How AI is Transforming Web Design: Field Notes from 2026

In 2004, when I built my first website, the internet was a completely different place. There was no ChatGPT, Claude, Gemini, or tools claiming "create a website in 30 seconds." Back then, building a website was genuinely challenging. This article is not one of those typical "AI is coming, web design is over" pieces you read online. What I'm sharing here is a summary of 22 years of experience, starting with Mambo in 2004, encompassing hundreds of projects, thousands of development hours, numerous sectors, and real clients.

Today, you don't even need to be a developer to set up a website. AI designs for you, writes code, creates content, produces logos, prepares visuals, and offers SEO suggestions. Does this mean web design is now irrelevant? Absolutely not. In fact, the opposite has happened. AI hasn't eliminated good web designers; it has only made the average ones invisible.

The 22-Year Evolution of Web Design: From 2004 to 2026

In 2004, creating a website was more "engineering" than "design" as we understand it today.

CSS support wasn't as robust as it is now. The concept of responsive design didn't exist. Smartphones hadn't yet entered our lives. Figuring out why the same page looked different in Internet Explorer and Firefox could take an entire day. Even making a PNG file appear transparent was considered an achievement.

Everything changed rapidly in the following years. The iPhone launched in 2007, and mobile internet exploded. From the 2010s onwards, responsive design became a necessity. Flexbox and Grid made page layout more human-friendly. jQuery was replaced by modern JavaScript. WordPress dominated half the world. Then came static site generators, headless architectures, and edge computing.

The most important lesson I've learned in these 22 years is this: tools constantly change, but the logic of doing good work doesn't. No matter what technology comes along, we always return to the same question. Who is this site for, what single task will it accomplish, and what will it convince the visitor to do?

From Mambo to Joomla: My First Projects

My first professional project was a multilingual website for plastic surgeon Erhan Eryılmaz. The system I used at the time was Mambo CMS.

Mambo was one of the most powerful content management systems of its time. A few years later, the project team split, and Mambo was replaced by Joomla. I was right in the middle of this transformation for many years. I witnessed the birth, maturation, and eventual replacement of a system from start to finish.

This experience gave me more than just technical knowledge. I learned to see when a technology is on the rise, when it reaches its peak, and when it needs to be abandoned. Today, when I tell a client "custom code instead of WordPress" or "don't chase the current trend," this foresight doesn't come out of nowhere. It's the result of intuition honed over hundreds of projects.

What Has AI Really Changed?

First, let me state the obvious: AI has accelerated everyone. Denying this is impossible.

I use AI every day. Whether it's generating code, writing blog posts, developing visual ideas, conducting SEO analyses, or even preparing for meetings. When used correctly, it boosts productivity incredibly. Tasks that used to take four hours can now be completed in twenty minutes.

But there's a critical point people overlook. AI provides the same speed advantage to everyone. So, it doesn't just speed you up; it speeds up your competitors too. Therefore, the competitive advantage is not in using AI but in how you use it.

What AI has truly changed is not production but where value is created. Production has become cheap and widespread. Value has shifted to strategy, experience, and judgment. Producing a website in minutes is no longer a skill. The skill lies in ensuring that site convinces the right person, at the right time, with the right message.

Why Do All Websites Look Alike?

I've reviewed hundreds of new websites in the past two years. At first glance, they all look quite modern.

Large headlines. Gradient backgrounds. Glass effects. Rounded cards. Glowing buttons. Micro animations. The first impression is genuinely impressive. But after a few minutes, you notice something interesting: it's as if all the sites were made by the same person.

The reason is simple. The tools used are the same, the prompts are similar, the ready-made components are identical, the color palettes are copies of each other. As a result, technically successful but characterless websites emerge.

In the past, there were amateur-looking sites. Today, there are professional-looking but forgettable sites. I think this is the biggest problem of 2026. A website shouldn't just look good; it should reflect the brand, instill confidence in the user, and create the "this is the right place" feeling within the first few seconds. This feeling is formed through experience, not ready-made templates.

UI Doesn't Win, UX Does

Most people think of visuals, or the interface (UI), when they hear web design. But the real work revolves around user experience (UX).

A beautiful interface impresses the user. A good experience turns the user into a customer. These are not the same thing. A site can look like a diamond, bringing someone to the cart but losing them there. Another site might look simpler but generate much higher conversions.

UX answers these questions. How many seconds does it take for a visitor to find what they're looking for? Is the next step clear? How many fields are in the form, and are they all necessary? Can it be used with one hand on a phone? What does the user see in case of an error? The answers to these questions will earn you more money than the color or font of the site.

