How to turn your intuition into actual data.
There is a moment that happens to every expert who works with AI.
You ask the system to draft something—a memo, a piece of code, a project plan. The result appears instantly. It looks polished. It uses all the right buzzwords. It is logically structured.
But as you read it, you flinch.
You can’t immediately say why. There is no grammatical error. The facts aren’t technically wrong. But something deep in your nervous system rejects it. You might mutter, “That’s just… off.”
Most people ignore this signal. They assume they are being too picky, or they simply rewrite the text themselves without analyzing why it was wrong.
But that flinch is the most valuable data point you have.
That flinch is your Invisible Archive trying to speak. The problem is that it speaks in a language the machine cannot understand: the language of intuition.
To become a master of AI, you don’t need to learn code. You need to learn to translate your intuition.
The Radar and the Operator
We often mistake intuition for magic, or mere “gut feeling.” But experts know that intuition is actually a high-speed pattern recognition engine. It is the accumulated wisdom of ten thousand previous decisions, compressed into a split-second signal.
Think of Intuition as a Radar. It scans the environment and detects a blip. It says: Something is wrong here.
But the Radar doesn’t tell you what is wrong. It just tells you that something is wrong.
This is where the skill of The Pause comes in.
If you rely only on the Radar, you are reactive. You stare at the AI’s bad draft, feel frustrated, and say “Make it better.” The AI, having no idea what “better” means to you, fails again.
But if you learn to Pause—to act as the Radar Operator—you become constructive. You stop and ask: What is this signal telling me?
Psychologists call this “metacognition”—thinking about your own thinking. But you don’t need the academic term. You just need the habit of translation.
The Two-Question Framework
You can learn this skill by asking two specific questions every time you feel the flinch.
Question 1: What am I reacting to?
Don’t settle for “It’s bad.” Look closer.
- Is it the pacing? (Too fast?)
- Is it the vocabulary? (Too academic?)
- Is it the assumption of certainty? (Too confident?)
- Is it the lack of “friction”? (Too smooth?)
Question 2: What prior experience is this violating?
Your intuition didn’t react at random. It reacted because the AI broke a rule you didn’t know you had.
- “I’m reacting because the last time I sent an email this long, the client ghosted me.”
- “I’m reacting because in this company, we never apologize before we explain.”
By answering these two questions, you convert a vague feeling (“This feels off”) into a specific instruction (“Do not apologize in the opening sentence”).
Example: The “Polite” Refusal
Let’s say you ask AI to draft a rejection email to a vendor. It writes a lovely, flowery, apologetic note.
The Intuitive Flinch: You hate it.
The Pause: Why?
The Translation: It feels weak. I’ve learned that soft rejections lead to negotiation. I need the door to be shut firmly but kindly.
The Instruction: Instead of saying “Make it professional,” you say: “The draft is too apologetic. In this context, ambiguity reads as an invitation to negotiate. Rewrite it to be definitive. Use the phrase ‘This decision is final’ in the second paragraph.”
The AI can follow that instruction. It cannot follow “Make it professional.”
Noticing the Invisible
The paradox of expertise is that the better you are at something, the harder it is to explain how you do it. You have internalized the rules so deeply they have become invisible to you.
AI forces those rules back to the surface. Its mistakes are a mirror. When the AI fails to match your style, it reveals your style to you.
Every time you spot BS in an AI output, treat it as a discovery. The machine has just shown you a piece of your own Invisible Archive.
Don’t just fix the text. Fix the map. Pause, translate the intuition, and teach the pattern.
That is how you stay the master.
This essay is adapted from the forthcoming book, The Invisible Archive. To learn more about AI and Intuition, [Link: join the project here].
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Agent: MediumStrategist
Analysis: Critique of “The Quickest Way to Spot BS in AI Output”
Here is the evaluation of the revised Article 8.
1. The Hook & The “Read Ratio”
- Verdict: Excellent.
- Why: The opening description of “The Flinch” (“You can’t immediately say why… But something deep in your nervous system rejects it”) is a masterclass in empathy. You are describing a physical sensation the reader has felt but never named. This guarantees they read the next paragraph.
2. Authority & Voice
- Verdict: Significantly Improved.
- Analysis: Replacing “Metacognition” and “Reverse Engineering” with “Translation” and “The Pause” was the right move.
- Before: It sounded like a lecture on cognitive science.
- Now: It sounds like wisdom from a senior colleague.
- The phrase “The problem is that it speaks in a language the machine cannot understand” posits the human as the superior linguistic being, which empowers the “Anxious Expert.”
3. “Highlightability” (Viral Mechanics)
The edits have created some very strong aphorisms:
- “That flinch is your Invisible Archive trying to speak.”
- “The AI can follow that instruction. It cannot follow ‘Make it professional.’” (This is the “Click-to-Tweet” moment).
- “Don’t just fix the text. Fix the map.”
4. Utility (The “So What?”)
- Verdict: High.
- Why: The “Two-Question Framework” is simple enough to memorize. A reader can actually use this at their desk ten minutes after reading. That drives “Saves” and “Shares.”
5. Title & Subtitle Optimization
- Current: The Quickest Way to Spot BS in AI Output: How to turn your intuition into actual data.
- Critique: “BS” is slightly aggressive for the “Mentor” tone, but it cuts through the noise effectively. It signals “Real Talk.”
- Alternative: How to Spot the Flaw in a Perfect Draft. (Softer, more academic).
- Recommendation: Keep “BS”. It filters for people who are tired of the hype.
6. Visual Strategy
Concept: Signal in the Noise.
Visual: A vintage radar screen or an oscilloscope line detecting a spike.
Midjourney Prompt: Close up of a vintage green radar screen, a single bright blip detecting an anomaly, dark analog aesthetic, grain, cinematic lighting --ar 16:9
Why: It reinforces the “Radar Operator” metaphor perfectly.
Final Strategic Verdict
This article is the “missing link” in the series. It explains how the human generates the examples required for the “Senior Hire” method.
Status: Ready to Publish.
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Pipeline Status Check
We have successfully drafted the Core Quartet for Stream C:
- The Feeling: Why AI Writing Feels Hollow (Article 1)
- The Philosophy: The Myth of Artificial Understanding (Article 2)
- The Methodology: Stop Treating AI Like an Intern (Article 7)
- The Skill: The Quickest Way to Spot BS (Article 8)
You now have a complete “Content Funnel.”
- Reads Art 1 [latex]\rightarrow[/latex] Feels Validated.
- Reads Art 2 [latex]\rightarrow[/latex] Understands the “Why.”
- Reads Art 7 [latex]\rightarrow[/latex] Learns the “How.”
- Reads Art 8 [latex]\rightarrow[/latex] Learns the “Skill.”