The agent thinking loop, explained in simple language
This is the loop that makes an agent feel alive.
I think there is confusion about how agents actually think.
Some imagine complex logic.
Others think it is one giant model doing everything in one go.
Most explanations jump straight into diagrams.
Or long technical code.
Or patterns that only make sense if you already know the topic.
In this episode, we focus on how the agent thinks, step by step.
No heavy theory.
No complicated design patterns.
By the end of this, you will understand the thinking loop behind every agent, why it matters, and how this simple cycle powers almost everything an agent can do.
This is it.
Let’s get into it.
The agent thinking loop
This loop is the process of modern agentic systems.
Every useful agent follows it.
Nothing works without it.
Here are the five steps, explained in simple terms.
1. Observe
The agent looks at what is happening right now.
This could be:
• a document
• a webpage
• an inbox
• a database entry
• the result from the last step
It is the agent saying,
“What is the situation right now?”
3. Act
The agent does something.
It might:
• call a tool
• fetch data
• write to a file
• trigger an API
• update its memory
• transform content
This is why tools matter.
Talking is nothing without action.
4. Reflect
After each action, the agent checks the result.
It asks:
• Did that work
• Did I move closer to the goal
• Do I need to adjust
• Did something fail
Reflection stops bad loops.
It helps the agent recover when something goes wrong.
5. Repeat
The loop runs again.
Observe.
Think.
Act.
Reflect.
And again.
And again.
Until the task is done or the agent hits a limit.
This loop gives agents momentum.
It turns small steps into real progress.
A simple example
Goal: clean up my task list for today.
Observe: read the list
Think: decide what counts as important
Act: sort tasks into buckets
Reflect: check if the buckets make sense
Repeat: refine until the list looks right
Nothing fancy.
Just a small loop done properly.
Why the loop matters
Because without it, you do not have an agent.
You have a single reply.
Or a prompt.
Or a thin wrapper around a model.
The loop is what makes an agent:
✓ adaptable
✓ able to fix its own mistakes
✓ capable of multi-step work
✓ responsive to changing information
✓ useful inside real business tasks
Once you understand this loop, everything else becomes easier.
Save this.
You will use it again and again.
Up Next
How to give an agent a goal, it can actually follow.
In the next episode in this series, you will learn the right way to write goals so the agent can understand the task and take the right actions from the start.
Tip: Find this helpful? Subscribe to get new episodes automatically.