How I, a Web Director, Changed My Approach to Giving Shape to the 'Unknown'

Working as a Web director requires a wide range of knowledge, including CMS, production tools, access analysis, and task management.

I, too, have learned how to use the tools necessary for my work and have increased my knowledge regarding production and operations.

However, there was one thing I was always bad at.

That is the task of taking a 'vague request' that has no form yet and concretizing it from scratch.

'What should I look into?'

'What information should I organize?'

'Where should I even begin?'

While thinking about things like that, my hands would stop. Moreover, I would try to come up with the right answer from the start, making me even more unable to move.

I was like that, but as I challenged myself with things I hadn't experienced before, such as AI, Python, and Web marketing, my approach to work gradually changed.

This time, I will talk about how I stopped getting stuck on the 'unknown' and learned to first give it shape and move forward.

The wall I couldn't overcome even after learning to use tools

As a Web director, I have used various CMS, production tools, effectiveness measurement tools, and management tools.

As you learn how to use tools, the work you can do increases.

Updating pages.

Managing production schedules.

Checking access status.

Sharing progress with stakeholders.

I became able to handle these tasks little by little as I gained experience.

However, just because you can use tools doesn't mean you can move forward with all your work.

What I couldn't overcome was the task of structuring work from a state where neither the correct answer nor the final form is visible.

If a job has established operating procedures, you can move forward by looking up the steps.

On the other hand, requests like 'I want you to come up with something like this' or 'I want you to organize these issues' do not have fixed procedures from the start.

For a long time, I was troubled by this difference.

Every time I received a 'vague request,' my thinking would stop.

Whenever I received a vague request, I used to get anxious immediately.

'Is this understanding correct?'

'Shouldn't I be researching more?'

'If I show them something half-baked, will they think I'm incompetent?'

The more I thought about it, the more afraid I became to take action.

As a result, although I was researching something, I ended up in a state where I didn't know how to use the information I had found.

Before I knew it, the amount of material had increased, but no deliverables had been created.

Even though I was working hard, from the perspective of those around me, the work wasn't progressing.

I fell into that state many times.

I don't know what to research or where to start.

Back then, when I received a request, I would start by searching.

However, because I was searching without organizing the objectives or necessary items, the scope of my research would keep expanding.

I open pages that seem relevant.

I get curious about other keywords.

I search even more.

Before I know it, even what I was trying to research in the first place has become vague.

At this rate, it's less of an investigation and more of getting lost in information.

What was truly needed was not to search for answers right away.

First, I had to organize:

'What is this work intended to decide?'

'What items are necessary for that purpose?'

'What do we know now, and what is still unknown?'

I had to organize these points.

However, at the time, I didn't even know how to organize them.

I dared to dive into an inexperienced world to overcome my weaknesses

If I continued like this, I would keep getting stuck in the same places over and over.

Thinking this, I decided to intentionally challenge myself with things I had never experienced before.

I took on two main initiatives.

The first was building a web application using AI and Python.

The second was learning web marketing broadly.

In web marketing, I touched on various fields, including ad operations, creative production, data analysis, SEO article writing, sales copywriting, creating rough drafts for landing pages, and building SEO sites using WordPress.

I didn't know how to do any of these from the start.

In fact, I was surrounded by things I didn't understand.

However, this 'experience of starting from a state of not knowing' ultimately changed how I approach my work.

I tried building a web application from scratch using AI and Python

In web application development using Python, I started by thinking about what to build.

What are the necessary functions?

What should the screen look like?

How should the input information be processed?

If an error occurs, where should I check?

Naturally, I wasn't able to do everything from the start.

If I wrote code, errors would appear.

If I fixed one thing, something else would stop working.

When I thought it was working well, it would behave in ways I hadn't anticipated.

I started over many times.

Even so, by consulting with AI and moving forward one step at a time, it gradually took shape.

From this experience, I realized one thing.

Work that involves creating from scratch is not about producing a finished product from the beginning.

Build small.

Try running it.

Find the problems.

Fix them.

