Oracle 1z0-1157-26 Exam : Agentic AI Foundations Associate

1z0-1157-26
  • Exam Code: 1z0-1157-26
  • Exam Name: Agentic AI Foundations Associate
  • Updated: Sep 08, 2026
  • Q & A: 60 Questions and Answers

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Oracle 1z0-1157-26 Exam Syllabus Topics:

SectionWeightObjectives
OCI Enterprise AI Agents25%- OCI Enterprise AI platform and agent services
  • 1. OCI Enterprise AI Agents development, orchestration, and execution
    • 2. OCI Enterprise AI platform services for the enterprise AI agent lifecycle
      • 3. OCI Enterprise AI Agents building blocks: Responses API, tools, memory, and vector stores
        • 4. Deployment and scaling options
          • 5. Building and running AI agents with OCI Enterprise AI Agents
            Model Context Protocol (MCP) Fundamentals15%- MCP architecture and integration
            • 1. MCP hosts, clients, servers, tools, resources, and prompts
              • 2. Role of MCP in standardizing integration between AI agents and external tools
                • 3. JSON-RPC 2.0 message format
                  • 4. MCP transport options including stdio and Streamable HTTP
                    • 5. Integrating MCP capabilities into agentic AI workflows
                      OpenAI Responses API and Agents SDK15%- OpenAI agent stack
                      • 1. Multi-agent design patterns and handoffs
                        • 2. Function calling and tools
                          • 3. Guardrails for validating inputs, outputs, and agent actions
                            • 4. OpenAI Responses API for agentic applications
                              • 5. Agents SDK primitives: Agent, Runner, Tool, Handoffs, and Guardrails
                                Agentic AI for Oracle AI Database25%- Oracle AI Database agentic AI capabilities
                                • 1. Oracle AI Vector Search, Select AI, and MCP integration
                                  • 2. Grounding agent responses with enterprise data from Oracle AI Database
                                    • 3. Select AI for natural-language interaction with Oracle AI Database
                                      • 4. Oracle AI Vector Search workflow: document chunking, embedding generation, similarity search, and retrieval
                                        • 5. Oracle Autonomous AI Database MCP Server
                                          • 6. VECTOR data type, vector embeddings, and similarity search
                                            • 7. Oracle AI Database Private Agent Factory
                                              Introduction to AI Agents15%- AI agent fundamentals
                                              • 1. Core components of an AI agent: LLM, tools, and orchestration loop
                                                • 2. Agent reasoning patterns: Chain-of-Thought and ReAct
                                                  • 3. Safety considerations and guardrail techniques
                                                    • 4. Differentiate AI agents from traditional chatbots and rule-based workflows
                                                      LangChain for AI Agents5%- LangChain fundamentals and agent construction
                                                      • 1. LangChain tools, prompts, and chains
                                                        • 2. LangChain agent reasoning and tool execution flow
                                                          • 3. LangChain core abstractions: chat models, prompts, tools, and agents

                                                            Oracle Agentic AI Foundations Associate Sample Questions:

                                                            Question 1

                                                            What is Oracle AI Database Private Agent Factory?

                                                            A. A managed orchestration layer for deploying to Kubernetes
                                                            B. A no-code platform for building agents
                                                            C. A backup utility for embeddings
                                                            D. A hardware appliance for training models on-premises


                                                            Question 2

                                                            Which approaches are supported by OCI Enterprise AI Agents?

                                                            A. Call the Responses API directly or deploy a hosted agent application.
                                                            B. Deploy using Python-only or Java-only options.
                                                            C. Build a frontend agent or a backend agent.
                                                            D. Select a free or paid deployment model.


                                                            Question 3

                                                            Which set lists built-in tool categories supported by OCI Enterprise AI Agents?

                                                            A. SMS, Email, and Fax connectors.
                                                            B. VCN routing and load balancing tools.
                                                            C. File Search, Code Interpreter, Function Calling, and MCP Calling.
                                                            D. SSH, FTP, and RDP tools.


                                                            Question 4

                                                            Which SQL function computes distance between vectors in Oracle AI Vector Search?

                                                            A. VECTOR_DISTANCE()
                                                            B. VECTOR_SCORE()
                                                            C. SCORE_SIMILARITY()
                                                            D. EMBEDDING_DISTANCE()


                                                            Question 5

                                                            In the OpenAI Agents SDK, how does a Handoff differ from the Manager pattern?

                                                            A. A Handoff transfers control; a Manager keeps control.
                                                            B. A Handoff calls tools directly; a Manager only routes messages.
                                                            C. A Handoff uses async execution; a Manager uses sync execution.
                                                            D. A Handoff keeps control; a Manager transfers control.


                                                            Solutions:

                                                            Question 1
                                                            Answer: B
                                                            Question 2
                                                            Answer: A
                                                            Question 3
                                                            Answer: C
                                                            Question 4
                                                            Answer: A
                                                            Question 5
                                                            Answer: A

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