Let domain experts share powerful AI systems without exposing their intellectual property.

Hello OpenAI Team,

I am a solo business operator in South Korea, running a wellness business built around Nu Skin/Pharmanex products.

Over nearly two years, I have moved from GPT to Gemini to Claude and back to GPT, trying to figure out how AI could actually become part of my business — not merely as a chatbot, but as an operating system.

After countless hours of trial and error, I have built something that now works.

Inside GPT, I have developed profile instructions, domain-specific operating rules, Skills, product databases, evidence-grading frameworks, project knowledge, consulting logic, and report templates. Together they allow GPT to consistently follow the scientific, regulatory, and business framework I have developed for my field.

That experience taught me something important about the future of AI.

AI is easy to chat with. It is still extremely difficult for a non-developer to turn AI into a reliable business operating system.

Most ordinary businesspeople do not want to become AI engineers.

Expecting hundreds of millions of self-employed people, freelancers, consultants, coaches, salespeople, and small-business owners to study advanced prompting, agent architecture, APIs, coding, Skills, knowledge management, and AI workflows is similar to expecting all computer users to become software developers.

They will not.

And they should not have to.

What they need is not necessarily the ability to build sophisticated AI systems themselves.

They need access to sophisticated AI systems built by someone who understands their industry.

That distinction creates what I believe is a very large opportunity for OpenAI.

In every industry, there are a small number of people who are willing to spend hundreds or thousands of hours learning how AI works while also bringing years or decades of real domain knowledge.

A developer may understand software extremely well, but cannot be expected to understand every industry’s unwritten rules, customer psychology, workflows, regulations, sales processes, professional judgment, and accumulated field experience.

Domain experts have the opposite problem.

They understand their industries deeply, but most cannot code.

Generative AI has created a historic bridge between these two worlds.

For the first time, a non-developer domain expert can gradually teach an AI how their business works and build something close to a specialized operating system.

But there is currently a missing distribution layer.

My problem is a simple example

My business is network marketing.

I do not truly succeed unless my business partners succeed.

Therefore, if I spend two years developing an AI system that makes me more capable, my ultimate goal is not to keep it to myself.

I want every partner I recruit to be able to use the same system at 100% capacity, even if they know almost nothing about AI.

They should not have to spend two years repeating what I did.

That is the entire point of replication.

But I also cannot simply hand over everything I have built.

My instructions, Skills, resolved business rules, knowledge structure, product logic, report systems, and workflows are intellectual property.

They are also one of my strongest recruiting advantages.

If I have to expose all of that source material in order to let someone use the system, then the moment I share my competitive advantage, I destroy the very advantage that made sharing valuable.

A partner can copy it, leave, reproduce it elsewhere, or give it to somebody else.

The rational result is obvious:

Creators keep their best AI systems private.

And when creators keep them private, AI does not spread through their networks.

This is not just an intellectual-property problem.

It is a distribution problem for AI itself.

The current alternatives do not solve it

Custom GPTs are useful, but for my use case they do not reproduce the full capability, project context, Skills, workflows, and operating environment that I can build and use directly inside GPT.

The API is not a realistic answer for people like me.

I am not a developer.

Using an API means learning or hiring for coding, building an interface, maintaining infrastructure, recreating functionality, handling updates, and operating a second system alongside the ChatGPT product.

That defeats one of the greatest advantages of ChatGPT for non-technical people: the ability to build increasingly sophisticated systems through natural conversation.

ChatGPT Business and current workspace sharing solve a different problem.

They are designed primarily around collaboration inside an organization.

What I need is distribution across independent operators.

My partners are not my employees. They are independent business owners.

They should have their own OpenAI accounts and pay for their own subscriptions.

I should control access to the AI system I created — not pay for and administer every user’s seat.

What I believe OpenAI is missing

I would call it a Protected AI Distribution Layer, or perhaps a Licensed Agent Network.

Think of it as a franchise model for AI expertise.

The principle is simple:

The right to use an AI system should be separable from the right to inspect or copy the intellectual property that created it.

Software users can run software without receiving its source code.

AI should be able to work the same way.

The owner or creator would build:

OpenAI would provide a protected execution layer around them.

The licensed user would then:

  • Use the full behavior of the system

  • Use it through their own OpenAI account

  • Pay for their own ChatGPT subscription

  • Receive updates when the creator improves the system

  • Never need to understand how the underlying AI system was built

But the licensed user could not:

  • View the protected instructions

  • Open or export protected Skill source

  • Download protected knowledge files

  • Extract the system through the UI

  • Ask the model to reveal protected source instructions or content

  • Transfer access to another person without authorization

The creator would have:

  • Grant-access controls

  • Immediate revocation

  • Version management

  • Central updates

  • User/group management

  • Basic usage analytics

In other words:

Build once. Protect once. Distribute many times.

Why I believe this could create a very large market

This is not only about network marketing.

ILO data indicate that nearly half of the world’s employed population is self-employed.

The global direct-selling industry alone has approximately 104 million independent contractors according to WFDSA.

And skilled freelancers are already adopting AI rapidly. Upwork research has reported that 62% of skilled freelancers use AI tools regularly in their workflows.

Not all of these people will become sophisticated AI builders.

That is exactly the point.

They do not need to.

Imagine that within each profession or business community, only a very small percentage of people become serious AI system builders.

One real-estate professional builds an exceptional AI operating system for real-estate agents.

One insurance expert builds one for insurance advisers.

One fitness professional builds one for trainers.

One beauty professional builds one for beauty consultants.

One marketing expert builds one for agencies.

One direct-selling leader builds one for their organization.

One consultant builds one for other consultants.

Those creators could then recruit, train, or serve hundreds or thousands of ordinary people in their own industries.

Those users would not be buying “AI technology.”

They would be buying the ability to do their existing work better.

And if using that professionally designed AI system required an individual ChatGPT subscription, I believe many of them would readily pay the current Plus-level price rather than spend months or years trying to become AI experts themselves.

This creates a fundamentally different growth model:

One expert learns AI deeply.
That expert creates a system for an industry.
Ten people adopt it.
Those ten introduce it to one hundred.
One hundred become one thousand.

Because AI systems can be distributed digitally and updated centrally, this kind of replication can happen extremely quickly.

The missing ingredient is trust.

Creators must know that distributing their system does not mean surrendering their intellectual property.

Intellectual-property protection is not merely a security feature

I believe this is the most important point in my proposal.

IP protection would create an economic incentive for domain experts to distribute their best AI systems instead of hiding them.

Without protection:

Creator builds valuable AI system
→ sharing exposes the source
→ creator keeps it private
→ users never receive it
→ AI adoption remains shallow.

With protection:

Creator builds valuable AI system
→ OpenAI protects the source
→ creator safely distributes it
→ independent users subscribe individually
→ users become more successful with AI
→ the creator expands the network
→ more users subscribe.

The protected layer therefore becomes not only an IP feature.

It becomes an AI distribution engine.

OpenAI has already made AI extraordinarily accessible at the conversational level.

I believe the next opportunity is to make advanced AI capability accessible without requiring everyone to become an advanced AI builder.

The answer is not to turn hundreds of millions of domain experts and small-business owners into developers.

The answer is to let a relatively small number of domain experts build excellent AI systems — and safely distribute those systems to everyone else.

I have spent almost two years trying to solve this problem for my own business.

I suspect I am far from the only person who has reached this wall.

If OpenAI creates the layer that separates AI system ownership from AI system usage, it could unlock an entirely new market between individual ChatGPT subscriptions and traditional enterprise workspaces.

I hope you will consider it.

Thank you for reading.

KIM HAKSOO
South Korea