How an AI Agent Works

AI assistant moving through Plan, Act and Check stages before human approval.


How an AI Agent Works

The Plan–Act–Check Loop

An ordinary AI conversation often follows a simple pattern: you ask a question and receive an answer.

An AI agent can go further. It may select an action, use an approved tool, inspect the result, and decide what should happen next.

That does not mean an agent should have unlimited freedom. A useful agent operates inside a defined task, approved permissions, review criteria, and stop conditions.

A beginner-friendly way to understand this process is the Plan–Act–Check loop.

THE PLAN–ACT–CHECK LOOP

PLAN → ACT → CHECK → CONTINUE, ESCALATE OR STOP

What Makes an AI System an Agent?

OpenAI describes agents as systems that accomplish tasks on a user's behalf. An agent typically combines:

  • A model that interprets the task and decides what to do next
  • Instructions defining its objective and boundaries
  • Tools for retrieving information or taking actions
  • A loop that continues until an exit condition is reached
  • Guardrails and approval controls

A single AI-generated answer is not necessarily an agent. The important difference is that an agent can manage multiple steps and adjust its next action according to the current state of the task.

Step 1: Plan the Next Useful Action

The planning stage begins with the goal.

The agent should identify:

  • The requested outcome
  • Available information
  • Missing information
  • Permitted tools
  • Constraints and approval requirements
  • The evidence required for completion
  • Conditions requiring escalation

Planning does not always require an elaborate end-to-end strategy. For uncertain work, the safer approach may be to choose one small, reversible next action.

For example, an agent preparing a software comparison might plan to open the three approved official product pages before drafting any conclusions.

Instruction Example
Weak “Research these tools and recommend the best one.”
Controlled “Collect the listed features and published prices from the three approved official pages. Record the source URL and verification date. Do not recommend a purchase.”

The second instruction defines both the action and its boundary.

PLAN = WHAT SHOULD HAPPEN NEXT, WHY, AND WITH WHICH PERMISSION?

Step 2: Act Through an Approved Tool

During the Act stage, the agent performs the selected operation.

Tools might allow an agent to:

  • Search approved websites
  • Read a document
  • Query a database
  • Calculate a result
  • Create a draft
  • Update a record
  • Send a message

These actions do not carry equal risk.

Example Action Control Consideration
Read a public webpage Generally easier to reverse because the agent is retrieving information rather than changing an external system.
Create a draft Review the content before it is published or sent.
Update a customer record Requires appropriate authorization, validation, and potentially human approval.
Send an external message Consider requiring approval before communication leaves the system.
Approve a payment or delete a file Higher-impact actions deserve stronger permissions and explicit approval controls.

Permission matters: An agent should receive only the tools required for its assigned task. Access controls should be enforced by the surrounding system—not merely requested in a prompt.

Record the tool used, the supplied inputs, and the returned result. That evidence becomes important during the Check stage.

Step 3: Check What Happened

The agent now compares the result with explicit acceptance criteria.

It might ask:

  • Did the tool call succeed?
  • Does the result answer the current question?
  • Is the source permitted and relevant?
  • Is required information missing?
  • Does another source conflict with this result?
  • Has the task reached its completion criteria?
  • Is human approval required before continuing?
  • Has a retry, time, cost, or step limit been reached?

“Check” should mean more than asking the same model whether its work looks correct.

Where possible, validation should use observable evidence:

  • A returned status
  • A required field
  • A source link
  • A structured schema
  • A deterministic rule
  • Review by an accountable person

CHECK THE RESULT AGAINST EVIDENCE—NOT JUST CONFIDENCE.

Continue, Escalate, or Stop

After checking the result, the agent needs a controlled exit decision.

Decision When to Use It
Continue Another permitted action is necessary and the current result has passed its required checks.
Escalate Information is missing, sources conflict, authorization is unclear, or a consequential decision requires human judgment.
Stop The goal is complete, safe progress is no longer possible, evidence is unavailable, approval is rejected, or a defined limit has been reached.

Define Stop Conditions in Advance

Stop when:

  • The goal has been met
  • The agent cannot proceed safely
  • Required evidence is unavailable
  • A tool repeatedly fails
  • An approval request is rejected
  • A step, retry, time, or cost limit is reached

A good agent is not defined by how long it can keep working. It is defined partly by whether it knows when it should stop.

