Most prompting advice focuses on structure. Templates. Formats. Roles. Those matter. But they're surface mechanics. The real skill is what you think about BEFORE you write the prompt. Second-Order Thinking is one framework. There are dozens more from investing, military
@godofprompt
-
Three-question prompt review to anticipate model outputs
By
–
The method is three questions. Use them before you hit send on any prompt. 1. "What's the most obvious output I'll get from this?" 2. "What happens after that output gets implemented?" 3. "What second and third-order effects should the model account for?" Add questions 2 and
-
AI models are literal first-order thinkers
By
–
AI models are first-order thinkers by default. You ask a question, they answer it. Directly. Literally. Without considering what happens next. That's not a flaw. That's how they work. The model responds to exactly what you give it. So if your prompt doesn't include the second
-
Ask the follow-up: improve generic AI outputs
By
–
"Why does my AI output sound so generic?" Because you're prompting at the surface. You ask for a strategy, AI gives you one, you move on. You never ask "and then what happens?" That one missing question separates average AI work from exceptional. And it has a name.
-
Pope Issues Major Encyclical Focused on AI
By
–
Some people calling this a declaration of war on AI. It's not. I read it. Pope Leo XIV just released "Magnifica Humanitas." 42,300 words. His first encyclical. The most authoritative document a pope can issue. Entirely focused on AI. He signed it on the 135th anniversary of
-
Prompt engineering challenge: multi-format conversion
By
–
Challenge 6: The Format Switcher Give them a single paragraph from a blog post. Ask them to convert it into three formats in one prompt: a tweet, a LinkedIn post, and a cold email subject line. One prompt. Three distinct outputs. Do they specify each format's constraints
-
Using AI Hallucinations to Test Candidate Review Skills
By
–
Challenge 4: The Hallucination Trap Before the interview, generate an AI output about a topic relevant to the role. Leave 2-3 subtle factual errors in it. Realistic-sounding but wrong. Hand it to the freelancer. Ask them to review it. Do they catch the errors without being
-
Prompt-engineering iteration exercise for improving AI outputs
By
–
Challenge 3: The Iteration Loop Run a basic prompt that produces a generic, C-minus output. Show it to them on screen. Ask them to make it better using only follow-up prompts. No rewriting by hand. What to watch for: Do they give specific direction ("tighten the intro to one
-
Improving a Prompt: The Constraint Architect
By
–
Challenge 2: The Constraint Architect Hand them this prompt and ask them to improve it before running it: "Write a blog post about marketing." Then count. How many constraints do they add? Audience. Word count. Tone. Structure. Examples. Output format. Point of view. What to
-
Cold Start Prompting Test for AI Assistants
By
–
Challenge 1: The Cold Start Test Give them this brief and nothing else: "Write me a landing page for my product." No context, audience, tone. Not even constraints. Now watch. Do they paste it straight into Claude or do they ask you 3-5 clarifying questions first? A skilled