Zero to AI Blog
Tall Poppy Syndrome meets AI: why we secretly hate beginners.
AI is the first technology in a generation where almost everyone is a beginner at the same time. That should make learning easier. In New Zealand, it often makes learning publicly feel like walking through a minefield.
The cultural problem
We need people experimenting, but we punish people for learning out loud.
Tall Poppy Syndrome makes visible learning feel risky. It encourages people to stay quiet, perform expertise, and avoid asking questions. That is a serious problem when AI capability needs to develop quickly and practically.
I posted about an AI experiment I tried last week. Nothing fancy, just testing whether ChatGPT could help me organise my weekly planning.
Within an hour, someone I had never met had commented: “Bit basic, mate. Most of us moved past that months ago.”
This is very New Zealand.
We have a particular cultural affliction that makes learning anything publicly, especially AI, feel like walking through a minefield. It is called Tall Poppy Syndrome, and it is killing our ability to adopt new technology at exactly the moment we need to be learning fastest.
What Tall Poppy Syndrome actually means
If you are not from New Zealand or Australia, here is the quick version: Tall Poppy Syndrome is the cultural tendency to cut down anyone who stands out, achieves something, or, crucially, tries to improve themselves in a visible way.
The metaphor is literal. If a poppy grows taller than the others, you cut it down so it matches the rest of the field.
In practice, this shows up as:
- downplaying your own achievements;
- dismissing other people’s wins;
- punishing people for trying something new;
- creating an environment where it is safer to stay quiet than risk looking stupid.
This works reasonably well for maintaining social harmony in a small island nation of five million people where you are going to run into the same people your entire life.
It works terribly for learning AI.
Why AI learning and Tall Poppy Syndrome are a terrible mix
AI is the first technology in a generation where almost everyone is a beginner at the same time.
Senior executives are beginners. Technical experts are beginners. Twenty-year veterans in their fields are beginners.
This should be great. It should level the playing field. It should create an environment where we are all learning together.
But in New Zealand, it does not work like that.
Everyone pretends they are further along than they are
Nobody wants to be the person asking “dumb” questions, so they do not ask questions at all. They nod along in meetings, Google it later, and hope nobody notices.
The people experimenting get cut down
Post about trying something with AI and someone will tell you it is basic. Share something that worked and someone will explain why their approach is better.
We are more comfortable mocking AI than learning it
It is socially safer to make jokes about ChatGPT writing terrible poetry than to admit you are using it every day and finding it useful.
Expertise gets performed, not developed
People are incentivised to look like they know AI rather than actually learning it, so we get confident opinions and very little honest experimentation.
The result? New Zealand is full of people who are quietly curious about AI but publicly dismissive of it, because that is the culturally safe position.
The comment section problem
Here is a pattern I see constantly on New Zealand professional forums, LinkedIn and local business groups.
“I just tried using ChatGPT to help draft client emails and it saved me about an hour today. Pretty cool.”
The responses come in three flavours.
The Dismissive Expert
“Lol, we have been doing that for years. Wait till you discover the more advanced thing. You are barely scratching the surface.”
The Concern Troll
“Just be careful about privacy. And accuracy. And bias. And job displacement. Have you thought about this long list of risks?”
The Humble Bragger
“Nice. I have been using Claude, custom GPTs, API integrations and my own fine-tuned model to automate my entire workflow. Let me know if you need help with the basics.”
Notice what is missing?
- “That is great, what kind of emails are you writing?”
- “Did you run into any issues?”
- “I tried something similar, here is what I learned.”
Genuine curiosity. Shared learning. Building on each other’s experiments.
Instead, we get a performance of superiority designed to establish hierarchy. The person who posted feels stupid for sharing. They do not post again. And we all lose the benefit of their learning.
The gap between “I should probably learn this” and “I am now competitively disadvantaged” is measured in months, not years.
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Why this matters more than you think
New Zealand is a small, isolated economy that punches above its weight in several industries. We are good at agriculture, tourism, film production, and increasingly, technology services.
All of these industries are about to be reshaped by AI.
