The Rookie Mindset
A guide to staying original in an automated world.
You can't out-expert this moment. But you can out-question it.
We’re taught that expertise is the goal. That if you collect enough frameworks, wins, and proof points, you’ll eventually graduate from not knowing. But in my experience, the opposite is true.
We grow through the process of figuring things out, not by having them figured out.
That’s the rookie mindset. Not something to outgrow, but something to protect.
And now, in a world where AI makes it easier than ever to skip that process, staying rookie-minded isn’t just helpful, it might be your only edge.
The Default Thinking Crisis
Everyone’s rushing to use AI, but nobody’s asking how it’s shaping them in return.
We're optimizing workflows, stacking tools, fast-tracking decisions, and calling it productivity. But the faster we go, the more we forget what made the work meaningful in the first place: curiosity, originality, and intent.
AI isn't just a tool. It's a mirror. And people are too busy automating to notice what it's reflecting back.
We've entered an era of default thinking—where convenience wins, templates replace thought, and speed is confused for clarity.
Default is the path of least resistance. It’s what happens when we outsource the hard part—not the typing, the thinking.
Default thinking robs you of ownership. Your ideas sound right, but they don’t sound like you. The pattern is everywhere:
🧑🎓 College students paste essay prompts into ChatGPT. Professors get 10 variations of the same argument. Nobody remembers what the topic was even about.
🧑💼 PMs feed user data into AI tools and accept the “recommended” insight. Metrics stay neutral. Meaning goes missing.
🚀 Founders pitch startups that feel AI-generated. Same slide. Same framework. Same illusion of originality.
📹 Creators let AI outline their content. The tone works. The structure flows. But the soul is gone.
The outputs might be clean, but they all look the same. The evidence backs it up:
🧠 Stanford outlines how struggle is essential for deep learning, but AI is training us to skip it.
🏢 Microsoft reports that higher confidence in AI is associated with less critical thinking, while higher self-confidence is associated with more critical thinking.
👉 Forbes explains that AI is steering us toward a more monolithic and less diverse world.
💼 Akash thinks LinkedIn posts, newsletters, slide decks, landing pages, they’re starting to blur together. Not because of bad design, but because of default ideas.
This isn’t just an efficiency trend, it’s becoming a thinking crisis. The best work comes from unique perspectives, challenging assumptions, and noticing what others miss.
You can’t automate your way to originality, you have to think your way there.
That’s why this matters. If you don’t protect your perspective, AI will flatten it. If you don’t pause to question, it will auto-complete your thinking.
So the question isn't whether to use AI, it’s how to use it without losing your mind—literally.
The Rookie Mindset
My antidote isn't about rejecting AI, it's about rebuilding our relationship with the learning process itself.
We grow through the process of figuring things out, not by having them figured out.
The process is the point.
Embracing that process, running towards it instead of away, is what I call the rookie mindset. It's not about being new, but staying new: in how you think, question, build, and adapt. It's remaining open when the room wants to sound certain.
So what does that actually look like in practice? These 4 traits anchor it:
These aren't just traits, they're deliberate choices.
1. Confident Doubt
Not afraid to be wrong. Always ready to be surprised.
WHAT: Confident Doubt is the the practice of moving forward with clarity while staying open to being challenged. It’s not indecision, it’s strategic humility. The best thinkers don’t cling to their first ideas. They treat beliefs like prototypes: testable, flexible, and never too precious to revise.
WHY: In a culture obsessed with confidence, we reward people for having fast answers. But in a world shaped by AI, speed is cheap. The real value lies in the ability to shift your thinking as the context changes. That’s what confident doubt protects.
→ When the room wants to sound sure, be the one still asking better questions.
2. Beginner's Curiosity
Sees things with fresh eyes. Asks "why" when others assume "of course."
WHAT: Beginner’s Curiosity is the practice of approaching familiar problems like you’re seeing them for the first time. It’s not a lack of experience, it’s the refusal to let experience harden into assumption. It helps you stay alert to what others miss, simply because they’ve stopped noticing.
WHY: In a world of pattern-matching and best practices, curiosity gets flattened. We assume because something exists, it must be optimal. But progress doesn’t come from what’s accepted, it comes from questioning what’s taken for granted.
→ When the room is building on assumptions, be the one breaking them.
3. Effortful Thinking
Chooses depth over default. Takes the harder path—on purpose.
WHAT: Effortful Thinking is the choice to slow down, go deeper, and understand, even when tools offer you the fast-forward button. It’s the willingness to struggle with a problem before the answer. Not because struggle is virtuous, but because that’s where insight lives.
WHY: AI promises instant answers without the messy middle. Yet that middle—the confusion, the dead ends, the reformulations—is where breakthrough thinking happens. Skip the struggle and you'll produce what everyone else produces: ideas that are correct but common.
→ When the room automates the thinking, be the one still doing the manual reps.
4. Pattern Sense
Thinks in systems, not fragments. Understands the why behind the what.
WHAT: Pattern Sense is the practice of seeing beyond individual problems to the systems that generate them in the first place. It’s systems thinking applied to daily decisions—the discipline of zooming out before zooming in. Instead of asking why this user dropped off, ask what journey brought them here.
