How AI Agents Work

Every agent, regardless of framework, runs some version of the same loop: reason about the current state, decide on an action, execute it safely, observe the result, and repeat until done.

The Agent Loop, Step by Step

Goal
 ↓
Context (goal + conversation history + prior results)
 ↓
LLM reasoning/decision  → "What should happen next?"
 ↓
Tool selection           → LLM picks a tool + arguments
 ↓
Application validation   → is this tool call allowed? are arguments valid?
 ↓
Tool execution           → the actual function/API call runs
 ↓
Observation              → the tool's result is read back
 ↓
State update              → history/context updated with the new information
 ↓
Next action OR final response

The "application validation" step is not optional in a well-built system — the LLM's chosen tool call is a request, not a command that should execute unchecked. See Tool Validation.

Worked Example

User: "What's the total of my last 3 orders?"

Iteration 1:
  LLM decides: call get_recent_orders(user_id=42, limit=3)
  App validates: user_id matches authenticated session ✓
  Tool runs → returns [{"id": 101, "total": 450}, {"id": 102, "total": 300}, {"id": 103, "total": 275}]
  Observation added to context

Iteration 2:
  LLM decides: it now has enough information — no more tools needed
  LLM generates final answer: "Your last 3 orders total ₹1,025."

Why the Loop Terminates

A well-built agent stops when the LLM determines the goal is satisfied and returns a final answer instead of another tool call — but production systems also enforce a hard maximum iteration count as a safety net, since a model can occasionally get stuck repeating similar tool calls. See Infinite Agent Loops.

Common Mistakes

• Executing tool calls directly from the LLM's output with no validation layer — a missing safety step, not a minor detail
• No maximum iteration limit, risking a runaway loop that burns cost and time with no progress
• Not persisting intermediate state, so a crash mid-loop loses all progress instead of allowing resumption

Interview Relevance

Expect to be asked to draw or describe this loop from memory in an agentic AI interview — and to explain specifically why the validation step sits between "LLM decides" and "tool executes," not before or after.

Practice Question

Walk through the agent loop for a task: "Cancel my subscription and email me a confirmation." Where would you insert a human-approval step, and why?

Related Notes

• AI Agent Architecture
• Agent Loop
• Tool Validation