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

  • Exam Code: 1z0-1157-26
  • Exam Name: Agentic AI Foundations Associate
  • Updated: Sep 18, 2026
  • Q & A: 60 Questions and Answers

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Oracle 1z0-1157-26 Exam Syllabus Topics:

SectionObjectives
Topic 1: Implementing Model Context Protocol (MCP)- MCP fundamentals and integration
Topic 2: OCI Enterprise AI Platform- OCI Enterprise AI services overview
- OCI Enterprise AI Agents and Knowledge Bases
Topic 3: Oracle AI Database for Agentic AI- Oracle AI Vector Search
- Agentic AI capabilities in Oracle AI Database
Topic 4: Enterprise Agent Development and Governance- Multi-agent systems and handoffs
- Guardrails, agent tracing and monitoring
- Function calling and tool integration
Topic 5: Building Agents with LangChain and OpenAI Agent Stack- OpenAI Agents SDK usage
- LangChain components and chains
Topic 6: Agent Fundamentals and Reasoning Patterns- Agent reasoning patterns and workflows
- AI agent core concepts and architectures

Oracle Agentic AI Foundations Associate Sample Questions:

Question #1

How do On-Demand serving and Dedicated AI Clusters differ for OCI Enterprise AI Models?

  • A. On-Demand supports only embedding models while Dedicated AI Clusters support generative models.
  • B. Both options use identical infrastructure but are differentiated by pricing and branding only.
  • C. On-Demand doesn't use processors while Dedicated AI Clusters use isolated GPUs for all workloads.
  • D. On-Demand uses shared infrastructure while Dedicated AI Clusters provide isolated GPUs required for custom models.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #2

Why is chunking necessary before generating embeddings for large documents?

  • A. To remove semantic meaning from the document.
  • B. To convert text into SQL-compliant rows.
  • C. To overcome token limits for large documents.
  • D. To automatically encrypt content before indexing.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #3

Which tasks is handled automatically by LangChain when using agent.invoke()?

  • A. Optimizing GPU memory allocation and distributing model inference across hardware accelerators.,,
  • B. Building tool schemas, parsing tool calls, and orchestrating execution loops.
  • C. Training the foundation model from scratch.
  • D. Managing conversation state, formatting API requests, and routing tool execution across the agent loop.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #4

Which approaches are supported by OCI Enterprise AI Agents?

  • A. Build a frontend agent or a backend agent.
  • B. Call the Responses API directly or deploy a hosted agent application.
  • C. Deploy using Python-only or Java-only options.
  • D. Select a free or paid deployment model.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #5

What integration problem does MCP address?

  • A. Latency in cloud-hosted models
  • B. N × M custom-connector problem between AI apps and tools
  • C. Token-limit problem in large language models
  • D. GPU memory fragmentation during inference
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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