A team is integrating Genie Spaces with their agentic system. They want to monitor the performance of natural language queries, including accuracy and latency. They also need to track changes to the Genie Spaces configuration. What should they do?

Store query logs in a separate database and manually review

Use MLflow to log query metrics and track Genie Spaces configuration as artifacts

Use a custom dashboard that queries Genie Spaces logs

Rely on Genie Spaces built-in monitoring only

A company is building a system that handles customer inquiries. They want to use multiple specialized agents: one for order status, one for product recommendations, and one for returns. These agents need to communicate with each other to resolve complex issues. Which design approach is most appropriate?

Use a multi-agent system where a coordinator agent delegates tasks to specialized agents

Use a single agent with a large prompt covering all scenarios

Use separate standalone agents with no communication

Create a single agent that handles all tasks

A company is designing a multi-agent system where one agent handles user interaction and another retrieves data from a conversational API. The system must ensure that user queries are answered quickly, but the data retrieval agent can be slow due to complex queries. What is the best way to handle this?

Cache all data retrieval results to avoid delays

Use synchronous communication and block until data is retrieved

Use asynchronous communication between agents

Have the user-facing agent perform the data retrieval directly

A development team is building an agent that needs to fetch data from a Databricks warehouse. They want to use a conversational API that allows the agent to issue natural language queries and receive structured results, while ensuring secure access. What is the recommended approach?

Use a direct JDBC connection to the warehouse

Use the Genie API to send natural language queries and receive results

Use a webhook to trigger a notebook that runs a query

Use the Databricks SQL Connector to run SQL queries

DatabricksCertified Generative AI Engineer Associate

Domain 3Objective 5

Tooling and Frameworks GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions (Page 1)

Part of the Section 3: Application Development domain, which makes up ~18% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~6–11 in this domain), expect 1–2 from this objective — we provide 24 practice questions to prepare you well beyond it. (estimate)

24questions here

5free pages

6concepts

Questions 1–5

1foundation · easy
A team is building a generative AI application that requires a modular framework with strong support for integrating custom tools and managing complex chains. Which orchestration framework is specifically designed to provide a modular and composable approach for building applications with language models?
Select an answer first
2expert · hard
A team is integrating Genie Spaces with their agentic system. They want to monitor the performance of natural language queries, including accuracy and latency. They also need to track changes to the Genie Spaces configuration. What should they do?
Select an answer first
3application · medium
A company is building a system that handles customer inquiries. They want to use multiple specialized agents: one for order status, one for product recommendations, and one for returns. These agents need to communicate with each other to resolve complex issues. Which design approach is most appropriate?
Select an answer first
4expert · hard
A company is designing a multi-agent system where one agent handles user interaction and another retrieves data from a conversational API. The system must ensure that user queries are answered quickly, but the data retrieval agent can be slow due to complex queries. What is the best way to handle this?
Select an answer first
5application · medium
A development team is building an agent that needs to fetch data from a Databricks warehouse. They want to use a conversational API that allows the agent to issue natural language queries and receive structured results, while ensuring secure access. What is the recommended approach?
Select an answer first

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Tooling and Frameworks GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions (Page 1)

Questions 1–5

A team is integrating Genie Spaces with their agentic system. They want to monitor the performance of natural language queries, including accuracy and latency. They also need to track changes to the Genie Spaces configuration. What should they do?

A development team is building an agent that needs to fetch data from a Databricks warehouse. They want to use a conversational API that allows the agent to issue natural language queries and receive structured results, while ensuring secure access. What is the recommended approach?

Keep studying — Section 3: Application Development