It is through this repetition that you get closer to the finished product.

I learned a wide range of Web marketing and acquired perspectives beyond just 'building'

Learning Web marketing also led to a major change.

Until then, my focus tended to lean toward the perspective of 'how to build' a website.

However, as I learned about ad operations, data analysis, SEO, and sales copywriting, I began to adopt a perspective of 'how to connect to results after creation'.

For example, when creating an LP, just making it look good is not enough.

Who is it for?

What kind of problems do they have?

What should I convey to get them interested?

What action do I ultimately want them to take?

It is necessary to think about the required elements by working backward from these objectives.

By learning across various fields, I have become able to have an awareness of thinking from 'why we are creating it' and 'who we are creating it for', rather than just 'what to create'.

I couldn't get my work done because I was aiming for 100 points right away

Through various challenges, I also realized a major reason why I couldn't get my work done before.

That was trying to submit a 100-point deliverable from the very beginning.

From the moment I received a request, I felt I had to create something with a high degree of perfection.

There must be no mistakes.

There must be no omissions.

That is what I believed.

However, you cannot produce a 100-point result from the start on a job where the final form is not yet visible.

Even so, when you try to aim for 100 points, you lose track of how far you need to research.

The scope of thinking expands, you become unable to make decisions, and your hands stop.

In other words, while I intended to be careful, I was actually making the work difficult for myself.

First, shape it to 60 percent, and then increase the level of perfection through reviews

Currently, instead of aiming for 100 points from the start, I am conscious of first giving it shape, even if it's only 60 percent complete.

Of course, this does not mean submitting something half-baked.

I organize the content I can think of at the moment and create a preliminary version.

Then, I check it with my superiors and stakeholders.

"Is this direction correct?"

"Are there any missing perspectives?"

"Is there any issue with this understanding of the priorities?"

By receiving reviews at an early stage like this, I can reduce the possibility of heading in the wrong direction.

Also, because I can get concrete feedback from others, it becomes clear what I should revise next.

I used to be resistant to showing things that weren't finished.

However, now I believe that reviews are not something you receive after completion, but something you receive in order to complete it.

Changed AI from a 'tool to provide answers' to a 'partner to organize thoughts'

Another thing that has changed significantly is how I use AI.

Previously, I tried to get AI to provide finished answers.

But now, I use AI as a consultation partner to organize my own thoughts.

For example, when I receive a vague request, I consult it as follows:

"What items are necessary to proceed with this request?"

"Please organize the things that should be confirmed first."

"Are there any missing perspectives in this approach?"

While looking at the items generated by the AI, I judge for myself whether they are necessary.

In other words, it is not about leaving the work to AI, but rather having it provide a starting point for your own thinking.

It is easier to advance your thinking when you have a draft to work from, rather than trying to think from scratch on your own.

Identify the necessary items and bounce your own ideas off the AI

After having the AI identify the necessary items, write down your own thoughts for each one.

"This is what I think."

"Looking at this data, I think this way."

"However, information is lacking in this area."

"This part requires confirmation with the stakeholders."

In this way, you can organize what you know and what you do not yet know.

Furthermore, bounce those thoughts off the AI.

"Do you find anything strange about this way of thinking?"

"What kind of opinions would there be from the opposing perspective?"

"Will this explanation be understood by the other party?"

By repeating this interaction with the AI, I have become able to notice the weak points in my own thinking and areas where my explanations are insufficient.

The important thing is not to use the AI's answers as they are.

It is to put your own thoughts into words through dialogue with the AI.

Do not use AI responses as they are; coordinate with external parties or superiors

AI is convenient, but its answers are not always correct.

Also, in actual work, there are conditions that cannot be judged by AI alone, such as company policy, on-site circumstances, budget, and schedule.

Therefore, I do not treat the content organized with the AI as a final decision.

Ask for opinions from external partners as needed.

Confirm technical details with someone who is knowledgeable.

Ultimately, align my understanding with my supervisor.

I am mindful of this process.

For me, AI is not an entity that decides the correct answer.

