LESSON 3.2

Building an agent loop

15:50·16,839 learners
Priya RamanPriya Raman
Next lesson

In this lesson you will

  • Structure the call, execute, feed back cycle
  • Bound the loop with iteration and token limits
  • Log each step so failures can be replayed

An agent is a loop: call the model, run the tool it asked for, feed the result back, repeat. Every loop needs a stopping condition it cannot argue with.

What this lesson covers

  • Structure the call, execute, feed back cycle
  • Bound the loop with iteration and token limits
  • Log each step so failures can be replayed

This lesson sits in Tool Calling and Agents, part of Building AI Apps with LLMs. It assumes what came before it and leads directly into the next lesson in the module.

UP NEXT

3.3 · Guardrails and evaluation

07:18

Building AI Apps with LLMs

58%

Every lesson, searchable to the second.

© 2026 BIBLION

PRIVACY · TERMS · CONTACT