I’m a builder at heart.
It’s one of the reasons I gravitated toward computer science as a career. Building something and watching it work exactly as I defined still gives me that same immediate gratification.
From software to systems, I enjoy building things and taking them apart.
My first time with HTML and CSS was in a computer lab in my small town of Stoneham, Massachusetts: three computers, six seats, and a grumpy teacher who sat behind his desk.
With basic syntax, I could put pages on the internet and communicate ideas through color and layout. At sixteen, learning to center a div properly took real work. Building full sections of a page took hours. I cannot even begin to describe the drudgery of building multiple pages.
I had learned my first lesson in web development.
Less was more.
Today, the opposite is true for many websites. AI can produce a polished page in minutes, so the question becomes why not more?
The problems with AI-generated websites
To understand why websites are important especially for businesses, three core principles must be understood: purpose, design, and user experience.
- Purpose: What does the business do? Why is this product or service offered?
- Design: What does your business communicate beyond words? What emotions do you invoke in your prospects through color, fonts and layout?
- Experience: How are prospective customers interacting with your website? Is it difficult for them to engage or navigate?
Getting all three above right usually means higher conversion of customers when they visit your websites.
The emerging problem with AI-generated websites points to one thing. None of these principles are being adhered to.
AI website builders like Lovable, Base44, and the others all compress a build that once took weeks into a conversation that takes minutes. When this happens, the ability to make careful decisions often disappears or is handled on the fly through prompt iterations. Lovable is one company that makes that distinction clear.
The result is often incomplete, beautiful websites that are invisible to the whole internet. These websites usually lack basic SEO setup. Search engines such as Google cannot read most of them.
It is nearly impossible for a user without expertise in SEO to realize this and the impact for a business can be severe.
Consider a car. Its body may look complete, but without an engine it cannot move. Similarly, a website that cannot be crawled fails at the first principle: purpose. If the business cannot be found, the website cannot do the one job it exists to do.
The other problem is design.
Landing pages have grown long and verbose enough to feel like filler. Colors and fonts now look generic and similar. A website exists to convince a customer that the business is capable and different. Verbose text packed with irrelevant keywords does the opposite.
Underneath both problems sits an expertise gap. AI is a precise executor of tasks. If the task is framed with little expertise, the result is a website with none.
None of this makes AI website builders useless. They work well for testing an idea. For businesses that depend on being found, each broken principle becomes a cost.
The cost of AI slop on businesses
From what I have seen so far, these problems matter most to new service businesses, because visibility is part of the sales process. A moving company, a local restaurant, a consultant, or a home-service provider needs pages that match the way people search.
A page that says “quality solutions for your needs” may sound pleasant, but it does not tell a prospective customer or a search engine what the business does, where it works, or why a customer would choose it.
A website that has a generic design looks incapable and lazy. A visitor who has seen two of these sites recognizes the third one immediately. Same hero pattern, same testimonial rail. The visual language meant to earn trust begins to do the opposite.
When all of this is combined with maddening verbosity of text on pages, it creates cognitive overload for a prospective customer and delivers a poor experience.
The internet has named this pattern “AI slop.”
Fun Fact: Merriam-Webster named “slop” its 2025 word of the year because the internet agreed that AI-generated content reads a particular way.
All of this ties back to SEO because AI-generated websites should always be considered as drafts.
Visibility is the first revision that is required of AI-generated websites. Second is content quality.
Google’s recent announcements support this. Google’s systems reward helpful, original content and demote thin or generic pages. Visibility alone is not enough if the content itself is low quality.
For businesses, the problem is AI slop, not the use of AI itself.
Websites are vital because first impressions matter.
Dressing well for an event to meet someone important is no different from putting your strongest foot forward for prospective customers.
The ROI of AI use on websites
So far, I have only discussed the costs of doing this wrong. So that raises the question.
Is AI actually useful for my business?
In recent weeks, the division of labor has become crystal clear for me: I define the business, and my agents implement the decisions. Anything outside of this has only impacted my business negatively.
I write all of this from experience as a new entrepreneur. Defining my own branding comes easily. Implementing it has been harder because there is no existing process in place: what SEO means for the business, what the message needs to say, and which customer needs to hear it.
I work harder now than I did before these tools existed because I have to define each process before I ask an agent to carry it out.
My work so far has concrete inputs:
- The audience and the problem the business solves.
- The offer, the service area, and the reason a customer can trust it.
- The search terms that best describe the customer’s intent.
- The voice, visual choices, proof, and next step that belong on the page.
Once those decisions exist, AI becomes useful. It can turn a defined brand into page layouts, components, metadata, and draft copy. When the decisions do not exist, the same tool produces a generic version of a business that has not yet been explained.
I learned all of these lessons the hard way.
I perfected my cold-email techniques and wrote strong ad copy, but I left messaging, website implementation, and design to my AI agent with almost no concrete guidelines - only past messages and memory context for it to rely on.
The results were clear. Website traffic was high, but conversion was low. PostHog showed events of a single scroll on landing page, with prospects dropping off shortly after.
Prompting “add some SEO to my website” or “make it convert—no mistakes” has produced negative ROI for me, in relation to my AI use.
A useful request names the requirements and the checks. It asks for crawlable page content, unique titles and descriptions, canonical URLs, a sitemap, a robots.txt file, relevant structured data, and links between related pages.
It also asks for the site to be checked in Google Search Console and Bing Webmaster Tools after publication.
A process that gives AI the right job
Learn the SEO basics before you generate the site
Start with Google’s SEO Starter Guide.
Learn the difference between technical SEO, content SEO, and local SEO. You do not need to become a search specialist before you begin. You only need enough knowledge to recognize a missing sitemap, an accidental noindex directive, a weak page title, or a page that search engines cannot read.
If you have processes or SEO setup in place, it is easier to point an AI agent to Google’s documentation for SEO instead, and have it implement the best practices.
If you do not have any process setup, scan through the documentation. Depending on what your business does, some will apply and some will not. This will allow you to create the guideline for your agent to follow.
Choose the target search before you write the page
Keyword research comes before copy generation. Decide what each page needs to help a customer find. A service page may target a service and a city. A guide may answer a specific question. The page title, main heading (H1), body copy, internal links, and call to action must support that intent.
This does not mean repeating the same phrase until the page becomes unreadable. It means using the customer’s language to make the page specific. The research gives the page a job. The business’s experience and point of view give it a reason to exist.
Define the brand and the experience
Decide what a prospect needs to understand in the first few seconds. Make the offer clear. Show evidence that the business can deliver it. Remove claims that could belong to any competitor. Choose the images, colors, typography, and layout because they fit the business.
If your agent is offering to do this for you to begin with, you are doing it wrong. The default for AI models is pick from sample distribution. If you are unsure where to start, point to an existing design to draw inspiration from.
First impressions matter, but clarity carries the page after the first impression. A polished design cannot repair a vague offer. A strong brand cannot compensate for a page that a crawler cannot access.
Ask AI to implement, then verify the result
Give the builder a written brief with the target pages, search intent, brand decisions, and technical requirements. After publication, inspect the live site. Check the page source and rendered content. Test links, titles, canonical URLs, the sitemap, robots.txt, structured data, mobile layout, and form behavior. Use Search Console’s URL Inspection tool to compare what users see with what Google can access.
Always treat the first generated version as an implementation draft. Review it with the same care you would give a site built by a human developer that you paid thousands of dollars to.
Your decisions determine whether that page has a purpose, earns trust with a good design, and provides a great experience that would make a prospective customer know that you can serve them well.