It is an entity that helps me form my own ideas and prepare for discussions with stakeholders.is what it is.

AI, myself, external opinions, and my supervisor's judgment.

I combine each of these to solidify the direction of my work.

Rather than stopping at 'I don't know,' consult with a hypothesis in mind

In the past, when there was something I didn't understand, I would sometimes just say, 'I don't know.'

Of course, there is no need to pretend to understand something you truly don't.

However, asking a question without thinking versus asking with a hypothesis of your own changes both the impression you give to others and the answers you receive.

Currently, I am mindful of organizing my thoughts as follows before consulting with others.

'At this point, this is how I understand it.'

'I am thinking of proceeding in this way.'

'However, I am not confident in this part of the judgment.'

'I would like to confirm if my understanding is correct.'

By communicating in this way, it becomes easier for the other person to provide a concrete answer.

And I, myself, can learn the way of thinking rather than just being told the answer.

Instead of hiding 'I don't know,' show it along with the process of your thinking.

I feel this is an essential mindset for moving work forward.

Work from scratch is not about guessing the right answer, but about giving it shape.

Work that starts from zero sometimes doesn't have a correct answer prepared from the beginning.

Therefore, trying to get the right answer on the first attempt becomes painful.

What is needed is to form a hypothesis.

To give it a small shape.

To confirm with stakeholders.

To make revisions.

And then, to confirm again.

Through this repetition, what was initially vague gradually becomes concrete.

Come to think of it, website production is the same.

A finished design does not just appear out of nowhere.

We organize requirements, create a structure, make a rough draft, receive reviews, and complete it while making revisions.

The way of proceeding with work itself was the same as that.

Once I let go of the desire to aim for perfection, my approach to work changed.

I used to be afraid of showing my inability.

So, I wouldn't show it to anyone until it was somewhat complete.

I would research more before asking questions.

I wouldn't submit anything until I found the right answer.

However, that attitude cornered me and became the cause of stalling my work.

Nowadays, even if it's not perfect, I try to give it shape once.

When I don't understand something, I ask questions based on a hypothesis.

I form my own ideas while also borrowing the power of AI and external resources.

And then, I increase the level of completion through reviews.

I am conscious of this flow.

Of course, I still sometimes feel lost in work that requires starting from scratch.

Even so, I feel less like I'm 'stuck because I don't know' than I used to.

If you don't know, try organizing it first.

If you can't organize it, try consulting an AI.

Once you have a hypothesis, try bouncing it off someone.

Being able to think this way has been a major change for me.

Summary | 'I don't know' is not a word to stop work, but a signal to start

Although I have learned various tools and production methods as a Web Director, for a long time, I had a sense of weakness in assembling work from scratch.

I don't know what I should research.

I don't know where I should start.

I can't move because I can't see the correct answer.

The trigger for escaping that state was taking on challenges in fields I had no experience in, such as AI, Python, and Web marketing.

What I learned there is that there is no need to aim for 100 points from the start.

First, try to give it shape, even if it's only 60 percent.

Use AI to organize the necessary items.

Put your thoughts into words.

Present them to others or your superiors to align on the direction.

Through this repetition, vague ideas gradually take shape.

Feeling like you 'don't know' is not inherently bad.

The important thing is not to stop there, but to think about what you can do next to move forward just a little bit.

Now, I have come to accept 'I don't know' not as words that stop work, but as a signal to start it.

A message to the reader

Have you ever had the experience of your work coming to a halt because you were faced with a task where the correct answer wasn't visible, or you received a vague request?

In such cases, it is okay not to try to create a perfect answer right away.

First, write down the items that seem necessary.

Consult with AI to create a starting point for your thinking.

Summarize your own hypothesis.

And then, show it to someone when it is 60% complete.

Once you give it shape, even if it is small, you will see what needs to be corrected next.

Perhaps the moment you feel 'I don't know' is actually a chance to acquire a new way of thinking.

When you face a task you don't understand, how do you take that first step?

Please take a moment to reflect on your own way of dealing with it.