Start with what matters
Build around a real question, responsibility, or capability.
Learn beyond the answer
Turn curiosity
into capability.
Choose something that matters to you. Curiosity Project helps you understand it, connect it to the work around you and practise until you can explain, apply and challenge it for yourself.
Planned launch offer: 14-day full trial. No card. No automatic charge. You do not need to know where to begin.
Curiosity
Explore
Challenge
Apply
Keep
What you can
now do
now do
Learn by doing
Explain, attempt, compare, question, and revise.
Show what became yours
Keep AI help visible and test what you can do independently.
Keep building
Stop at the current goal and return when a new need appears.
AI can answer. You still have to understand.
A fast answer is useful, but learning requires more.
AI can explain a concept, complete a task and produce convincing work in seconds. That can make you more productive without making you more capable.
Curiosity Project focuses on what still has to become yours. You work on understanding the problem, asking better questions, judging the evidence and applying what you learned when the situation changes.
The human role is moving up a level
Being in the loop is not enough.
Being the human in the loop matters only if the human understands enough to add something consequential to the loop.
As machines do more of the immediate work, people need to set direction, judge the result, challenge it when necessary and keep it grounded in reality.
Curiosity is human leverage
Let curiosity run. Give it direction.
Curiosity opens possibilities. Discipline helps you decide which ones are worth pursuing and what evidence could change your mind.
Curiosity finds the direction.
Begin with a question, tension, responsibility, or something you want to become better able to do. It can be incomplete.
Disciplined curiosity takes you deeper.
Look for assumptions, missing evidence, rival explanations, boundaries, and questions worth pursuing.
A clear process turns work into capability.
Set a result, use good material, practise in different ways, test under changed conditions and update when the evidence changes.
Go deeper. Then look sideways.
Understand the subject. Then see where it connects.
Depth
Go further inside the subject.
Understand how it works, what supports it, what it assumes, where it fails, and how to judge it responsibly.
Breadth
Follow the connections that matter.
Connect what you know to the teams, functions, customers, decisions, incentives, risks, and systems around it.
Breadth is not a request to learn everything nearby. Your project follows only the connections that matter to the result you chose.
Making learning explicit
We taught machines to learn explicitly. What can we borrow back?
Define a resultLearn from useful materialAttemptUpdateTest somewhere changed
People are not machines, but making learning explicit is useful. It gives us a process we can examine and improve.
How a Curiosity Project works
One meaningful goal. A clear path. No surprise finish line.
- 01
Bring what matters
Tell us what you are curious about, responsible for, or hoping to become better able to do. “I know nothing about this yet” is a valid place to start.
- 02
Agree on the result
Review what you will work toward, why it matters, what is in scope, and what will count as success. If only an honest first phase can be defined, you will know before you begin.
- 03
Learn actively
Work through explanations, examples and attempts. Compare ideas, test connections and revise. The help tapers as you become more independent.
- 04
Try it somewhere new
Explain it in your own words, handle a changed situation, challenge a weak answer, or apply it in the context that matters to you.
- 05
Reach the goal. Keep the project.
When you demonstrate the result you agreed to pursue, active learning stops. Your project remains available if the domain changes or you choose a new direction later.
Know what became yours
Count what you can demonstrate, not the answers you received.
The project records the help you received and only credits what you demonstrated under the tested conditions. Confidence and content completion do not count as proof.
Encounter itWork with itShow itUse it somewhere changedApply it where it mattersReturn later if needed
Reasons to begin
Start with a real need, not a perfect question.
01I have taken responsibility for an area I do not understand well enough yet.
02I need to judge AI-generated work instead of accepting it at face value.
03I know my specialty, but I need to understand how it affects the rest of the organization.
04I need to make a decision in a domain that is new to me.
05I can follow examples, but I struggle when the situation changes.
06I want to challenge what I think I know before I rely on it.
The framework matters more than the software
You do not need Curiosity Project.
You can use these ideas with ChatGPT or the LLM of your choice: set an objective, explore, ask questions, challenge assumptions, test yourself in changed situations, follow meaningful connections, and return when things change.
Curiosity Project exists to make that process easier to practise consistently and preserve over time.
Why I built it
I want people to keep developing their own capability as AI improves.
AI worries a lot of people, and I understand why. I also see an opportunity. A project that once required an expensive course, access to a specialist or weeks of research can now begin with a question and an LLM.
I want to find out whether AI can help us follow our curiosity, learn more deeply and better judge the systems around us.
Darren SooCreator, Curiosity Project
Planned launch offer
Learn while it matters. Stop when you're done.
Pay for active learning support. Keep your project history after active access ends.
Standard individual
CA$22.99 / active month
- 14-day full trial
- No card and no automatic conversion
- One focused project in active learning at a time
- Cancel before the next renewal
- Read-only project history under the published inactivity policy
A rough question is enough to begin
What are you curious about?
Start with something that matters to you. The question can improve as you learn.