ISSUE NO. 00
How This Series
Happened.
This series did not begin as an AI project.
It began on a drive to Norwich, with one unfinished ONE Academy idea and a two-hour conversation that kept getting bigger.
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READ THIS IF YOU ONLY HAVE TWO MINUTES
It started with
a half-formed idea.
This series started on a drive to Norwich.
I was driving with Rosie to a Rock and Roll concert.
For roughly two hours, she had to listen to me talking to my AI about ONE Blades.
I did not start the conversation because I wanted to create an AI series.
I started with a business idea that was not fully formed.
What if the future standalone ONE Academy became subscription-based, while EDGE owners kept access included?
That was not the final idea.
It was only the starting point.
The conversation kept moving.
No single prompt contained that final system.
Then I noticed something bigger than the idea itself.
I had not asked AI for a finished answer.
I had given it an unfinished thought.
It expanded the idea.
I reacted.
Some parts were useful. Some were wrong. Some gave me completely different ideas.
We kept narrowing, challenging, and rebuilding the thought until the final idea was much stronger than where we started.
Then I asked a different question.
Why is this not how
more people are taught
to use AI?
Most AI education I had seen focused on prompts, tools, features, or which model to use.
Very little of it explained the way I was actually using AI every day while building a company.
- Speaking rough thoughts out loud.
- Giving AI deep context.
- Building projects around real work.
- Maintaining source-of-truth files.
- Teaching AI the rules behind decisions.
- Letting AI help update its own project context.
- Challenging its answers instead of accepting them.
- Turning repeated conversations into systems.
THE WHOLE IDEA
The most important lesson from the drive was not the final idea.
It was how we got there.
GO DEEPER
People judge AI from
the wrong moment.
The useful part of AI is often misunderstood because people judge it from the wrong moment.
They look at the first prompt and the first answer.
That is like judging a coaching relationship from the first sentence a coach says to a skater.
The value is in what happens next.
The first idea
did not need to be right.
It only needed to be
good enough to start talking.
The idea kept
moving.
We had recently repositioned ONE Blades and rebuilt large parts of the website as a custom experience.
That opened up possibilities that did not exist when the site was treated mainly as an ecommerce store.
ONE Academy was becoming much bigger than a collection of skating lessons.
We had lessons.
Guides.
Coaching resources.
Progress ideas.
Assessments.
And a much more complete platform beginning to form around EDGE.
The thought that started the conversation was whether the future Academy platform could eventually become a paid subscription for non-EDGE users, while remaining included for EDGE owners.
That was enough to begin.
The first useful shift was realizing that subscription revenue was not the immediate goal.
The immediate goal was to build something useful enough that people would want to keep using it.
That led naturally to progress tracking.
Progress led to assessments.
Assessments led to coaching.
And suddenly we were no longer talking about one feature inside ONE Academy.
We were talking about a wider ONE ecosystem.
The first answer
was not the product.
The conversation
was the process.
ONE Credit changed
when the question changed.
When assessments entered the conversation, we discussed paid human feedback.
That led to a simple assessment fee.
Then the idea of store credit appeared.
At first, someone could pay for an assessment and receive that value back as credit toward physical products.
That sounded useful.
But something felt incomplete.
Then the bigger question appeared.
Why should ONE Credit only be useful for physical products?
If the credit could also be used for assessments, technical feedback, coaching, and other useful digital services, the credit itself became more valuable.
The better idea appeared
when we stopped asking
how to use the credit
and asked what the credit could become.
That changed another problem.
Import fees.
A customer paying a significant import charge could receive the same value back into their ONE account.
And instead of that credit only being useful when they wanted another expensive physical product, it could potentially be used for skating development.
The same idea could make smaller creator rewards more useful.
A creator earning ONE Credit for a specific brief could use that value toward feedback or coaching.
The original question was about subscriptions.
The conversation had now connected Academy, progress, assessments, coaching, ONE Credit, import-fee reimbursement, creators, products, and future account history.
The AI did not
replace the human.
There were several points in that conversation where the AI suggested something that was not quite right.
Those moments were useful.
The AI might suggest one economic model.
I would notice the flaw.
The flaw would trigger another idea.
That new idea would become the next starting point.
Then the AI could help develop it.
That is the relationship I find most useful.
Disagreement is not a failure.
Sometimes the wrong suggestion exposes the missing piece.
Sometimes rejecting an answer produces the better question.
The AI does not need to arrive at the final idea immediately.
It needs to help the thinking move.
AI expands the space.
The human decides
what matters.
Why voice
mattered.
This whole conversation happened while I was driving.
That matters.
I was not sitting at a desk carefully constructing prompts.
I was talking.
Voice-to-text let me say the unfinished version.
When I type, I naturally compress the thought.
I make it neater before I send it.
I remove some of the uncertainty.
I remove some of the side thoughts.
When I speak, the AI gets more of the actual thinking process.
When discovery matters,
talking can be better
than trying to write
the perfect prompt.
Speaking captures the contradiction.
The background.
The thing I am unsure about.
And sometimes the better idea that appears halfway through the sentence.
Rosie probably heard a two-hour conversation that moved from subscriptions to customs charges to coaching to AI methodology.
That messiness was useful.
Then I stopped talking
about ONE Blades.
Eventually I stopped asking about ONE and started asking about the process itself.
Why had the conversation worked?
Why did starting with a half-formed idea produce something much better several rounds later?
Why did the AI become more useful as the context improved?
Why was I maintaining project documents, rules, source-of-truth files, and decision frameworks, when most AI education seemed obsessed with individual prompts?
That was the moment the second idea appeared.
We should teach this.
Not as an AI expert explaining theory.
As someone showing how AI is actually being used while building something real.
That realization
became this series.
ONE is the evidence.
The method is transferable.
The seven issues that follow explain the method.
They are not about ONE Blades alone.
ONE is the evidence.
But the reader's world can be completely different.
You might be a teacher.
A parent.
A coach.
A freelancer.
A student.
A doctor.
A creator.
A small business owner.
Or simply someone trying to organize your own life.
The transferable lesson is the same.
How to think with AI.
How to give it useful context.
How to build projects around real work.
How to give it source material.
How to teach it your decision rules.
How to turn repeated conversations into systems.
And how to keep the human responsible for the final decision.
The most important lesson
from the drive was not
the final ONE Credit idea.
It was how we got there.
DO THIS NOW
Start with something
you have not finished thinking.
Do not wait until the idea is clean enough to become a prompt.
Give AI the unfinished version and work through it.
Pick a real unfinished problem.
Something you are genuinely trying to work out right now.
Not a fake exercise.
Say the messy version.
Explain what you know, what you do not know, and what feels wrong.
Use voice if that helps you capture more of the thought.
Let AI expand the space.
Ask what you are missing.
Ask what the idea could become.
Ask what it might unlock.
React instead of accepting.
Tell it what is useful.
Tell it what is wrong.
Follow the part that gives you another idea.
Look back at the path.
When the conversation reaches something useful, compare it with where you started.
Ask what changed, what triggered the change, and which part came from your judgment.
THINK WITH AI · ISSUE NO. 00
The idea was useful.
The way we reached it
was more important.
That is how this series happened.
ISSUE NO. 01