PLAN → ACT → CHECK

Evidence supports another step? → CONTINUE
Missing evidence or approval? → ESCALATE
Goal complete or limit reached? → STOP

Example: A Supervised Product-Research Agent

Imagine an agent asked to prepare a factual comparison of three business tools.

Stage Agent Behavior
Plan Identify the required comparison fields and approved official sources.
Act Open one official pricing or documentation page and extract only the requested fields.
Check Confirm that each extracted claim is supported by the page and record the verification date.
Next Decision Continue to the next approved source, escalate a conflict, or stop when the comparison is complete.

If a price is unavailable, the agent should mark it Needs verification instead of guessing.

If two official pages conflict, it should escalate the discrepancy. It should not select a product or purchase a subscription unless an authorized person makes that decision.

Copy-and-Paste Plan–Act–Check Prompt

You are operating as a supervised task agent. Work through a Plan–Act–Check loop. GOAL: [DESCRIBE THE REQUIRED OUTCOME] APPROVED SOURCES AND TOOLS: [LIST THEM] PROHIBITED ACTIONS: [LIST THEM] COMPLETION CRITERIA: [DEFINE SUCCESS] HUMAN APPROVAL REQUIRED BEFORE: [LIST ACTIONS] MAXIMUM STEPS: [ADD LIMIT] MAXIMUM RETRIES PER FAILED ACTION: [ADD LIMIT] For each step: 1. PLAN State the next action, why it is necessary, and which approved tool or source it requires. 2. ACT Perform only that action. Record the tool, input, and result. 3. CHECK Compare the result with the completion criteria and available evidence. Then choose one status: CONTINUE ESCALATE STOP Do not invent missing facts, permissions, successful tool results, or approvals. Escalate conflicting information, unclear authority, and consequential decisions. Stop when the goal is met or any defined limit is reached. Finish with: - A concise action log - Sources used - Unresolved items - Items requiring human review

Data reminder: Never provide confidential, personal, financial, medical, employee, or customer information to an AI system unless that system is explicitly approved for the information involved.

Five AI Agent Mistakes to Avoid

Mistake Better Approach
Giving the agent a vague goal Define an inspectable output and explicit completion criteria.
Providing unnecessary tools Give the agent only the permissions required for the assigned task.
Failing to define the Check stage Specify observable evidence and acceptance criteria before the trial.
Allowing unlimited retries Define retry, step, time, and cost limits where appropriate.
Omitting human approval Keep people responsible for consequential financial, legal, employment, security, medical, and external communication decisions.

Start With a Supervised Agent Trial

Your first agent experiment does not need broad autonomy.

Start with a narrow, preferably read-only task. Define the sources the agent may use, the tools it may access, the evidence it must collect, and the conditions requiring human review.

A Beginner-Friendly First Trial
  1. Choose one narrow task.
  2. Prefer read-only tools.
  3. Specify approved sources.
  4. Define completion criteria.
  5. Set retry and step limits.
  6. Define escalation conditions.
  7. Review the action log yourself.

Conclusion

The Plan–Act–Check loop makes an AI agent easier to understand:

PLAN THE NEXT BOUNDED ACTION.
ACT THROUGH AN APPROVED TOOL.
CHECK THE RESULT AGAINST EVIDENCE.
CONTINUE, ESCALATE OR STOP.

Start with a narrow, read-only task. Limit the tools, define successful completion, and watch every step during the trial.

📥 Plan–Act–Check Agent Trial Checklist + Prompt Sheet

Map your first supervised AI agent experiment before giving the system tools, permissions, or the ability to take multiple actions.

The free resource can include:
  • Plan–Act–Check workflow
  • Agent goal worksheet
  • Approved-tools checklist
  • Permission and prohibited-action checklist
  • Completion-criteria worksheet
  • Human-approval checklist
  • Continue / Escalate / Stop decision sheet
  • Step and retry-limit planner
  • Agent action log template
  • Copy-and-paste Plan–Act–Check prompt
Download the Agent Trial Checklist →

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