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

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Exam Code: 1z0-1157-26

Exam Name: Agentic AI Foundations Associate

Updated: Sep 08, 2026

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Oracle 1z0-1157-26 Exam Syllabus Topics:

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


                                                            Question 2

                                                            What occurs during the MCP initialization phase?

                                                            A. The client completes user authentication as part of the protocol initialization exchange.
                                                            B. The server executes all tools once to warm internal caches.
                                                            C. The LLM is fine-tuned using the server's tool definitions.
                                                            D. The client and server exchange protocol versions and supported capabilities.


                                                            Question 3

                                                            Which statement describes the STDIO transport in MCP?

                                                            A. STDIO transport requires OAuth authentication for all requests
                                                            B. STDIO transport serializes messages as plain text rather than JSON
                                                            C. The host launches the server as a local subprocess communicating via stdin and stdout
                                                            D. The server runs as an HTTP service intended for remote multi-client deployments


                                                            Question 4

                                                            Which approaches can generate embeddings for Oracle AI Vector Search workflows?

                                                            A. Export data to a Python environment, generate embeddings, then reimport via SQL Loader
                                                            B. Use ONNX models in-database or external REST-based embedding providers
                                                            C. Train a custom embedding model and manually insert vectors row by row
                                                            D. Use external REST APIs exclusively, since in-database embedding is not supported


                                                            Question 5

                                                            What is the purpose of OCI Enterprise AI Governance?

                                                            A. Applying guardrails, identity controls, and network security controls to AI workloads.
                                                            B. Monitoring model latency and optimizing inference throughput.
                                                            C. Managing model versions and rolling back failed deployments.
                                                            D. Replacing the AI agent runtime layer.


                                                            Solutions:

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

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