Sunday, October 25, 2026

The DBA’s Guide to Oracle Agentic AI Foundations (AI agent basics)

What Is an AI Agent? Explained Like a DBA on Night Shift

The DBA's Guide to Oracle Agentic AI Foundations · Part 1 of 6

What Is an AI Agent? Explained Like a DBA on Night Shift

Oracle Agentic AI Foundations Associate (1Z0-1157-26) exam prep · ~6 min read

An AI agent is an LLM that doesn't just answer, it works: it plans, uses tools, checks results, and keeps going until the job is done.

The night-shift analogy

Imagine two people on your on-call rota.

The first only answers questions. You ask "What does ORA-01555 mean?" and they explain snapshot too old. Useful, but they never touch the database. That's a plain LLM.

The second gets an alert: "Tablespace USERS is 95% full." They check free space, look at what's growing, add a datafile, verify, and update the ticket. Nobody told them each step. They decided. That's an AI agent.

The five parts of every agent

Think of the second DBA again:

  1. Model (LLM) – their brain. It reasons and decides.
  2. Instructions – the runbook and rules: "Never drop objects in production."
  3. Tools – SQL*Plus, OEM, the ticketing system. Without tools, the brain can't act.
  4. Memory – what happened earlier tonight (short-term) and lessons from past incidents (long-term).
  5. Planning – breaking "fix the tablespace" into small steps.
Exam hook: M-I-T-M-P – "My Instructions Tell Me Plans." Model, Instructions, Tools, Memory, Planning.

The agent loop

Every agent runs the same loop: Perceive → Reason → Act → Observe → Repeat. It stops when the goal is met or a limit is reached.

One point people miss: the LLM never runs the tool itself. It says "call check_tablespace with name=USERS" as structured JSON. Your application runs it and hands back the result. This is function calling.

Agent or workflow?

If the steps are always the same (export, compress, copy), that's a workflow: code decides the order. If the path depends on what it finds, that's an agent: the LLM decides. Exam questions love this difference.

Autonomy is a dial: human-in-the-loop (approves each step), human-on-the-loop (watches, can stop it), or fully autonomous.

Remember for the exam

  • Agent = LLM + instructions + tools + memory + planning, in a loop.
  • The app executes tools; the LLM only requests them.
  • Fixed steps = workflow. LLM chooses steps = agent.
  • Grounding with real data (tools, RAG) reduces hallucination.

Self-check

  1. Who executes a tool call: the LLM or the application? (Application)
  2. A process that always runs the same 4 steps in order is a…? (Workflow)
  3. Name the five agent components. (Model, instructions, tools, memory, planning)

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