Your imagination is your invitation
In the AI-era, one of the most important skills is asking the right questions, and that usually requires deep expertise
In the BBC’s 2015 adaptation of Alice in Wonderland, Alice is agonizing over an invitation to the Queen of Hearts' grand party. Desperate, she seeks the advice of the Mad Hatter, who offers a cryptic but tantalizing suggestion: “In Wonderland, your imagination is your invitation.”
There’s just one problem. Alice doesn’t know what an invitation looks like. Her imagination, it turns out, is constrained by what she has previously seen and experienced.
After several false starts—multiple “prompts,” if you will—Alice finally conjures the image of a red-and-gold parchment. Then, emboldened, she imagines invitations for her entire family.
The theme, as the Mad Hatter suggests, is simple: “Anything your heart desires, as long as you can imagine it.” And at first glance, this feels like an apt metaphor for the discourse surrounding AI and the future of learning.
The prevelant temptation is to believe that AI can collapse the distance between ambition and achievement, that skill and effort matter less because the technology will fill in the gaps. That expertise itself is becoming obsolete. That temptation is deeply flawed.
The AI Illusion: Why Expertise Matters More Than Ever
In practice, anybody that’s used these tools knows that unless you have at least some domain expertise you will end up with mediocre results at best.
Yes, it’s easier now than ever to produce mediocre crap from apps to poems - which is precisely why the premium on high quality and distinctive outcomes will only go up.
The paradox is this: AI is a multiplier. For those with deep knowledge, it accelerates insight and execution. For those without it, it is a poor crutch to mediocrity. Gen AI gravitates towards the most “average” not the most optimal.
So, if expertise remains essential, what kind of expertise matters most? I would argue that three distinct dimensions of expertise will define success in the AI era.
1. Knowing What “Good” Looks Like
Learners need to know what good looks like. As Siya Raj Purohit at OpenAI notes: “the ability to visualize great output” and have a “sharper vision” for what great looks like will only become more important with time.
Learners cultivate this sense by continuing to immerse themselves in the great works and learning from experts in the field (and yes, an AI tutor might help them learn that content more efficiently but it cannot replace the needed exposure).
2. Cultivating a Unique Lens on the World
Learners need to cultivate their own unique taste. Cultivating a unique taste and context matters more than ever in a rising tide of sameness.
The more AI can execute, and the more its context windows expand “the more your eye for what's interesting – your ability to discern and curate what matters and why – becomes everything”.
Cultivating their own taste dramatically increases learners' ability to generate questions and combinations that are unique to them and their journey. This will become a unique advantage that helps them standout in a sea of sameness.
3. The Knowledge Paradox in Coding
The rise of large language models has created what some call a “knowledge paradox”: AI helps experienced coders exponentially more than novices.
Why? Because coding is not just about writing syntax—it’s about understanding how systems interact, how logic flows, how constraints shape creativity. AI can assist with debugging and optimization, but without foundational knowledge, users become overly reliant on a system they don’t fully understand.
To truly leverage AI’s capabilities, learners need a functional grasp of software architecture, frameworks, and problem-solving patterns. This isn’t about memorizing algorithms—it’s about learning to think like a builder.
As the AI gets better, the return on mastery in software development - especially at the foundational level - will also only increase.
Your Questions Can Only Be As Good As your Expertise
If you take one thing from this article, let it be this: the ability to ask the right questions has never been more valuable.
AI does not replace knowledge; it rewards those who know enough to push its boundaries. The better you understand your domain, the sharper and more original your questions will be—and in an AI-powered world, the best answers belong to those who ask the best questions.
Ramadan Kareem to all those observing the holy month 🌙 May you be seeking the right answers this time of year.
I hope you enjoyed the last edition of Nafez’s Notes.
I’m constantly refining my personal thesis on innovation in learning and education. Please do reach out if you have any thoughts on learning - especially as it relates to my favorite problems.
If you are building a startup in the learning space and taking a pedagogy-first approach - I’d love to hear from you.
Finally, if you are new here you might also enjoy some of my most popular pieces:
The Gameboy instead of the Metaverse of Education - An attempt to emphasize the importance of modifying the learning process itself as opposed to the technology we are using.
Using First Principles to Push Past the Hype in Edtech - A call to ground all attempts at innovating in edtech in first principles and move beyond the hype
We knew it was broken. Now we might just have to fix it - An optimistic view on how generative AI will transform education by creating “lower floors and higher ceilings”.