What is the plan-act-observe loop?

The plan-act-observe loop is an agent execution pattern in which the agent first creates a plan, performs an action from that plan, observes the result, and then updates or continues the plan.

A simplified cycle is:

Plan → Act → Observe → Replan or Continue

This pattern is useful when a task requires multiple coordinated steps rather than only an immediate reaction.

1. Plan

The agent starts by deciding how it intends to approach the goal.

For example, if the task is:

> Investigate why a deployment failed.

The initial plan might be:

1. Check deployment status.
2. Inspect error logs.
3. Review recent changes.
4. Identify the most likely cause.
5. Prepare a summary.

The plan gives the agent a direction before it begins taking actions.

2. Act

The agent then executes one of the planned steps.

For example:

Planned step: Inspect deployment logs. Action: Call the logging tool.

The agent usually performs one action or a small group of actions before checking the result.

3. Observe

After the action, the agent receives new information.

For example:

Observation: The deployment failed because a required environment variable was missing.

This observation may confirm the current plan or make part of it unnecessary.

4. Replan or continue

The agent compares the new observation with the remaining plan.

It may decide to:

• continue with the next planned step
• skip unnecessary steps
• change the order
• add a new step
• replace part of the plan
• stop because the goal is already complete

For example, if the missing environment variable clearly explains the deployment failure, the agent may not need to investigate several other possible causes.

Why replanning matters

A plan created before execution is based on incomplete information.

As the agent acts, it learns more about the task.

A rigid agent might continue following the original plan even when new evidence makes that plan outdated.

A plan-act-observe agent can adapt.

For example:

Initial plan: Check service A → Check service B → Check database

Observation after service A: Service A is definitely unavailable.

Updated plan: Investigate service A first instead of continuing through every original step.

Example

Suppose an agent is asked:

> Find and book a suitable hotel near my meeting location.

The agent may create this plan:

1. Find nearby hotels.
2. Filter by budget.
3. Check availability.
4. Compare suitable options.
5. Book the selected hotel.

It then acts:

Action: Search nearby hotels.

The observation might be:

> Only two hotels are within the required distance.

The agent updates its plan and continues with those two options instead of evaluating irrelevant hotels.

Plan-act-observe vs. observe-think-act

Both patterns describe iterative agent behavior, but they emphasize different things.

Observe-think-act emphasizes repeatedly understanding the current situation and choosing the next action.

Plan-act-observe emphasizes creating and maintaining a plan across multiple steps.

In practice, an agent may combine both ideas.

For the related pattern, see “What is the observe-think-act loop?”

Does the entire plan need to be fixed in advance?

No.

A useful agent plan is often provisional.

The agent can begin with a high-level plan and refine it as new information appears.

This is especially important when:

• tool results are unpredictable
• information is incomplete
• later steps depend on earlier results
• failures require alternative paths

In short

The plan-act-observe loop is a repeated process in which an AI agent creates a plan, performs an action, observes what happened, and then decides whether to continue or revise the plan.

It helps agents handle multi-step tasks while remaining flexible when new information changes the best path forward.