We’ve been told to treat AI like a machine to be hacked, a servant to be commanded, or an expert to be mimicked. What if we treated it with radical honesty instead?

Rethinking Mark Manson’s Models for the AI era is an interesting exercise. At its core, Models argues that true attraction doesn’t come from cheesy pickup lines, manipulation, or trying to game the system; it comes from non-neediness, radical honesty, and vulnerability.

If you treat AI like a traditional pickup artist treats dating—using rigid, “magical” prompt hacks, trying to game the algorithm, or blindly relying on it for validation—you get superficial, robotic results. But if you approach AI with the core tenets of Models, you unlock a highly productive, authentic workflow.

Here is how to rethink the core concepts of the book for working and living with AI.

1. Non-Neediness (The Human-in-the-Loop Principal)

In Models, neediness is defined as being more invested in what others think of you than what you think of yourself.

With AI, neediness looks like intellectual dependency. It’s copy-pasting an AI’s output into an email or code repository without reviewing it, or letting a chatbot dictate your business strategy because you’re too intimidated to make the call yourself.

The Non-Needy AI User: You hold your own ground. You value your own critical thinking and domain expertise more than the AI’s smooth-sounding, confident output. You use AI to augment your thoughts, not to replace your brain.

2. Radical Honesty & Vulnerability (How You Prompt)

Manson argues that vulnerability is a form of power—admitting your flaws and desires openly cuts through the noise.

In the AI world, people often waste hours trying to craft the “perfect, professional prompt” because they are afraid of looking foolish or messy. Vulnerability with AI means stripping away the corporate fluff and admitting exactly what you don’t know.

Instead of prompting: “Act as an expert data analyst and optimize this workflow,” Try the honest approach: “I have zero experience with SQL, I’m incredibly stressed about a 4:00 PM deadline, and my data is a complete mess. Here is the raw text. Help me fix just the first step.”

By giving the AI the raw, unvarnished truth of your situation, constraints, and ignorance, it can tailor its persona and output to what you actually need, rather than what you think you should ask.

3. Screening (Filtering Outputs and Tools)

In dating, Manson suggests “screening” women quickly to see if they are a good match, rather than trying to please everyone.

With AI, you must ruthlessly screen both the tools you use and the content they generate.

• Screening the Model: Don’t try to force a creative writing model to do heavy statistical analysis. Know when to stick with a tool and when to walk away.
• Screening the Output: If an AI gives you a hallucinated, garbage answer, don’t spend an hour politely arguing with it to fix it. Screen it out. Delete the chat, adjust your core constraints, or switch to a different model.

Models Core Concept	Original Meaning (Dating)	The AI Adaptation (Work & Life)
Groundedness	Being secure in your own skin and values.	Having a strong foundational knowledge of your work so you can spot AI hallucinations instantly.
The Friction Theory	Overcoming anxiety and external roadblocks to connect.	Overcoming the tech friction (setting up APIs, learning UI, managing information overload).
Demographics	Finding the right group of people who share your values.	Matching the right AI model/agent architecture to your specific daily lifestyle or industry.
Rejection	A healthy filtering mechanism to save time.	Accepting that an LLM will occasionally fail, break, or give a bad output—and moving on without frustration.

An “attractive” AI collaborator doesn’t rely on tricks. They don’t download 50-page PDFs of “Secret Prompts to Get Rich.” Instead, they treat the AI as a highly capable peer. They communicate with absolute clarity, express their true intent without shame, establish firm boundaries on what tasks they will hand over, and fiercely protect their own unique human perspective.

Undertaking the challenge to do Authentic Prompting.

When you prompt out of “neediness,” you try to control the AI through rigid tricks, hidden contexts, and over-engineering. When you prompt with “vulnerability,” you state your exact situation, your current limitations, and your true intent.

The Anatomy of the Two Styles

The Needy / Tactical Style

• The Mindset:“If I don’t use the exact magical buzzwords, the AI will give me garbage. I must trick it into being smart.”
• The Tells:Overusing personas (“Act as a world-class expert…”), piling on generic constraints (“Make it viral, engaging, and professional”), and hiding your actual skill level.
• The Result:Generic, hyper-polished corporate fluff that lacks soul and misses your actual goal.

The Honest / Vulnerable Style

• The Mindset:“Here is exactly where I am stuck, here is what I know, and here is where I am completely drowning. Let’s solve this specific piece together.”
• The Tells:Admitting confusion, specifying emotional or time constraints, providing raw/imperfect examples, and asking for collaboration rather than a finished miracle.
• The Result:Highly tailored, deeply contextual outputs that actually cut down your workload.

