Why Rule Engine 2.0 Feels Like an AI Agent
When you look at Favoriot’s Rule Engine 2.0, you see things that resemble agent behaviour:
- It reacts to events
- It makes decisions using conditions
- It takes action automatically
- It can control devices and talk to other systems
At a glance, that sounds agent-like.
But under the hood, it’s doing something very different.
What Rule Engine 2.0 Actually Is
Rule Engine 2.0 is a deterministic automation system.
That means:
- You explicitly define every step
- Every decision follows fixed logic
- The same input will always produce the same output
- It never “figures things out” on its own
You draw the flow.
You define the conditions.
You decide the actions.
The system executes exactly what you told it to do—no more, no less.
What an AI Agent Is (In Simple Terms)
An AI Agent has qualities that Rule Engine 2.0 intentionally does not.
An AI Agent can:
- Decide what to do next without a fixed flow
- Choose tools dynamically
- Adapt its strategy based on outcomes
- Work toward goals, not just rules
- Operate with partial information
- Learn or adjust behaviour over time
An agent is less like a flowchart and more like a junior engineer you give an objective to.
You say:
“Keep the room comfortable.”
The agent figures out:
- When to check sensors
- Whether to turn on the fan or air-con
- How often to act
- What to do when conditions change
You don’t draw the steps. The agent does.
The Core Difference (This Is the Key Point)
Rule Engine 2.0 answers: “If this happens, what should I do?”
An AI Agent answers: “Given my goal, what should I do next?”
That single shift changes everything.
Why Rule Engine 2.0 Is Not an AI Agent (By Design)
Rule Engine 2.0:
- Has no goals
- Has no memory of past success or failure
- Has no autonomy
- Has no reasoning loop
- Has no learning cycle
It does not:
- Replan
- Reflect
- Retry with a different strategy
- Ask for more information
- Decide which rule to run
It only executes what exists on the canvas.
And that’s a good thing.
Where Rule Engine 2.0 Is Actually Stronger Than Agents
This might sound surprising, but in many IoT systems:
- Predictability matters more than cleverness
- Issues of compliance more than creativity
- Deterministic behaviour matters more than autonomy
Rule Engine 2.0 gives you:
- Clear audit trails
- Repeatable behavior
- Easier debugging
- Safer device control
- Operational trust
In production IoT, that reliability keeps systems alive.
Think of It Like This
I often use this mental image.
- Rule Engine 2.0 is a very precise factory conveyor belt
- AI Agent is a flexible warehouse worker
You don’t want the warehouse worker deciding how fast a conveyor belt should move on its own.
Can Rule Engine 2.0 Be Part of an AI Agent System?
Yes. And this is where things get interesting.
Rule Engine 2.0 is an excellent execution layer for agents.
An AI Agent can:
- Decide what should happen
- Choose which rule to activate
- Adjust parameters dynamically
Rule Engine 2.0 then:
- Executes actions safely
- Controls devices
- Sends alerts
- Stores data
Agent thinks.
Rule Engine acts.
One Last Thought
Rule Engine 2.0 is not an AI Agent.
It is something more humble and more dependable.
It’s the muscle, not the brain.
And in real-world IoT systems, muscles matter a lot more than people realise.
Leave a Reply