For years, one of the standard ways to build a niche website was to look for keywords, write articles around those keywords, and hope Google sent traffic.
That model is changing.
Google is no longer just showing a list of blue links. More and more searches now include an AI Overview, which gives the searcher a quick summary directly on the results page. In many cases, that summary may be enough.
If someone searches for a simple definition, a basic explanation, or a quick fact, they may not need to click through to a website at all.
That sounds worrying for website owners, bloggers and affiliate marketers. And in some ways, it is.
But I do not think the lesson is that websites have no future.
I think the lesson is that ordinary, generic, easily repeated content has a much weaker future.
The opportunity now is not just to answer questions. The opportunity is to find where the AI answer is useful but incomplete.
That is the new content gap.
What Is Unique Non-Commodity Content?
Google has talked about the importance of creating unique, non-commodity content.
That phrase sounds a bit technical, but the idea is simple.
Commodity content is content that could be produced by almost anyone.
It is the sort of article where someone could read the top few Google results, ask AI to rewrite them, add a few headings, and end up with something very similar.
For example:
- “What is vibe coding?”
- “Best beginner telescope”
- “How to fix a car scratch”
- “What is affiliate marketing?”
- “Best scratch remover products”
- “How does an air fryer work?”
There is nothing wrong with answering those questions. The problem is that if the page only gives the same general information as everyone else, it becomes very easy for an AI Overview to summarise.
Unique non-commodity content is different.
It contains something that is not easily copied from existing results.
That might be:
- personal experience
- original examples
- screenshots
- photos
- case studies
- product testing
- mistakes learned from experience
- a real project walkthrough
- a decision chart
- a checklist
- expert input
- a strong opinion based on evidence
- practical judgement
- before-and-after examples
In other words, commodity content gives information.
Non-commodity content gives insight.
Commodity content answers the question.
Non-commodity content helps the reader make progress.
A Simple Test for Any Article
A useful test for any article is this:
Could someone create almost the same article by reading the top few Google results and asking AI to rewrite them?
If the answer is yes, the content is probably vulnerable.
That does not automatically mean it is bad. It may still be accurate. It may still be readable. It may still answer the question.
But it may not have much reason to exist beyond being another version of the same information.
That is the danger.
A lot of older affiliate content was built this way. The process was often:
- Find a keyword.
- Read the pages already ranking.
- Summarise the same points.
- Add a comparison table.
- Add affiliate links.
- Publish.
That model worked better when Google’s job was mainly to send people to websites.
But if Google can now summarise the common information directly in the search results, the website has to offer something more.
The new question is not simply:
Can I write an article about this keyword?
The better question is:
What can I add that would still make this page worth visiting after the AI Overview has already given the searcher the basic answer?
That is where the real content opportunity is now.
The Vibe Coding Example
The search term “vibe coding” is a good example because it shows how the depth of the user’s need can escalate.
Imagine someone searches:
What is vibe coding?
An AI Overview can probably answer that fairly well.
It might explain that vibe coding is a way of building software by describing what you want in natural language and using AI tools to generate or edit the code.
For many people, that basic answer may be enough.
But now imagine the searcher goes a little deeper:
How does vibe coding work?
Again, an AI Overview may provide a useful summary. It might explain that the user gives prompts, the AI creates code, the user tests it, gives more instructions, and gradually builds or changes the project.
Still useful.
But then the searcher may ask:
Is vibe coding good for beginners?
Now the answer becomes more complicated.
The person may need to understand the benefits, risks, limitations and learning curve. They may want to know whether they need coding knowledge, what happens when the AI creates errors, and how much they can realistically build without understanding the underlying code.
Then the searcher may go deeper again:
How do I build an app with vibe coding?
Now we are no longer dealing with a simple explanation.
The searcher may need:
- a beginner-friendly project idea
- a recommended tool
- the first prompt to use
- screenshots of the process
- examples of generated code
- a walkthrough of the project structure
- common errors
- debugging steps
- what to do when the AI gets stuck
- what the finished app looks like
- what the human still had to decide
An AI Overview might still give a general answer. But it cannot easily replace a full project walkthrough.
Then we get to an even deeper search:
Show me a full vibe coding project from idea to working app.
That is where a website, video, course or detailed tutorial becomes much more valuable.
The AI Overview can explain the concept.
A helpful resource can demonstrate the process.
That is the difference.
The Escalation of Search Intent
This is the important pattern:
| Search query | What the user needs | AI Overview likely usefulness |
|---|---|---|
| What is vibe coding? | Basic definition | High |
| How does vibe coding work? | General explanation | High |
| Is vibe coding good for beginners? | Pros, cons and judgement | Medium |
| How do I build an app with vibe coding? | Practical guidance | Limited |
| Full vibe coding project walkthrough | Step-by-step demonstration | Much more limited |
| What went wrong when you tried vibe coding? | Real experience | Website or video needed |
This is where I think the future opportunity sits.
