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

  • Exam Code: 1z0-1157-26
  • Exam Name: Agentic AI Foundations Associate
  • Updated: Sep 11, 2026
  • Q & A: 60 Questions and Answers

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Oracle 1z0-1157-26 Exam Syllabus Topics:

SectionObjectives
OCI Enterprise AI Agents- OCI Enterprise AI platform
  • 1. Building and running AI agents
    • 2. OCI Enterprise AI Agents service
      • 3. Deployment and scaling
        • 4. Agent development, orchestration, and execution
          • 5. Responses API, tools, memory, and vector stores
            Agentic AI for Oracle AI Database- Oracle AI Database agentic AI capabilities
            • 1. Grounding agent responses with enterprise data
              • 2. Oracle AI Database Private Agent Factory
                • 3. Select AI
                  • 4. Vector data types, embeddings, and similarity search
                    • 5. Document chunking, embedding generation, and retrieval
                      • 6. Oracle Autonomous AI Database MCP Server
                        • 7. Oracle AI Vector Search
                          OpenAI Responses API and Agents SDK- OpenAI agent development
                          • 1. Responses API
                            • 2. Guardrails and tracing
                              • 3. Function calling and tools
                                • 4. Multi-agent handoffs
                                  • 5. OpenAI Agents SDK
                                    Introduction to MCP- Model Context Protocol fundamentals
                                    • 1. Tool discovery and interoperability
                                      • 2. MCP concepts and architecture
                                        • 3. MCP clients and servers
                                          Introduction to AI Agents- AI agent fundamentals and architecture
                                          • 1. Agent reasoning patterns including Chain-of-Thought and ReAct
                                            • 2. Safety, guardrails, and responsible agentic workflows
                                              • 3. Core agent components: LLMs, tools, and orchestration loops
                                                • 4. AI agents, traditional chatbots, and rule-based systems
                                                  - Agent development concepts
                                                  • 1. Function calling and tool use
                                                    • 2. Multi-agent design patterns and handoffs
                                                      • 3. OpenAI Agents SDK guardrails
                                                        LangChain for AI Agents- LangChain fundamentals
                                                        • 1. LangChain and LangChain Expression Language
                                                          • 2. Tools, tool schemas, and tool execution
                                                            • 3. Agent invocation and orchestration flow
                                                              • 4. Building agents with LangChain

                                                                Oracle Agentic AI Foundations Associate Sample Questions:

                                                                Question #1

                                                                Which approaches are supported by OCI Enterprise AI Agents?

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

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                                                                Question #2

                                                                Which statement describes an MCP Host?

                                                                • A. It executes tool implementations directly and returns results to the LLM.
                                                                • B. It is the external REST API wrapped by the MCP server.
                                                                • C. Coordinates the LLM, user interaction, and MCP client connections to servers.
                                                                • D. It defines the protocol messages between clients and servers.
                                                                Answer: C

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                                                                Question #3

                                                                What is the architectural advantage of Autonomous AI Database MCP Server over a separately deployed third- party MCP server?

                                                                • A. It eliminates the need for SQL queries entirely.
                                                                • B. It reduces operational overhead and enforces security inside the database.
                                                                • C. It uses a common MCP host for all database connections.
                                                                • D. It moves all query execution to a separate compute tier outside the database.
                                                                Answer: B

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                                                                Question #4

                                                                Which OCI services are used for observability and auditing of deployed AI agents?

                                                                • A. OCI Data Catalog, OCI Search, and OCI DNS
                                                                • B. OCI Events, OCI Functions, and OCI Vault
                                                                • C. OCI Streaming, OCI Queue, and OCI Email Delivery
                                                                • D. OCI Logging, OCI Monitoring, and OCI Audit
                                                                Answer: D

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                                                                Question #5

                                                                Why are docstrings especially important when defining LangChain tools with the @tool decorator?

                                                                • A. They improve Python execution speed.
                                                                • B. They encrypt tool arguments before execution.
                                                                • C. They tell the LLM when and how to use the tool.
                                                                • D. They determine which API provider LangChain uses.
                                                                Answer: C

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