“What Should We Do So AI Can Read Our Site?” — Start With the Basics Before Adding llms.txt

“I asked ChatGPT about our company, and the answer was a little strange.”

Lately, we’ve been hearing more comments like this from people responsible for running company websites.

The conversation used to start with search rankings.

“Where do we rank?”
“How can we improve SEO?”
“Which page should we optimize next?”

Those questions still matter. But now, another layer of concern is being added.

“When someone asks an AI, does our site get used?”
“Will AI ignore us if we don’t prepare something special?”
“Do we need llms.txt, AI markup, or structured data?”

When new terms appear, it is natural to feel that something must be added right away. A file, a tag, a markup, a checklist item. Something that makes the team feel covered.

But when Google Search Central published guidance on optimizing for generative AI features, the message was simpler than many expected.

Before rushing to add something new, first check whether the site itself can be read properly.

In this article, we’ll look at why this concern is increasing, what Google has said, and what website teams can do first to keep their content readable for both users and AI.

Why “AI Optimization” Feels So Confusing Right Now

The confusion around AI optimization does not come from one single tool or one single file.

It comes from a shift in how people look for information.

Background 1: The Worry Has Moved Beyond Search Rankings

For a long time, website operations were closely tied to search rankings and organic traffic.

That has not disappeared. SEO still matters.

But users now ask questions in more places. Some ask ChatGPT or another generative AI tool before visiting a website. Some use AI answers as the first step in comparing companies, products, and services.

That changes the anxiety for website teams.

It is no longer only:

“Are we ranking?”

It is also:

“Are we being understood correctly?”
“Is our site being used as a source?”
“Is outdated or broken information affecting how we appear?”

Unlike a search ranking, an AI answer is not something a website owner can directly control. That makes it tempting to look for a clear, concrete action that feels like an answer.

Background 2: New Terms Quickly Become New To-Dos

llms.txt.
AI-oriented markup.
Structured data.

Once these terms start circulating, they often get added to the operations list before the team has had time to confirm what they actually do.

That is understandable. Website teams already have a lot to handle: page updates, SEO settings, analytics tags, landing page improvements, form checks, content revisions, and reporting.

So when “AI optimization” enters the conversation, it can feel safer to add everything.

But Google’s guidance draws an important line.

According to the guide, you do not need to create new machine-readable files, AI text files, or special markup to appear in Google Search, including its generative AI features. Files like llms.txt may be kept for other services, but Google does not reference them. Structured data is also not required for generative AI search, although it can still be useful for rich results and other search features.

In other words, generative AI optimization is not completely separate from ordinary website operations.

It sits on the same foundation: content quality, readability, and a site that can actually be understood.

The Practical Steps to Take First

If the goal is to make your website easier to read and trust, the first step is not always adding something new.

It is checking whether the existing site is in good condition.

Here is the process we use in the field.

STEP 1: Make the Current Site Condition Visible

Start by checking whether the content on the site can be read properly.

That means looking for issues such as:

• Broken links
• Broken images
• Missing measurement tags
• Empty SEO titles or descriptions
• Typos
• Inconsistent wording across pages

None of these are flashy AI tactics.

But they matter.

If a service page has a broken link, users may not reach the information they need. If an image is missing, the page may lose important context. If a tracking tag is missing on only one page, the team may not understand what happened after users visited. If a title or description is empty, the page may be harder to interpret in search.

And if typos or inconsistent wording change the meaning of a page, the content becomes less clear for both people and machines.

Before adding llms.txt or another AI-related file, it is worth checking whether these basics are already stable.

MONJI+ can help teams crawl an entire website and find issues such as broken links, broken images, and typos. For teams that do not want to rely only on manual checking, MONJI+ provides a way to make these issues visible across the site.

STEP 2: Turn Issues Into a Monthly WebOps Workflow

Finding an issue is only the first half.

The harder part is making sure it gets fixed.

In website operations, problems often get lost between discovery and completion.

A broken link is noticed, but no one knows who owns it.
A typo is shared in chat, then disappears in the flow of messages.
A missing tag is reported, but later no one knows whether it was actually fixed.

