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100% Oracle 1z0-1157-26 Guaranteed Success With Testing Engine

Exam Code: 1z0-1157-26

Exam Name: Agentic AI Foundations Associate

Updated: Sep 12, 2026

Number: 60 Q&As with Testing Engine

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Oracle 1z0-1157-26 Exam Overview:

Certification Vendor:Oracle
Exam Name:Agentic AI Foundations Associate
Exam Number:1Z0-1157-26
Real Exam Qty:40
Passing Score:65%
Exam Duration:60 minutes
Exam Format:Multiple Choice
Available Languages:Japanese, English
Related Certifications:Agentic AI Certified Foundations Associate
Exam Price:Free
Sample Questions:Oracle 1z0-1157-26 Sample Questions
Exam Way:Online certification exam
Pre Condition:No formal prerequisite exam is stated. Oracle recommends basic knowledge of LLM concepts, practical Python knowledge, and basic Oracle Cloud Infrastructure knowledge.
Official Syllabus URL:https://www.oracle.com/education/certification/

Oracle 1z0-1157-26 Exam Syllabus Topics:

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

                                                                Oracle Agentic AI Foundations Associate Sample Questions:

                                                                Question #1

                                                                Which three model categories are available through OCI Enterprise AI Models?

                                                                A. SQL, NoSQL, and Graph models.
                                                                B. Chat models, Embed models, and Rerank models.
                                                                C. Robotics, Audio, and Vision models.
                                                                D. Forecasting, Clustering, and Regression models.


                                                                Question #2

                                                                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 tell the LLM when and how to use the tool.
                                                                D. They encrypt tool arguments before execution.


                                                                Question #3

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

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


                                                                Question #4

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

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


                                                                Question #5

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

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


                                                                Solutions:

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

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