If we cannot figure out how to learn AI without our cultural immune system rejecting anyone who tries publicly, we are going to fall behind. Fast.
Because here is the thing about AI: it is moving too quickly for the traditional Kiwi approach of “she’ll be right, we’ll figure it out.”
The gap between “I should probably learn this” and “I am now competitively disadvantaged” is measured in months, not years.
And the gap between “someone in my industry is experimenting with this” and “my business model is obsolete” is even shorter.
We do not have time for Tall Poppy Syndrome anymore.
The Beginner Punishment Tax
I talk to business owners and mid-career professionals every week who are trying to figure out AI.
The most common thing I hear is: “I feel stupid asking this, but…”
They are not stupid. They are beginners. There is a difference.
But our culture has created an environment where being a beginner is something to apologise for, hide, or overcome as quickly and quietly as possible.
Time wasted
Instead of asking a simple question that would save them three hours, they spend three hours trying to figure it out themselves, often getting it wrong.
Money wasted
They buy tools or courses they do not need because they do not know enough to ask, “do I actually need this?”
Confidence destroyed
Every failed experiment reinforces the belief that “I am just not technical enough” or “AI is not for people like me.”
Learning delayed
They wait until they feel ready to start, which in practice means they never start.
The irony is that the people actually making progress with AI are the ones who are comfortable being publicly incompetent.
They ask dumb questions. They share half-formed experiments. They admit when something did not work.
And they learn faster than everyone else because they are not wasting energy pretending to know things they do not.
What this looks like in practice
Let me give you a real example from a workshop I ran last month.
I was teaching a group of small business owners how to use ChatGPT for basic business tasks. Writing emails, summarising documents, brainstorming ideas. Nothing advanced.
One participant, let’s call him David, was clearly struggling. He kept making the same mistake with his prompts: being too vague, then getting frustrated with generic responses.
Another participant, Sarah, said: “Oh, I was doing that exact same thing ten minutes ago. Here is what worked for me. I just added more context about who I am writing to and what I actually want. Try it.”
David tried it. It worked. He got a better response. He looked relieved.
Then someone else, Mark, jumped in: “Yeah, but that is pretty basic. You should really be using custom instructions and system prompts. That is how you get proper results.”
The energy in the room changed immediately.
David’s relief turned to embarrassment. Sarah stopped sharing what she had learned. Mark had established himself as the expert, but nobody wanted to ask him questions because he had already signalled that basic stuff was beneath him.
The rest of the workshop, people stopped experimenting out loud. They worked quietly. They googled things on their phones. They did not risk looking stupid.
Classic Tall Poppy Syndrome in action.
One person trying to help another beginner got cut down by someone performing expertise.
The AI advice industrial complex makes it worse
New Zealand businesses are being flooded with AI advice from three sources:
International AI gurus
They often do not understand our market, scale or constraints. Their advice is optimised for Silicon Valley startups with unlimited budgets and dedicated AI teams.
Local AI consultants
Some are legitimate, many are not. The incentive is often to make AI sound both essential and complicated.
LinkedIn performative experts
People who discovered ChatGPT recently and are now posting daily about elaborate workflows that very few normal people actually use.
All of this creates an environment where simple, practical AI use feels embarrassingly basic, complex AI use feels like the only thing worth talking about, and normal people trying to learn get stuck between “this is too simple to share” and “this is too complicated to ask about.”
The middle ground, where most actual learning happens, disappears.
What it feels like to learn AI in New Zealand right now
You are a mid-career professional. You have heard enough about AI that you know you should probably be doing something about it.
You watch a few YouTube videos. You sign up for ChatGPT. You try a few prompts. Some work okay. Some do not.
You are not sure what you are doing wrong. You are not sure what good looks like. You are not sure if you are making progress or wasting your time.
You think about asking someone. But who?
Your colleagues are probably in the same boat, but nobody is talking about it. Your boss might think you are behind. LinkedIn feels risky because someone will either make you feel stupid or try to sell you something.
So you keep quiet. You keep experimenting in private. You make slow progress, but you are never quite sure if you are doing it right.
Meanwhile, everyone around you seems to have it figured out.
