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Karthik Gokul
Karthik Gokul

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Your “AI Agent” Might Just Be an Automation

AI systems are increasingly being called agents.

But here’s the problem: an AI assistant, an automation workflow, and an autonomous agent can all use the same LLM — while behaving very differently.

The key difference is who decides what happens next.

🤖 1. AI Assistant — Helps You Decide

An assistant responds to what you ask.

You ask → AI responds → You decide

Examples:

  • Summarizing documents
  • Drafting emails
  • Answering questions
  • Recommending next steps

The AI provides intelligence, but the human remains in control of the next action.


⚙️ 2. Automation — Follows a Defined Path

Automation executes a sequence that was designed beforehand.

Trigger
   ↓
Rules
   ↓
Actions
   ↓
Result
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For example:

New support ticket
        ↓
    Classify
        ↓
     Assign
        ↓
 Send notification
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You can add an LLM to parts of this workflow, but if the path is still predetermined, it doesn't necessarily make the system autonomous.


🧠 3. Autonomous Agent — Decides and Adapts

An autonomous agent starts with a goal, evaluates the current situation, chooses an action, observes the result, and can change its approach.

Goal
 ↓
Reason
 ↓
Plan
 ↓
Act
 ↓
Observe
 ↓
Adapt
 ↺
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Imagine telling an agent:

“Resolve this production incident.”

Instead of following one fixed workflow, it could:

→ Investigate logs

→ Check monitoring systems

→ Search relevant documentation

→ Determine the next action

→ Execute an approved operation

→ Observe the result

→ Decide whether another step is needed

That's a fundamentally different execution model.

So what's actually different?

Assistant: helps a human make a decision.

Automation: executes a predefined decision path.

Agent: can make bounded decisions during execution.

And in real-world systems, autonomy doesn't mean unlimited freedom.

Agents still need boundaries around:

  • Permissions
  • Tool access
  • Policies
  • Human approvals
  • Budget limits
  • Auditability
  • Execution safety

That's why I think a better question than:

“Is this an AI agent?”

is:

“What can this system decide when the expected path changes?”

That question tells you much more about whether you're actually building an agent — or just adding an LLM to a workflow.

What do you think is the minimum capability required before a system deserves to be called an AI agent?

AI #AIAgents #AgenticAI #LLM #Automation #SoftwareEngineering #ArtificialIntelligence #DevTools

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