what actually makes a system agentic?

Hemantkumargiri — Sat, 08 Aug 2026 02:17:44 +0000

LLM + Tools ≠ Agent

I used to think an AI agent was simply:

LLM + tools = Agent

After exploring agentic system design, I’m starting to see it differently.

The LLM is only one component.

The real engineering challenge is designing the execution loop around it.

A basic LLM application looks like:

"Input → LLM → Response"

An agentic system looks more like:

"Goal → Reason → Act → Observe → Reason → Act → ... → Done"

For example:

Receive a user request
Understand the goal
Determine what information is required
Select the appropriate tool
Execute the tool
Inspect the result
Decide the next action
Retry, change strategy, or escalate if required
Stop when the goal is achieved

This introduces problems that are very familiar to software engineers:

State management
Tool selection
Error handling
Retries and timeouts
Guardrails
Termination conditions
Human-in-the-loop
Observability and tracing

So I'm beginning to think that reliable agent development is not primarily a prompt-engineering problem.

It is a system-design problem with an LLM inside the system.

The question I'm exploring now is:

«How do we design the execution loop so an agent can reason and act without becoming unpredictable?»

For developers building agents in production, what has been the hardest part for you: reasoning, tool orchestration, memory/state, or controlling the execution loop?

DEV Community: Hemantkumargiri

what actually makes a system agentic?