven responses are produced by a model permitted under the organization's governance policy. An instruction that tells the model to use an approved model cannot control the underlying runtime; model selection is a platform configuration, not a behavior the model can enforce on itself. Citations address provenance, not model approval. Azure AI Search supplies grounding data but also does not choose the foundation model. Publishing is necessary to expose completed changes to users, yet it does not automatically substitute a compliant model. The team should also test the prompt against representative inputs after changing models, because output quality, formatting adherence, latency, and token behavior can vary across models even when the prompt remains identical. Governance records should capture the selected model, prompt version, owner, and validation evidence. Study Guide alignment: Integrate and extend agents in Copilot Studio > Integrate agents with Azure > Configure custom prompts to use the Foundry model catalog.

Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A generative answers node inside the topic is the correct place to retrieve from configured knowledge sources for that specific conversational path. The node can use the user's message as input, search designated sources, and generate a grounded response from the retrieved content. Topic-level sources can override the broader agent-level set, which is useful when the topic must restrict itself to approved data. A custom prompt that merely instructs the model to use company information does not create or enforce a retrieval connection. Increasing the response limit affects length, not grounding. Analytics measures usage after the fact and cannot supply knowledge. Adding SharePoint only at agent level is unnecessarily narrow and would not satisfy the requirement for custom sources configured within the topic. The builder should enable Search only selected sources when strict scoping is required and turn off general knowledge if no ungrounded fallback is allowed. Testing should inspect both the answer and the resource details to confirm that the intended source supplied the evidence. Study Guide alignment: Plan and configure agent solutions > Configure topics > Configure generative answers node; Configure advanced agent responses with custom knowledge sources.