Practical Scenarios in Action

Scenario 1: Tackling Project Overwhelm

You are staring at a massive project scope (like a long guide or an intensive strategy) and you don’t even know where to start.

• The Needy / Tactical Prompt:“Act as a premium business consultant. Write a comprehensive, 10-chapter outline for a digital marketing e-book that guarantees high conversions and covers all social platforms perfectly.”
  • Why it fails: It forces the AI to generate a massive, generic template. It doesn’t solve your actual overwhelm; it just gives you a longer to-do list of generic ideas.
• The Honest / Vulnerable Prompt:“I am trying to outline a long business e-book about community growth, but I am completely drowning in my own notes and feeling overwhelmed by the scope. Let’s ignore the big picture for a minute. I want to start just with Chapter 1, which is about organic engagement. Here is a messy brain-dump of my core ideas: [Insert raw notes]. Help me organize just this onechapter into a logical, 3-step flow that feels approachable to write.”

Scenario 2: Content Creation & Writing

You need to write a post, email, or caption, but your brain is fried and you’re out of ideas.

• The Needy / Tactical Prompt:“Write a viral, highly engaging social media post about vintage style trends. Use psychological hooks, emojis, and a call to action to maximize comments.”
  • Why it fails: You are asking the AI to use “pickup lines” on your audience. The result will sound like an aggressive late-night infomercial or a generic marketing bot.
• The Honest / Vulnerable Prompt:“I run a community focused on retro aesthetics, and I need to write a post for them. Honestly, my brain is fried today and I feel like I’m recycling the same three talking points. I want to give them something that feels warm and authentic, not like a sales pitch. Here is a quick description of a trend I love: [Trend details]. Give me three different conversational angles to start a genuine discussion in the comments.”

Scenario 3: Facing a Technical Roadblock

You are dealing with a software feature, design tool, or spreadsheet formula that you don’t fully understand.

• The Needy / Tactical Prompt:“Generate an advanced, bulletproof automated workflow formula for tracking inventory margins across multiple dynamic sheets.”
  • Why it fails:You’re hiding your lack of knowledge behind big words. The AI will give you an incredibly complex solution that you won’t know how to fix or debug when it inevitably errors out.
• The Honest / Vulnerable Prompt:“I am trying to set up a sheet to track inventory and profit margins, but spreadsheets honestly stress me out and my current layout is a bit chaotic. I don’t need anything fancy or advanced—just a simple, clear formula to calculate profit without breaking my columns if I add new rows. Here is how my columns look right now: [A: Item, B: Cost, C: Price]. Walk me through where to paste the formula like I’m a beginner.”

The Three Rules of Authentic Prompting

1. Drop the Mask:If you don’t know what a term means, say so. If your data is a total mess, admit it. The AI doesn’t judge you; it adapts to your baseline.
2. Isolate the Friction:Instead of asking the AI to build Rome in one prompt, tell it exactly where youare bottlenecked right now (e.g., “I have the ideas, but my tone sounds too stiff,” or “I have the data, but I don’t know how to visualize it”).
3. Own the Final Call:Treat the AI’s first response as a rough draft from a colleague. Correct it openly: “That first point feels a little too corporate. Let’s make it sound more down-to-earth, like a friend giving advice.”

We are living through one of the greatest “outsourcing” moments in human history.

With a few keystrokes, artificial intelligence can now help write our emails, organize our schedules, generate ideas, summarize research, and even make decisions for us. Used thoughtfully, these tools can be incredibly helpful. But cognitive scientists and educators are increasingly recognizing an important distinction: AI can either act as a scaffold that supports our thinking, or as a surrogate that replaces it entirely.

That difference matters more than most people realize.

When we consistently outsource difficult mental work to automated systems, we also reduce the kinds of cognitive effort that help keep the brain adaptable, resilient, and engaged over time. The issue is not technology itself. The issue is what happens when convenience quietly removes the healthy mental friction our brains actually need.

Psychologists use the term “desirable difficulties” to describe challenges that make learning or problem-solving harder in the short term but far more beneficial in the long term. Effortful recall, experimentation, planning, troubleshooting, and creative decision-making all force the brain to actively construct knowledge instead of passively receiving it. In other words, struggle is not always a flaw in the process. Sometimes the struggle is the process.

