Quiz: Agentic Agents Flashcards
(15 cards)
What is the core reasoning engine in most modern AI agents?
A Large Language Model (LLM).
What is the primary purpose of LangChain?
To simplify the development of applications powered by language models, including AI agents.
How does LangGraph differ from LangChain?
LangGraph is designed for building more complex, stateful agentic applications with cyclical workflows, while LangChain is more focused on linear chains of operations.
What is the goal of the Model Context Protocol (MCP)?
To standardize how AI models interact with external tools and data sources.
What problem does the Agent-to-Agent (A2A) protocol aim to solve?
Enabling secure and interoperable communication between different AI agents.
What is Retrieval Augmented Generation (RAG) used for?
To improve the factual accuracy and reduce hallucinations in LLM responses by providing external knowledge.
Give an example of a business use case for AI agents in financial services.
Enhanced fraud detection and prevention, automated compliance monitoring, personalized wealth management.
What is a key challenge in ensuring the reliability of AI agents?
The potential for LLMs to hallucinate or generate incorrect information.
What is the importance of ‘memory’ in the context of AI agents?
It allows agents to maintain context, learn from past interactions, and make more informed decisions over time.
What does the ‘perceive-reason-act-learn’ cycle describe?
The continuous operational loop of an AI agent.
Name one company that provides a platform for building AI agents.
Google (Vertex AI Agent Builder), Microsoft, Amazon (AWS), OpenAI, IBM.
What is ‘tool use’ in the context of AI agents?
The ability of an agent to interact with external systems or APIs to perform actions or gather information.
Why is ‘human-in-the-loop’ important for AI agents in regulated industries?
To provide oversight, validation, and control for critical decisions and sensitive tasks.
What is a potential benefit of using multi-agent systems?
Specialization of agents, scalability, fault tolerance, ability to solve complex problems.
What is a key focus of Google’s Vertex AI Agent Builder?
Providing an enterprise-grade platform with interoperability through MCP and A2A.
