Can I Work Less
and Turn My Experience into a Product?

I know I saved it.
Why can't I find it when I need it?

I save good articles. I take screenshots of images I want to reference later and write down things said in meetings. At the time, I am sure I will use them again. But when that moment comes, I have to start by finding where I put them.

Was it in a messenger, Notion, or Drive? I try different search terms and eventually look for something similar again, or reconstruct it from memory. Even when I have already done the work, getting started again takes time.

That was my experience for a long time. As a brand director, I help businesses and shops decide how they present themselves to customers. Working across planning, design, and content means ideas, references, and client requests keep accumulating. Yet for all that activity, surprisingly few of my records helped with the next job.

If you are a freelancer or solo business owner who proposes the work, makes it, and talks to clients yourself, this may sound familiar. Ultimately, I am the only person who remembers what I did, finds the material, and connects it to the next task.

So I decided to build a system. Not to become more diligent about taking notes, but because I wanted something I had already done to make the next round a little easier.

Organization wasn't the real problem.
I had no way to reuse what I saved.

I had material in note apps, Notion, and Drive. But when I wondered whether a previous client had made a similar request, I could not retrieve it readily. I began to look less at where I saved things and more at what I recorded alongside them.

The location was not the only problem. Even when I found the file, it did not tell me why I had saved it, which task it was for, or what I had decided at the time.

For example, imagine saving a client's comment: "The explanation is too long." That sentence alone will not tell you what needed changing. To use it in another proposal, you also need to know which proposal it concerned, what the client did not understand, and what you decided to change.

What I had saved was the material.
What I needed again
was the reason behind the decision.

The same was true of nearly twenty years of experience: why an idea occurred to me, a choice that did not work, or something I wanted to do differently next time. Relying on memory made that experience hard to retrieve when a similar situation arose. I did not need a bigger archive. I needed a structure that connected past experience to the work in front of me.

I started using AI.
Then another kind of busywork appeared.

At first, AI felt exciting. I thought that simply handing over the reading and organization of scattered material would make things much easier. It did help me get drafts and summarize long texts.

But receiving an answer did not finish the work. I still had to choose the material to share, explain what I did, correct what did not fit, and save the result. At the next task, I brought out the same background explanation again.

I often wondered, "Am I using AI properly?" Answers arrived quickly, but my days were still busy. Was there less work, or was I doing the same work in a different way?

I used AI to reduce the work.
Then organizing its output
became another task.

So I changed direction. Rather than explaining everything from the beginning with every request, I wanted the next task to draw on my work and decisions already made. That meant recording which client it was for, what we had agreed to do, why we chose that direction, and what remained undecided.

That is how I became interested in a personal ontology system. The term may sound difficult, but the idea I want to apply to my work is simple: rather than storing people, projects, material, and decisions separately, define how they relate to one another. I want to preserve the sequence: this client's request changed the direction of this project, so this is what we need to do next.

I thought that connecting these organized records so AI could reference them might reduce how often I had to explain all the background myself. Collecting records does not mean AI automatically knows everything. I still have to decide which material it can read and check important judgments. I want to reduce not the act of deciding, but the repeated gathering and explaining that comes before a decision.

How AI defines me
will be a competitive advantage.

Building this system led me to another realization. Knowledge management organizes things internally, but now I also need to organize what others can see.

People now ask AI instead of entering keywords into a search box: "Recommend a brand director" or "Who is good at AI branding?" How AI describes me in response to those questions shapes my brand. Beyond ranking highly on Google, being included in AI's answers will be a competitive advantage.

That is why I started exploring GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization): structuring my information so AI can describe me accurately. It is also why I built a website, connected my activities, and organized them in a format AI can read. If I do not define myself first, AI may define me inaccurately.

This is not only for famous people or large companies. Solo professionals also need to explain what they do, which problems they have solved, and why someone should work with them. Actual work and the judgments behind it can say more about me than a job title alone.

That is why I want to turn experience accumulated internally into cases others can understand. This is not about revealing all of a client's private material. Within what I am allowed to share, I want to explain which problem I solved and how. A record that helps me reuse my work can also become evidence of why someone might choose to work with me.

I am not building a system
so I can do more work.

Honestly, I am the kind of person who builds systems because I would rather not have to work.

I work because I want freedom. That is why I keep building systems: things that can operate without me, keep accumulating once set up, and be retrieved later. The purpose of automation and structure is not more work, but the same result with less effort.

And there is another reason. As this system develops, it can become a product. Not just something for me, but something I can sell to people facing similar problems. Freelancers and solo business owners know this feeling of fragmentation. Building a way to solve it, using it myself, and organizing it into something I can offer is what I am doing now.

Of course, collecting records alone does not create a product someone needs. What matters is whether others share the difficulty I experienced and can apply my approach to their work. Rather than handing over my working files unchanged, I want the templates and design method to explain what to record and how to connect it, so finding and explaining things again takes less effort.

Solve a problem I experienced,
then help someone else
use that method in their own work.

That is where I want the experience shared in this article to lead. Rather than keeping what I learned working alone as personal know-how, I want to turn it into a product that reduces someone else's trial and error. That is what monetizing experience means to me.

How to start today

You do not need an elaborate system. When you jot down one thought today, add just this question.

"Which project or topic
does this connect to?"

That one connection is a starting point for an ontology. You begin accumulating relationships, not just information.

For example, if you find an introduction page you like, save more than its link. Add a line: "Reference for the first page of next month's proposal. I like how it explains the service in one sentence before anything else."

Later, you can recall why you saved it and where you could use it, not just where the page was. As small connections accumulate, you can give AI material with reasons to reference it rather than a bare list of links.

After starting with one line, you may wonder which fields to record or how to connect records across multiple projects. So you do not have to invent every rule alone, I am preparing both a structure you can start using and a way to learn the design process.