The other day I wrote "Why isn't knowledge easy to get?" This is related.
When you want a new skill, how do you learn?
The world has free (or cheap) learning materials, but nothing that systematically maps a path to your purpose.
If you join a school because you know nothing, someone capable has made useful content — just completing it should get you to a certain level (supposedly).
But downsides: learning isn't matched to your purpose, content isn't fitted to you, and money and time cost too much.
So I thought I'd try making it myself.
Still, thanks to web articles, YouTube, Udemy and other learning video platforms, useful materials exist.
No systematic roadmap — but the parts are there.
If I make the roadmap myself and gather the parts, it can be free.
What I learn, reflected into the materials, becomes my own textbook and notebook.
That way, my own school is complete.
I say "school" on purpose — because most schools in the world are probably built the same way.
Fully original schools basically don't exist. Ultra-personal schools where the value is "who" teaches you are one thing — but MBA, design school, programming school: existing learning already overflows, so gathering that alone should make a minimum set of materials.
Still, whatever you learn, practice is needed — so design the feedback experience in advance too.
Getting feedback from customers or mentors and stacking experience is necessary.
Whether you pay, or get paid while doing it as work, I think you need that — either way, designing feedback in advance (who, on what points, toward which skill gains) is a good idea.
Concretely this time: I asked ChatGPT and broke skills for my purpose into a mandala chart — finer pieces.
I also made a basic-learning roadmap for how to sharpen each skill.
(ex: imitate and trace concrete examples → test phase close to real cases → learn as an actual project, etc.)
At that point, set provisional clear criteria for each phase.
Making this, I realized: I've been learning a domain deeply with a mentor, and it often felt like endless foundational learning — boring.
In the foundational phase you can learn forever if you try, so I need to split phases, call them cleared, and move on. Lesson learned.
And it's bad to keep slipping back to foundational learning whenever you want more knowledge.
Let me summarize the overall flow.
First I worked on clarifying what I want to learn.
Put into language what skill you want to grow and what outcomes you want.
Especially: for what use, what benefit to you, at what finish level.
Next I asked ChatGPT how to learn XXX efficiently.
Look up prompts that tend to output well, then try those — recommended.
Organize information and get an objective view.
ChatGPT offered angles and methods I wouldn't notice alone, so I could see the learning plan with a wider field of view.
While summarizing ChatGPT's output into a mandala chart, I put it in a spreadsheet.
Comprehensive organization shows "I already get this" vs "this looks high priority."
After breaking skills in the mandala chart, plan for each skill what to learn and in what order.
Where to start and what to prioritize becomes clear, so learning can move efficiently.
Next I turned that into training materials.
I used Google Slides, but anything works.
For each skill I clearly wrote learning goals, procedures, and completion criteria.
Made for myself, so it ended up clear and practical.
Have acquaintances help with tests, pay a mentor, take work — learn while doing.
This domain looked usable on existing projects as-is, so practice-as-experience was fine — but to raise quality I paid someone who could mentor and got feedback.
That's it.
You still need experience until it holds up in real work, and the feedback that comes with it — but making training materials for yourself is fun as an experience.
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