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

  • Exam Code: 1z0-1157-26
  • Exam Name: Agentic AI Foundations Associate
  • Updated: Sep 24, 2026
  • Q & A: 60 Questions and Answers

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Oracle 1z0-1157-26 Exam Syllabus Topics:

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

                                                                Oracle Agentic AI Foundations Associate Sample Questions:

                                                                Question #1

                                                                Which OCI capability is required for serving fine-tuned or imported custom models?

                                                                • A. Dedicated AI Clusters
                                                                • B. OCI Object Storage buckets
                                                                • C. Free Tier compute instances
                                                                • D. Shared On-Demand inference
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: A  🗳️

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                                                                Question #2

                                                                When is MCP most valuable?

                                                                • A. When defining prompts and output parsers inside a single LangChain chain.
                                                                • B. For simple local utilities like add() and multiply() .
                                                                • C. When building a single-agent app with no external dependencies.
                                                                • D. When tools are external or cloud-hosted.
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: D  🗳️

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                                                                Question #3

                                                                In JSON-RPC 2.0, what is the difference between a request and a notification?

                                                                • A. A request includes an ID and expects a reply, while a notification does not.
                                                                • B. A request can carry structured data, while a notification can carry only text.
                                                                • C. A request uses HTTP, while a notification uses a different transport protocol.
                                                                • D. A request is sent unencrypted, while a notification is encrypted before processing.
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: A  🗳️

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                                                                Question #4

                                                                In the OpenAI Agents SDK, what is the role of the Runner?

                                                                • A. It is the deployment platform for hosting agents in production.
                                                                • B. It handles authentication and rotates API keys for the agent.
                                                                • C. It executes the agent loop.
                                                                • D. It defines JSON schemas for function tools at compile time.
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: C  🗳️

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                                                                Question #5

                                                                In a production MCP architecture, where are tool implementations hosted?

                                                                • A. Hardcoded inside the agent file using @tool decorators.
                                                                • B. Inside the LLM's training weights.
                                                                • C. In the MCP client application that invokes the tools.
                                                                • D. On a separate MCP server.
                                                                Reveal Solution  Discussion  0

                                                                Correct Answer: D  🗳️

                                                                Explanation: Only visible for Exams4Collection members. You can sign-up / login (it's free).

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