The Learning Prompt Engineering Blog
Practical articles on how AI models process prompts, methods that often improve your results, and how those techniques hold up in real tasks. Organized into three areas — getting started, techniques, and real-world use — so you can start wherever’s useful to you.
What's New
Fresh content across all three topic areas — published on a rolling schedule.
How to Structure a Text-to-Image Prompt from Scratch
A step-by-step walkthrough of the five-component text-to-image prompt structure: subject, style, lighting, mood, and aspect ratio — with a fully labeled example.
GPT Image vs Nano Banana 2 vs Kling vs Veo 3.1: A Visual AI Tool Guide
Compares four visual AI tools — GPT Image, Nano Banana 2, Kling, and Veo 3.1 — across prompt sensitivity, best-use contexts, style defaults, and key limitations to help practitioners choose the right tool.
How to Use Prompt Modifiers to Control Visual Output
A practical guide to the five core modifier types — subject, style, lighting, mood, and aspect ratio — and how stacking them shapes AI image results.
Visual AI Prompting: Why It’s Different from Text
Learn why visual AI prompting requires a different skill set than text prompting and what that means for how you write your first image prompts.
3 Common AI Content Mistakes and How to Fix Them
ai content creation mistakes, content prompt errors, brand voice missing, ai publishing review, prompt iteration content
Brand Voice vs. Generic Output: A Side-by-Side Comparison
Introduction You have probably seen this scenario before. A marketer sits down, types a quick request into an AI tool, and gets back a draft that reads like it could belong to any company in any industry. The tone is neutral, the phrasing is safe, and the output is...
Getting Started
New to prompt engineering? This is where you begin. You'll learn what prompts actually are, how AI models process them, and the foundational concepts that make everything else click.
How to Structure a Text-to-Image Prompt from Scratch
A step-by-step walkthrough of the five-component text-to-image prompt structure: subject, style, lighting, mood, and aspect ratio — with a fully labeled example.
GPT Image vs Nano Banana 2 vs Kling vs Veo 3.1: A Visual AI Tool Guide
Compares four visual AI tools — GPT Image, Nano Banana 2, Kling, and Veo 3.1 — across prompt sensitivity, best-use contexts, style defaults, and key limitations to help practitioners choose the right tool.
How to Use Prompt Modifiers to Control Visual Output
A practical guide to the five core modifier types — subject, style, lighting, mood, and aspect ratio — and how stacking them shapes AI image results.
Visual AI Prompting: Why It’s Different from Text
Learn why visual AI prompting requires a different skill set than text prompting and what that means for how you write your first image prompts.
3 Common AI Content Mistakes and How to Fix Them
ai content creation mistakes, content prompt errors, brand voice missing, ai publishing review, prompt iteration content
Brand Voice vs. Generic Output: A Side-by-Side Comparison
Introduction You have probably seen this scenario before. A marketer sits down, types a quick request into an AI tool, and gets back a draft that reads like it could belong to any company in any industry. The tone is neutral, the phrasing is safe, and the output is...
Prompt Techniques
Practical methods for writing better prompts. Zero-shot, few-shot, the seven-element framework, iterative refinement, A/B testing — each one explained clearly with examples you can apply right away.
How to Structure a Text-to-Image Prompt from Scratch
A step-by-step walkthrough of the five-component text-to-image prompt structure: subject, style, lighting, mood, and aspect ratio — with a fully labeled example.
GPT Image vs Nano Banana 2 vs Kling vs Veo 3.1: A Visual AI Tool Guide
Compares four visual AI tools — GPT Image, Nano Banana 2, Kling, and Veo 3.1 — across prompt sensitivity, best-use contexts, style defaults, and key limitations to help practitioners choose the right tool.
How to Use Prompt Modifiers to Control Visual Output
A practical guide to the five core modifier types — subject, style, lighting, mood, and aspect ratio — and how stacking them shapes AI image results.
Visual AI Prompting: Why It’s Different from Text
Learn why visual AI prompting requires a different skill set than text prompting and what that means for how you write your first image prompts.
3 Common AI Content Mistakes and How to Fix Them
ai content creation mistakes, content prompt errors, brand voice missing, ai publishing review, prompt iteration content
Brand Voice vs. Generic Output: A Side-by-Side Comparison
Introduction You have probably seen this scenario before. A marketer sits down, types a quick request into an AI tool, and gets back a draft that reads like it could belong to any company in any industry. The tone is neutral, the phrasing is safe, and the output is...
Real World Use
Prompt engineering applied to real work — content creation, business automation, professional workflows, and visual tools. The focus here is practical: what to prompt, how to structure it, and what to do when the output needs work.
How to Structure a Text-to-Image Prompt from Scratch
A step-by-step walkthrough of the five-component text-to-image prompt structure: subject, style, lighting, mood, and aspect ratio — with a fully labeled example.
GPT Image vs Nano Banana 2 vs Kling vs Veo 3.1: A Visual AI Tool Guide
Compares four visual AI tools — GPT Image, Nano Banana 2, Kling, and Veo 3.1 — across prompt sensitivity, best-use contexts, style defaults, and key limitations to help practitioners choose the right tool.
How to Use Prompt Modifiers to Control Visual Output
A practical guide to the five core modifier types — subject, style, lighting, mood, and aspect ratio — and how stacking them shapes AI image results.
Visual AI Prompting: Why It’s Different from Text
Learn why visual AI prompting requires a different skill set than text prompting and what that means for how you write your first image prompts.
3 Common AI Content Mistakes and How to Fix Them
ai content creation mistakes, content prompt errors, brand voice missing, ai publishing review, prompt iteration content
Brand Voice vs. Generic Output: A Side-by-Side Comparison
Introduction You have probably seen this scenario before. A marketer sits down, types a quick request into an AI tool, and gets back a draft that reads like it could belong to any company in any industry. The tone is neutral, the phrasing is safe, and the output is...