| 1 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | ReAct Pattern | What does "ReAct" stand for when describing agentic reasoning loops? | Easy | 1 | A | Reasoning and Acting. | Reading and Acting. | Researching and Actuating. | Repeating and Acknowledging. |
| 2 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | ReAct Pattern | In a standard ReAct loop, what is the "Observe" step specifically responsible for? | Medium | 1 | C | Thinking about the next step. | Generating a new plan. | Receiving and analyzing the results from a tool execution. | Synthesizing the final answer for the user. |
| 3 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Multi-Expert Agents | Why use a "Multi-Expert" pattern (specialized tools) over a single generic web search tool? | Medium | 1 | B | It reduces API costs and improves speed. | It provides specialized domain knowledge and structured reasoning. | It simplifies the prompt engineering process. | It removes the need for a reasoning-capable LLM. |
| 4 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Prebuilt Components | What is a major advantage of using the prebuilt ToolNode in LangGraph? | Medium | 1 | D | It is the only technical way to invoke tools. | It provides unlimited free API calls. | it executes asynchronous code faster than custom nodes. | It automatically handles tool execution, parsing, and error management. |
| 5 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Coordinator | What is the main responsibility of the "Coordinator" node in a multi-expert system? | Medium | 1 | A | To analyze the query and route it to the correct expert tool or agent. | To execute the underlying Python logic of the tools. | To only summarize the final answer once all tools finish. | To manage the database connection for persistence. |
| 6 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Control Flow | How do you standardly prevent an agent from entering an infinite ReAct loop? | Easy | 1 | C | By switching to a faster LLM model. | By disabling the tool execution node. | By implementing a max_iterations check in the routing logic. | By only allowing HumanMessage inputs. |
| 7 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Expert Tools | In a Multi-Expert architecture, how is a specialized "Expert" typically implemented as a tool? | Hard | 1 | B | As a hardcoded Python logic script. | As a tool that invokes a specialized LLM with a domain-specific system prompt. | As a separate physical server deployment. | As a raw SQL query to a knowledge base. |
| 8 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Message Protocol | What specific content in an AIMessage signals that the agent wants to use a tool? | Medium | 1 | B | The content string contains the word "tool". | The tool_calls parameter is populated with tool details. | It is followed immediately by a SystemMessage. | The role is set to "assistant_tool". |
| 9 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Planning Agent | What is the role of a "Planning Agent" in advanced agentic workflows? | Hard | 1 | D | To execute the final code. | To store the memory of the conversation. | To check for grammar errors. | To break down a complex query and decide on a sequence of actions for the coordinator. |
| 10 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Reflection | What does the "Reflection" pattern involve in agentic AI? | Medium | 1 | A | The agent reviewing its own output or steps to identify and fix errors. | The agent showing its thoughts to the user. | The database reflecting the latest state. | The coordinator mirroring the user's input. |
| 11 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Multi-Expert Agents | Why is Multi-Expert better than Web Search for analysis? | Medium | 1 | B | Lower token cost. | Consistent reasoning and synthesis. | No knowledge cutoff. | Faster execution. |
| 12 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Coordinator | What does the "Think" phase of the Coordinator LLM involve? | Medium | 1 | A | Analyzing if help is needed and who to call. | Writing Python code. | Google searching. | Saving checkpoints. |
| 13 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Coordinator | Which method does a Coordinator use to bind tools? | Easy | 1 | D | app.compile() | workflow.add_node() | llm.invoke() | llm.bind_tools([...]) |
| 14 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Control Flow | Which variable tracks reasoning loops in the State? | Easy | 1 | C | messages | user_id | current_iteration | checkpoint_id |
| 15 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Control Flow | Which condition forces a ReAct agent to END? | Medium | 1 | A | No tool_calls or max_iterations reached. | User stops typing. | API key expires. | After every tool call. |
| 16 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Coordinator | How does a Coordinator execute parallel consultations? | Hard | 1 | B | Opening multiple prompts. | Populating multiple items in tool_calls. | Re-running the graph. | Parallel execution is not supported. |
| 17 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Planning Agent | What architectural issue does a Planning Agent solve? | Medium | 1 | C | High latency. | Local hardware limits. | Coordinator overload from too many tasks. | Bypassing checkpointers. |
| 18 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Multi-Expert Agents | How does dynamic expert selection work in advanced systems? | Hard | 1 | D | Browser history check. | Random assignment. | Exact keyword mapping. | Routing prompt returns best expert name. |
| 19 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Multi-Expert Agents | What is the purpose of structured synthesis? | Easy | 1 | A | To combine expert insights into a unified response. | To compress JSON state. | To translate output to code. | To hide tool errors. |
| 20 | Unit 2: Agentic Patterns: Multi-Expert Research Agent | Lec2 | Multi-Expert Agents | What is a major trade-off of the Multi-Expert Pattern? | Medium | 1 | B | Lower accuracy. | Higher cost and latency. | No LangGraph support. | Requires C++ code. |