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

1z0-1157-26 real exams

Exam Code: 1z0-1157-26

Exam Name: Agentic AI Foundations Associate

Updated: Sep 15, 2026

Q & A: 60 Questions and Answers

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1z0-1157-26 exam dumps

Oracle 1z0-1157-26 Exam Syllabus Topics:

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

                                                            Oracle Agentic AI Foundations Associate Sample Questions:

                                                            Question #1
                                                            What is the strategic theme behind agentic AI capabilities in Oracle AI Database?

                                                            A. Removing SQL functionality in favor of REST APIs
                                                            B. Replacing the database with a vector-only system
                                                            C. Selling vector products without database integration
                                                            D. Bringing AI capabilities natively into the database.


                                                            Question #2
                                                            Which statement describes use cases for input guardrails in the OpenAI Agents SDK?

                                                            A. Validating input, detecting unsafe content, and blocking prompt-injection attempts.
                                                            B. Filtering which tools the agent is allowed to call based on user role.
                                                            C. Checking that the agent's final response meets quality and safety thresholds.
                                                            D. Logging all user inputs to an audit trail for compliance reporting.


                                                            Question #3
                                                            Why are docstrings especially important when defining LangChain tools with the @tool decorator?

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


                                                            Question #4
                                                            Which OCI services are used for observability and auditing of deployed AI agents?

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


                                                            Question #5
                                                            Which value associates OCI Responses API requests with a specific OCI Generative AI Project?

                                                            A. Object Storage bucket name
                                                            B. VCN OCID
                                                            C. Project OCID
                                                            D. Tenancy display name


                                                            Solutions:

                                                            Question #1
                                                            Correct Answer: D
                                                            Question #2
                                                            Correct Answer: A
                                                            Question #3
                                                            Correct Answer: D
                                                            Question #4
                                                            Correct Answer: C
                                                            Question #5
                                                            Correct Answer: C

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