AI Builders: You May Not Have a Building Problem. You May Have a Fog Problem.
ai · October 24, 2026
AI has made it easier than ever to build something.
AI has made it easier than ever to build something.
That may also be the problem.
An app.
A website.
An automation.
An AI employee.
A chatbot.
A dashboard.
A SaaS product.
A new tool somebody showed you on YouTube yesterday.
You can go from:
"I have an idea."
to:
"Look what I built."
faster than at almost any point in history.
But there is a question AI cannot answer for you simply by making development easier:
Should you have built it?
That is where I think a lot of AI builders are getting stuck.
Not because they cannot build.
Because they are building through fog.
Building Is No Longer the Hard Part
For years, technical ability created a natural barrier.
You needed developers.
Money.
Time.
Infrastructure.
Specialized knowledge.
Today, a person with an idea and the right AI tools can create something surprisingly sophisticated.
That is powerful.
It is also dangerous.
Because when the barrier to building disappears, the barrier that remains is judgment.
What problem are you solving?
Who actually has that problem?
How painful is it?
Who will pay to solve it?
Are they already paying someone else?
Does your solution actually improve what exists?
Can you support it after launch?
Can you protect the information people put into it?
Is it ready for a real customer?
Those questions are less exciting than generating another application.
They are also the questions that determine whether you are building a business or collecting projects.
Busy and Productive Are Not the Same Thing
AI builders can stay incredibly busy.
New models.
New tools.
New frameworks.
New agents.
New automation platforms.
New ideas.
Every week brings something else worth experimenting with.
That can create the illusion of progress.
You built five things.
None are finished.
You bought eight domains.
None have customers.
You created three SaaS concepts.
Nobody has paid for one.
You redesigned the website.
Again.
Sometimes the problem is not your ability to execute.
Sometimes you are executing too many things that never should have survived the idea stage.
Activity is not traction.
The Fog Usually Appears Before the Build
This is why I created The Fog Check: AI Builder Edition.
The idea is simple.
Before building another thing, check the visibility.
Ask yourself:
What exactly am I building?
Who is it for?
What problem does it solve?
Why would somebody pay?
What evidence do I have that they care?
What happens when the project is finished?
What does "finished" even mean?
That last question deserves more attention.
Because a project can technically work and still not be ready for a real customer.
"It Works" Is a Very Low Standard
This may become one of the biggest challenges in the AI-building era.
The button works.
The automation runs.
The chatbot answers.
The payment processes.
The website loads.
Great.
Now what?
Did you review accessibility?
Privacy?
Security?
Data collection?
Third-party scripts?
Terms?
Disclosures?
Error handling?
AI-generated output?
What happens if the model gives the wrong answer?
Who owns the data?
Can the client export it?
What happens when an API changes?
What happens when the AI provider changes a model?
What happens when the original builder disappears?
A working demo and a client-ready system are not the same thing.
The next generation of AI builders should not be measured exclusively by what they can create. They should also be measured by what they were responsible enough to anticipate.
That Is Where Assurance Enters the Conversation
I think the AI-building industry is approaching another stage.
The first stage was:
Look what AI can build.
The next stage has to become:
How do we know what we built is ready?
That is why I have been thinking differently about tools such as CavScope.
Not as something you use after everything goes wrong.
As part of the building process.
Build.
Then check.
Review the public-facing website.
Review risk.
Review accessibility indicators.
Review privacy signals.
Review AI disclosures.
Review what evidence you can actually provide to the customer.
The question becomes:
What did you verify before you handed this to somebody who paid you?
That is a much more mature AI-building conversation.
There Is Another Kind of Fog: The Customer
Some builders know exactly what they can create.
They have no idea who they are selling it to.
That is a business problem.
"I built an AI scheduling system."
For whom?
"I created an AI employee."
Doing what?
"I have a CRM."
Why would someone leave the one they already use?
"This saves time."
How much?
Whose time?
Doing what task?
How often?
What does that time cost?
The more specific you become, the easier it is to see whether there is actually a business underneath the technology.
Stop Building for People Who Have Not Asked
This one can hurt.
Sometimes we fall in love with the solution before confirming the problem.
We convince ourselves:
People need this.
Businesses need this.
Coaches need this.
Small organizations need this.
Maybe.
Have they told you?
Have they paid for anything similar?
Have they tried solving the problem another way?
Are they frustrated enough to change?
A product nobody wants does not become better because you added AI.
Technology cannot create demand where demand does not exist.
Then There Is the Shiny-New-Thing Problem
AI makes this especially difficult because there is always something new.
You can abandon yesterday's idea because today's technology suddenly looks more exciting.
Then tomorrow arrives.
Another model.
Another platform.
Another opportunity.
Another build.
Eventually your portfolio becomes a museum of unfinished potential.
At some point the discipline has to become:
Finish before build.
Complete what has commercial relevance.
Get it in front of people.
Collect feedback.
Sell it.
Improve it.
Or deliberately kill it.
But stop allowing unfinished projects to quietly become permanent inventory.
Are You Building for Now or Building for the Future?
This may be the most important question.
A system can work today and still be badly designed for tomorrow.
Models change.
APIs change.
Regulations change.
Security threats change.
Accessibility expectations change.
Customer expectations change.
Your company grows.
The client's company grows.
Suddenly the shortcut that helped you launch quickly becomes technical debt somebody has to fix later.
Building for the future does not mean predicting everything.
It means recognizing that responsible design includes what happens after launch.
Who maintains it?
Who monitors it?
Who documents it?
Who updates it?
Who owns the process?
Who knows what to do when something breaks?
That is not as exciting as the demo.
It is what separates a demo from a system.
Maybe You Do Not Need Another Tool
Sometimes the fog tells you that you need another platform.
Another course.
Another certification.
Another AI model.
Another subscription.
Another framework.
Maybe.
Or maybe you already have enough tools.
Maybe the issue is clarity.
What are you finishing?
What are you selling?
Who are you serving?
What are you stopping?
That last question may be the hardest one.
AI dramatically expanded what we can build.
It did not increase the number of hours in the day.
It did not eliminate the need for focus.
It did not guarantee customer demand.
It did not remove responsibility.
And it certainly did not make every idea a good idea.
The Fog Check
So before the next build, ask:
Am I solving a real problem?
Can I identify the customer?
Will somebody pay for this?
Do I have evidence?
Am I finishing what I already started?
Is this ready for a real client, not just a demo?
Have I considered the risks created by what I built?
Can somebody besides me operate it?
Am I building for today or building something capable of surviving tomorrow?
And maybe most importantly:
Am I building a business, or am I just enjoying building?
There is nothing wrong with building for fun.
Experiment.
Learn.
Break things.
Try new technology.
But call it what it is.
The problem begins when experimentation gets confused with entrepreneurship.
Because AI may have removed a lot of barriers to building.
It did not remove the fog.
And sometimes the next thing an AI builder needs is not another build.
It is enough clarity to decide what deserves to be built at all.
The Fog Check: AI Builder Edition
If you are building websites, applications, automations, AI employees, or digital products and want to examine what may be hiding inside the fog:
https://anthonywashingtonsr.com/fogcheck/ai-builders
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