The shallow end of the topic is more easily handled by AI.
The deeper end still needs examples, insight, experience, demonstration and judgement.
This Applies to Many Niches
The same principle applies far beyond vibe coding.
Take car scratch repair.
An AI Overview can say:
- Clean the area.
- Assess the scratch.
- Use polish for light scratches.
- Use touch-up paint for deeper scratches.
- Protect the area afterwards.
That may be useful.
But if I am about to repair my actual car, I may still need much more than that.
I may want:
- photos of different scratch depths
- how to do the fingernail test
- when polish is enough
- when touch-up paint is needed
- what products to avoid
- what can go wrong
- when not to attempt it myself
- before-and-after examples
- a beginner checklist
- a cost comparison between DIY and professional repair
The AI answer gives the steps.
A helpful website gives the confidence.
Or take beginner telescopes.
An AI Overview can tell me that a beginner telescope may show Saturn’s rings.
But if I am actually going to spend money, I may want to know:
- what Saturn will realistically look like
- what aperture means in plain English
- why the mount matters
- what magnification claims to avoid
- which accessories are actually useful
- what budget makes sense
- what a beginner should buy if they mainly want the Moon and planets
Again, the AI Overview can give the gist.
A proper website can give the pathway.
The New Content Gap Analysis
Traditional content gap analysis was often about looking for keywords competitors ranked for that you did not.
That still has value, but I think we now need another layer.
The new content gap analysis is this:
- Put a search term into Google.
- Read the AI Overview.
- Ask what it covers well.
- Ask what it leaves out.
- Look at the websites below it.
- Ask whether any of them provide a truly complete resource.
- Look for the gap between the summary and the real help the searcher may still need.
You are not just looking for missing keywords.
You are looking for missing usefulness.
For example, after reading the AI Overview, ask:
- Does the answer give examples?
- Does it show photos or screenshots?
- Does it demonstrate the process?
- Does it include real experience?
- Does it help the reader make a decision?
- Does it explain what can go wrong?
- Does it include a checklist or decision chart?
- Does it show the beginner pathway?
- Does it help someone actually do the thing?
If the AI Overview gives a decent summary but the searcher would still need help applying the information, that may be an opportunity.
Try This Yourself
This is a useful exercise for anyone thinking about building a niche website.
Pick a topic you are interested in and search for something broad.
For example:
- how does vibe coding work
- can a beginner telescope see Saturn’s rings
- how do I know if a car scratch is too deep
- what air fryer size do I need
- how do I start balcony gardening
- best dart weight for beginners
- how do I organise craft supplies in a small room
Read the AI Overview carefully.
Then ask yourself:
If I were genuinely trying to solve this problem, would this answer be enough?
Sometimes the answer will be yes.
That is important to accept.
If the searcher only needs a simple answer, there may not be much opportunity for a website click.
But sometimes the answer will be:
This gives me the gist, but I still need more detail.
That is where the opportunity begins.
Now look at the websites ranking underneath.
Are they just repeating the same high-level points?
Or does one of them go much further?
Does it include original examples, images, product guidance, warnings, personal insight, screenshots, tools, checklists or a full pathway?
If not, you may have found a modern content gap.
The Future of Affiliate Content
This has big implications for affiliate websites.
Many old-style affiliate sites are likely to struggle because they do not have enough depth.
If the author does not understand the niche, has not used the products, has no experience, has no original images, and is only summarising information from elsewhere, the site becomes vulnerable.
AI can summarise generic information very quickly.
But that does not mean affiliate marketing is finished.
It means the standard is higher.
A strong affiliate site needs to be genuinely useful before it recommends anything.
It should help the reader understand the problem, compare options, avoid mistakes, and make a better decision.
The recommendation should feel like a natural part of the help, not the whole reason the page exists.
For example, a weak page says:
Here are the best AI coding tools.
A stronger page says:
I used these AI coding tools to build a simple app. Here is what worked, what broke, what confused me, and which tool I would recommend for different types of beginners.
That is much more useful.
It gives the reader something they could not get from a simple summary.
The Real Opportunity
The opportunity is not in producing more ordinary content.
The opportunity is in creating content that has a reason to exist even after the AI Overview has done its job.
That means going beyond the basic answer.
It means adding:
- examples
- experience
- judgement
- visuals
- tools
- demonstrations
- case studies
- mistakes
- comparisons
- personal insight
- practical next steps
The question is no longer:
Can I answer this search query?
The question is:
Can I create the resource someone wishes they had found after reading the basic answer?
That is the shift.
AI Overviews may reduce easy clicks.
They may answer many basic questions directly.
But they also reveal where the summary is not enough.
That gap between “I understand the gist” and “I know what to do next” is where helpful websites still have a future.