The Core of Expert Content Is Changing

In its familiar form, expert content is something nobody gives a damn about anymore.

Not because experts have become irrelevant, but because an AI now stands between a person and virtually any body of knowledge.

Suppose I am a marketer preparing yet another expert post: “10 Ways to Increase Website Conversion.”

Why the hell should anyone read me specifically? They can open ChatGPT and get not 10 but 50 ideas in 30 seconds. Ask it to explain each one. Ask for examples. Filter the answer for B2B. Then for construction. Then for a company with RUB 300 million in revenue.

They can upload their website and ask: “Now tell me which of these ideas actually applies to my business.” And get an answer.

AI does not get tired. It is not lazy. It does not need to stretch one thought into 15 posts just to fill a content plan.

The smarter models become, the less reason people have to follow dozens of “experts” and collect fragments of knowledge that a machine can gather, structure, and adapt to their situation in minutes.

But there is one problem. AI knows a great deal, yet it has not lived through your specific challenge.

You have. This is where the core value of content begins to shift.

The old value proposition was: “I know something you do not.” That advantage is rapidly approaching zero.

The new one is: “I have already done what you are about to do.”

AI cannot take that away yet.

So instead of “How to Implement AI in Business Correctly,” I am far more interested in: “We implemented AI here. This was the problem. This is what we did. This is where we fucked up. This is what we had to rebuild. And this is the result.”

Instead of another general article titled “How to Speed Up Development with AI,” I want a breakdown of the actual process.

That means showing the substance:

• which model was used;
• which plugins;
• which skills;
• how the pipeline was structured;
• which tools connected everything;
• where a person intervenes manually;
• what proved useless;
• what actually worked.

And, if you can, share the tools themselves.

Here is the skill’s .md file. Here is the instruction. Here is the prompt. Here is the repository. Here is the plugin. Here is the sequence of actions.

Take it and use it.

This creates an interesting paradox.

The more knowledge AI makes universally available, the more valuable someone else’s lived experience becomes.

People no longer need another textbook. They need a clue about which path someone has already travelled and how to avoid figuring everything out from scratch.

They do not want to repeat the journey, spend hours talking to a model, test every approach, retrain five skills, assemble four broken pipelines, or step on the same rakes.

What matters is the transfer of a shorter path.

A guy teaching entrepreneurs can no longer get away with explaining how to break through some imaginary ceiling or manage people.

Show the facts:

who you hired, who you fired, what you bought, what you sold, what you changed, how much it cost, and what happened to cash flow.

I can ask a machine for the general theory now.

But the machine has not lived your life.

I do not think expert content is dead.

What died is the expert’s monopoly on knowledge.

Experts will have to stop proving that they know a lot. Now they will have to prove that they have done a lot.

The classic formula of “70% expert content” may not disappear at all. The definition of expert content itself is what will change.

Knowledge → experience.
Theory → case studies.
Advice → results.
“The right way” → “the way I did it.”
Information → ready-to-use tools and a shorter path for someone else.

That, in my view, is the core that is changing now. And the smarter AI becomes, the faster the shift will happen.