Research suggests that when we rely too heavily on automation for thinking tasks, we risk reducing deep cognitive engagement. We begin spending more time verifying outputs than generating original thought ourselves. Information is increasingly stored externally, which can weaken memory formation and reduce opportunities for synthesis, reflection, and independent reasoning. Much like muscles weaken from disuse, mental skills can soften when they are rarely exercised.

This does not mean everyone needs to start a side business or become an entrepreneur. The deeper point is not commerce, it is engagement.

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A personal business simply happens to combine many cognitively rich activities at once: problem-solving, creativity, social interaction, planning, physical movement, adaptability, and emotional investment. But many deeply immersive hobbies can create similar benefits when they actively challenge the mind and involve meaningful participation rather than passive consumption.

Restoring vintage cars, woodworking, gardening, painting, sewing, photography, playing music, collecting antiques, designing miniatures, rebuilding cameras, writing, cooking elaborate meals, or even running a highly engaged community group can all demand sustained attention, creativity, learning, and real-world problem-solving.

The common thread is not productivity for profit. It is active engagement with complexity.

The brain appears to benefit most when we move beyond passive consumption and into activities that require us to think, adapt, create, and interact with the physical and social world around us.

People often talk about crossword puzzles or brain games as ways to stay mentally sharp, and while those activities certainly have value, they are often relatively closed systems with predictable rules and limited complexity. Deeply engaging creative pursuits are something entirely different. Whether you manage a vintage booth, restore old cameras, curate collections, stage displays, garden, paint, or build furniture, you are constantly engaging multiple cognitive systems at once.

You are solving logistical problems while making aesthetic decisions. You are balancing planning, memory, customer psychology, negotiation, physical movement, and creative judgment simultaneously. You are adapting in real time as conditions change. That is not passive entertainment. It is active cognitive engagement layered across emotional, social, creative, and analytical systems.

Research into cognitive reserve suggests that mentally stimulating, socially engaging, and physically active lifestyles may help support long-term brain resilience as we age. Cognitive reserve refers to the brain’s ability to adapt and compensate over time, and studies increasingly suggest that meaningful engagement matters. Activities that combine learning, movement, social interaction, and creative problem-solving appear especially beneficial.

Consider what happens when you spend an afternoon redesigning an antique booth, rebuilding a vintage camera, restoring furniture, or planning a large garden. You are analyzing spatial relationships and visual balance while remembering details, solving problems, and making constant adjustments. You are lifting, moving, arranging, editing, evaluating, and adapting. Your brain is coordinating executive function, memory, creativity, emotional judgment, and flexibility all at once.

That level of engagement is difficult to replicate through passive screen consumption alone.

One of the hidden dangers of modern technology is not simply distraction. It is passivity. Doom-scrolling, endless content feeds, and algorithmically curated entertainment place us into a reactive state where we absorb rather than participate. Consumption becomes our default mode.

Creation works differently.

When you build, stage, repair, negotiate, curate, write, or physically solve problems, you move from passive consumption into active participation with the world around you. Research increasingly suggests that productive, socially connected, and cognitively demanding activities are associated with better emotional resilience and lower risk of cognitive decline later in life.

Even the day-to-day demands of complex hobbies and creative projects exercise what psychologists call executive function, the mental systems responsible for managing complex behavior. Staying focused despite distractions, adapting when plans fail, juggling multiple variables at once, and making rapid decisions all require the brain to remain flexible and engaged. These are not abstract skills. They are the same systems we rely on for resilience, adaptability, and independent thinking throughout life.

AI itself is not the enemy. Used thoughtfully, it can absolutely enhance creativity, organization, and productivity. The key is maintaining an active role in the process. Technology should support thinking, not replace it entirely. There is a meaningful difference between using AI to organize your ideas and allowing it to fully replace your experimentation, judgment, creative voice, and problem-solving.

The goal is collaboration, not surrender.

Perhaps the bigger lesson is that not every inconvenience needs immediate automation. Sometimes wrestling with a problem is exactly what strengthens adaptability, confidence, and mental flexibility. The goal is not maximum friction, but it may also not be maximum convenience.

As machines become increasingly capable of acting like humans, it becomes even more important that humans continue acting like humans. We are not designed for endless passivity. We are designed to build, solve, adapt, create, and engage.

A deeply engaging hobby or creative pursuit may look simple from the outside, but cognitively it can function more like cross-training for the brain. It combines creativity, movement, social interaction, strategic thinking, emotional engagement, and real-world problem-solving into one deeply human experience.

The future likely belongs not to the people who outsource all thinking to machines, but to those who learn how to use technology while still keeping their own minds fully engaged.