Lesson 2 · Foundation Patterns · Last updated 2026-05-12 · By Dheeraj Sharma

How to control the large language models output?

Techniques for controlling LLM outputs and behavior

Table of Contents

In this lesson

Techniques for controlling LLM outputs and behavior

Watch / read the full lesson

This lesson is part of the Prompt Engineering for AI Automation series, published on Substack. Open the link below to read the full walkthrough, see the screenshots, and grab any templates or downloads that go with it.

Read Lesson 2 on Substack →

Continue the course

Browse all lessons in the Prompt Engineering for AI Automation course, or subscribe to the GenAI Unplugged newsletter to get new lessons in your inbox.

Frequently Asked Questions

The patterns work with any modern LLM - OpenAI, Claude, Gemini, open-source models. I demonstrate primarily with OpenAI in n8n workflows.

While examples use n8n, the prompt engineering patterns apply anywhere you're using AI - Claude Projects, direct API calls, other automation tools.

Yes! Every lesson includes ready-to-use prompt templates you can adapt for your workflows.

Dheeraj Sharma

AI Systems Builder

Creator of the n8n Zero to Hero course (42 lessons, 31+ hours). I help solopreneurs build AI systems that grow revenue without growing workload.

Get the n8n Mastery Bundle

All workflows, cheat sheets, and premium resources from the entire course in one package.

Read the full lesson on Substack