WHY: In fast-paced environments, we default to addressing symptoms rather than causes. We fix the same problems repeatedly without addressing their shared source. Pattern Sense shifts you from endless firefighting to designing systems that prevent fires altogether.
→ When the room fixes what’s broken, be the one redesigning the system that broke it.
The Rookie in the Wild
The rookie mindset isn’t just a theory, it’s alive in the daily choices of people who refuse the default. You won’t just find it in boardrooms or TED talks. You’ll find it in quiet moments, small acts of resistance, and the decision to think for yourself when no one’s watching:
🧑🎓 The student who doesn’t just ask AI to write the essay—they prompt, reflect from different angles, and rewrite. They use AI to understand the material, not bypass it.
🧑💼 The PM who doesn’t just accept “recommended insights”—they question every insight until it ties back to a real user need. They use AI for signal, not direction.
🚀 The founder who skips the YC template and starts with the problem that bothers them most in the real world. The one no prompt could generate, but can facilitate.
📹 The creator who uses AI to challenge their outline, not ghostwrite it. They gut-check every sentence until it sounds like them again.
And then there’s me 🧑💻 the writer—writing this issue. Using AI not for the words, but the push to make it better. It’s a co-pilot, not an auto-pilot. I do the thinking for me.
[my rookie process note]
I used ChatGPT, Claude, Perplexity, Gemini, and more late-night queries than I care to admit.
I started with a simple story I wanted to share. Then paused. Asked: What are people actually wrestling with right now?
AI helped me dig through Reddit threads, Google Trends, and other newsletters—but it couldn’t name the tension I was circling: staying original in an automated world.
I didn’t just listen to AI. I broke it, rewrote it, disagreed with it, and dropped in my favorite prompt many times:
Pretend you completely disagree with this post. Break down the flaws in my argument, challenge my assumptions, and identify any gaps in logic. If something is vague or unconvincing, call it out. Then suggest stronger ways to frame my point.
The goal wasn’t to get the right answer. It was to get uncomfortable. I didn’t use AI to skip the work, I used it to stretch it. To catch my blind spots, challenge soft logic, sharpen structure. The ideas, the voice, the judgement?—still had to come from me, every-time.
This isn’t draft 1. Or draft 10. It’s probably draft 25. And that’s exactly the point.
The rookie mindset shows up not in the tools you use, but in the posture you bring. Not in what you automate, but in how much of yourself you’re still willing to put in.
That’s where originality lives…
The Rookie Practice
You made it this far so let’s get practical.
This isn’t a mindset you adopt once. It’s a practice—a series of small choices that compound over time.
While others accept AI outputs as gospel, rookies ask: What's missing here? What assumptions are baked in? What if the opposite were true?
Here are 10 ways to stay deliberately rookie in how you think, create, and collaborate:
These are the rookie rituals. Small shifts that compound. Practice one, and the rest get easier.
Start with a blank page – Before reaching for a template or prompt, open a blank doc and invite your brain to make the first move. Let your own thinking lead. Clarity loves a blank canvas.
Zoom out until the REAL question reveals itself – Instead of debating tiny answers, ask the bigger question that makes the rest irrelevant—the one that shifts the frame, not just the tactic.
Reverse your strongest opinion – Take your most confident belief and spend 15 minutes arguing the opposite. What would make you wrong? What might someone with a different background say?
Designate a rookie in every meeting – Rotate someone to ask the naive, disruptive questions no one else will. Bonus: it turns critique into a creative role, not a threat.
Build something with no outcome in mind – Run a 30-minute creation sprint with zero stakes. Make a landing page, a poem, a visual, a write-up…. explore by doing, not performing.
Relearn the basics – Return to a beginner resource in your field and notice what hits different now. The fundamentals evolve as you do and the basics reveal different insights at different stages of expertise.
Audit your defaults – Once a week, write down one default decision you made on autopilot and question if it still serves you. Also question the assumptions that led you to that decision in the first place.
Stretch the argument – Ask AI (or friends and colleagues) to disagree with you. Not to win but to stretch, spot the gaps in your logic, and refine your thinking. Treat it like a mental sparring partner.
Change your inputs to change your thinking – Step out of your usual context, read outside your domain, rearrange your workspace, take the longer but more scenic route. Creativity follows contrast.
Think promptly – Don’t ask “How do I get this done?”, think “How do I write the perfect prompt to get this done?” What are the constraints? The goals? The assumptions baked in? Prompt like a product thinker.
The rookie mindset isn’t something you have, it’s something you do. The more you do it, the more original your thinking becomes. Not automated, not templated, just yours.
Some rituals are solo, some collaborative, but all repeatable. Pick one, try this week, and see what happens.
Again…
You can't out-expert this moment. But you can out-question it.
This took 25+ drafts, 4 AI models, countless late-night prompt rewrites, and moments of genuine doubt. The Rookie Mindset isn’t a theory I’m sharing, it’s how this was made.
That’s what rookies do, that’s who this is for.
More soon.
— Akash
📩 P.S.
What’s one part of your life running on autopilot?
How would the rookie version of you approach it differently?
I love this! Some of the steps in the rookie mindset, like reversing your opinion or zooming out, really align with the SCAMPER design thinking methodology, which I often use when I want to dissect a problem and make sure I'm looking beyond the surface level.