That is why issues should be recorded and managed as part of a monthly workflow.

For each issue, it helps to track:

• Which page it appeared on
• What the issue is
• Who is responsible
• When it should be handled
• Whether it has been fixed

This turns website maintenance from occasional cleanup into an ongoing operation.

In our own work, we do not stop at spotting issues. We turn them into Feedback, assign an owner and a due date, and move them toward a fix.

It is plain work. But it is often the work that keeps a site from slowly falling apart.

STEP 3: Check the Numbers After the Fix

Once issues are fixed, the next step is to look at the numbers.

A fix should not simply disappear into the task list.

When possible, compare the fixes with traffic and other key metrics over the following months.

For example:

• Did traffic change on pages that were fixed?
• Did pages with improved SEO settings behave differently?
• Did users move through the site differently after broken links were repaired?
• Are the number of recurring issues decreasing month by month?

Of course, one fix does not explain everything.

Search performance and AI visibility depend on many factors. It would be too strong to say that fixing one typo or one broken link directly caused a specific result.

But when fixes and numbers are reviewed together, the team can make better decisions about where to check next.

With MONJI+, teams can view key metrics for each project alongside Google Analytics data. That makes it easier to review what happened after a fix and connect site maintenance with ongoing improvement.

What Actually Changes When the Basics Are Maintained

We cannot decide whether an AI system will pick up a website.

But we can improve the preconditions.

When a site has fewer broken links, missing images, missing tags, SEO gaps, and typos, its content is easier to read and interpret.

In practice, the changes are often simple:

• Important links lead where they should
• Images that provide context are visible
• SEO titles and descriptions are not left empty
• Tracking tags are less likely to be missing from individual pages
• Wording is more consistent across the site
• Issues are assigned to someone instead of being left as vague observations
• Fixes can be reviewed later with traffic data

None of this feels dramatic.

But if the goal is to help users and AI understand the site correctly, these basics are hard to skip.

The more attention AI optimization receives, the more tempting it becomes to chase the newest tactic. But in the field, the work that pays off first is often much more ordinary: keeping the website readable.

Notes and Limitations

There are a few limits worth stating clearly.

First, maintaining the site properly does not guarantee that your company will appear in an AI answer.

What a website team can do is prepare the content so that it can be read correctly. How an AI system chooses, interprets, or uses that information is not something the site owner can fully control.

Second, not every type of content can be checked in the same way.

For example, text baked into images is outside the normal scope of typo checking. Copy inside banners, screenshots, and visual materials still needs a separate human review process.

Third, structured data is not meaningless.

It can still be useful for rich results and other parts of search. The point is not that structured data should never be used. The point is that it should not be treated as a required shortcut for appearing in generative AI features.

The order matters.

Before adding files or markup because they sound AI-ready, first make sure the site itself is not broken, incomplete, or difficult to read.

MONJI+, a WebOps Platform Built From the Field

Whether AI reads your website correctly will only become a bigger concern from here.

That is exactly why the less flashy work matters: keeping the preconditions for being read from breaking down.

MONJI+ is a WebOps platform that crawls the whole site to find broken links, missing pieces, and typos, then turns them straight into Feedback so teams can carry them through to a fix.

The after-the-fix numbers can be checked in the same place too, alongside Google Analytics.

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Summary

As AI search and generative AI tools become more common, more teams are asking how their websites are being read.

But the first answer is not necessarily to add llms.txt, AI-specific text files, or special markup.

Google’s guidance makes clear that those are not required for appearing in its generative AI features. Instead, generative AI optimization sits on the same foundation as ordinary search and website quality.

That means the basics still matter.

Broken links, broken images, missing tags, empty SEO settings, typos, and inconsistent wording can all get in the way of clear understanding.

Humans should focus on the part only humans can supply: real experience, accurate information, original context, and the reason something can be said.

Tools can help watch for the issues that quietly damage that content.

We cannot decide whether AI will pick us up. But we can prepare the site so that, when it is read, it can be understood correctly.

That is why maintaining the ground beneath the content is not a detour.

It is the shortcut.