But here is the truth: most of them are doing exactly what you are doing. Figuring it out quietly, feeling uncertain, wondering if they are the only one who does not really get it.
We are all beginners pretending not to be.
Real expertise comes from doing things, failing at things, and learning from things. Not from sounding confident on LinkedIn.
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Breaking the cycle
I do not have a complete answer, but I have some observations from the people I have seen actually make progress.
They normalise being public beginners
They post about trying things and getting them wrong. They ask questions that might sound basic. They admit when something does not work.
They celebrate other people’s experiments
When someone shares that they tried something with AI, even if it seems basic, they respond with curiosity rather than judgement.
They share the messy middle
Not just the polished workflow, but the three failed attempts that came before it.
They build learning communities
They create spaces where it is safe to not know things, where questions are welcomed, and where progress matters more than performance.
This is not easy in New Zealand culture. It requires actively fighting against our default mode.
But it is necessary.
What I am trying to do differently
With Zero to AI, I am trying to create the opposite of Tall Poppy Syndrome.
I share things that did not work. I admit when I am uncertain. I ask basic questions. I show the failures alongside the successes.
Not because I think this makes me special, but because I think this is what actual learning looks like.
And I am trying to create a space where other people can do the same.
A place where you can say, “I just figured out how to use ChatGPT to summarise my meeting notes and it saved me 20 minutes,” without someone jumping in to tell you about their multi-agent autonomous AI system.
A place where you can ask, “what is the actual difference between ChatGPT and Claude?” without someone implying you should already know.
A place where you can experiment publicly, fail publicly, and learn publicly without getting cut down for standing out.
Because right now, we need more people experimenting, not fewer.
The real risk
New Zealand businesses are going to adopt AI. That is not in question.
The question is whether we adopt it thoughtfully, experimentally, with our eyes open to both opportunities and risks, or reactively and desperately after we have already fallen behind.
Right now, we are set up for the second path.
Because our culture is creating an environment where:
- the people who are genuinely experimenting stay quiet;
- the people who are loudly confident are not necessarily competent;
- the people who need help are too worried about looking stupid to ask for it;
- everyone is slightly behind where they could be because we are all pretending to be further along than we are.
This is expensive. Not just in individual careers, but in national competitiveness.
Every person who delays learning AI because they are worried about asking dumb questions is a person who is not building capability.
Every business that waits because it does not want to look like it is behind is a business that is actually falling behind.
Every community that punishes people for learning publicly is a community slowing down its own adaptation.
We cannot afford this anymore.
What needs to change
This is not about becoming American. We do not need to turn into a culture of relentless self-promotion and individual exceptionalism.
But we do need to make some adjustments.
Celebrate experimentation, not just achievement
The person who tries something and shares what they learned, even if it did not work, is contributing.
Value questions as much as answers
Asking a good question helps other people who have the same question and moves everyone forward.
Create safe spaces for public learning
Online communities, meetups and workshops need explicit norms that we are all figuring this out together.
Stop performing expertise and start building it
Real expertise comes from doing things, failing at things and learning from things. Not from sounding confident on LinkedIn.
This is cultural change. It is slow. It is hard. It requires individual people making different choices.
But it starts with one person being willing to be a public beginner.
Your turn
If you are reading this and thinking, “yeah, I feel that,” you are not alone.
Most people learning AI in New Zealand are feeling the same thing.
The difference between people who make progress and people who stay stuck often comes down to one decision: are you willing to look stupid for a little while?
- Are you willing to ask the basic questions?
- Are you willing to share the experiment that did not work?
- Are you willing to admit you do not know something?
- Are you willing to be the tall poppy that might get cut down?
Because that is what it takes.
Not forever. Just long enough to actually learn something.
The irony is that the people most worried about looking stupid are often the ones thinking most carefully about what they are doing.
They are just stuck because they think everyone else knows more than they do.
They do not.
We are all beginners. Some of us are just louder about it.
Keep reading
Zero to AI is built for honest, practical learning.
If you are learning AI in New Zealand, you do not need to pretend you are already there. Start small, ask better questions, share what you are learning, and build capability through real use.