AI can draw you a beautiful interface. But it doesn't know what convinces the visitor in your business, which sentence makes the phone ring, or which objection stops the sale. These are things learned through 420 projects, one by one.

My System for Working with AI

The secret to using AI efficiently is to position it as an assistant, not a strategist.

My workflow progresses in this order. First, strategy: who is the project for, what single task will it accomplish, and how will success be measured. This is a human decision, not AI. Then speed: once the strategy is clear, I accelerate drafts, variations, and routine code blocks with AI. Finally, judgment: I review everything produced because only experience can bridge the gap between the model's "average correct" and the real "correct."

The best areas for AI in my work are repetitive production, breaking the blank page syndrome, and patience-requiring checks like accessibility and error scanning. Its weakest point is one thing: it doesn't know your business. That's where humans fill the gap.

Why PageSpeed Insights is Still Critical

Speed is not a matter of comfort; it's directly about money. Every second a page takes to load means lost visitors and reduced conversions.

Google PageSpeed Insights measures a page's performance using both lab and real user data and provides you with a concrete roadmap. But there's an important nuance here: a high PageSpeed score is not the goal but the result. The goal is for the real user to experience the page quickly and smoothly. I've seen sites inflate scores with tricks that ruin the real experience. The right approach is to genuinely improve the core metrics.

In all my projects, speed is not an afterthought but a design decision from the start. Zero unnecessary frameworks, self-hosted fonts, optimized visuals, minimal JavaScript. That's why they are structurally faster than most sites built on ready-made themes.

Core Web Vitals: LCP, CLS, and INP

Google's performance language has three core metrics, and you can't move forward in modern web design without knowing them.

LCP (Largest Contentful Paint): The time it takes for the largest image or text block on the page to appear on the screen. The moment the user feels "the page is open." A good value is under 2.5 seconds. Large hero images, slow server response, and render-blocking resources typically disrupt this metric.

CLS (Cumulative Layout Shift): Measures how much elements shift while the page loads. That annoying feeling when an ad loads just as you're about to click a button, shifting the layout. A good value is below 0.1. Pre-defining sizes for images and ad spaces solves this.

INP (Interaction to Next Paint): Measures how quickly the page responds when a user clicks or types something. It replaced the old FID metric in 2024. A good value is under 200 milliseconds. This metric breaks when heavy JavaScript occupies the main thread.

These three metrics are not just technical details; they directly affect Google rankings and how long users stay on your site.

Visual Optimization: AVIF, WebP, and Lazy Loading

The blame for most slow sites lies in one place: heavy images. Unoptimized images typically make up a large portion of a page's total size.

The solution is threefold. First, the right format: AVIF offers the best compression today, while WebP is a strong alternative with broad browser support. Classic JPEG and PNG are often left behind. Then, the right size: there's no point in placing a 4000-pixel-wide photo in an 800-pixel space; the image should be served at the size it will be displayed. Finally, lazy loading: images not visible on the screen are loaded only when needed with loading="lazy", lightening the initial load.

These three steps significantly reduce page size on most sites and directly improve the LCP metric.

Font Optimization

Fonts are a silent performance killer. When set up incorrectly, they slow down the page and create privacy issues.

The right approach is first self-host: placing the font on your server instead of pulling Google Fonts directly from Google's server speeds things up and is cleaner from a GDPR perspective, as visitor data doesn't go to a third party. Then woff2 format: offers the best compression. Then font-display: swap: prevents text from being invisible until the font loads, so the user isn't kept waiting. And subsetting: loading only the character set used reduces the file size.

On my site, fonts are set up exactly this way; zero external requests, zero privacy leaks.

JavaScript and Bundle Size

The most common mistake in modern web is building everything on a heavy JavaScript framework when it's not needed.

Every line of JavaScript is a cost. It needs to be downloaded, parsed, and executed; all of which occupy the main thread and disrupt the INP metric. Building a promotional site with the full load of React or a similar framework is often like using a sledgehammer to crack a nut.

My approach is to choose tools based on need. I can build a simple corporate site lightly with vanilla JavaScript without diving into a heavy framework. When a framework is needed, I control the bundle size with tree-shaking, code splitting, and lazy loading. The rule is simple: the user should only download the code they need at that moment.

CDN and Edge Cache

How fast a site opens is also related to the physical distance of the server from the user. For a visitor in Germany, pulling content from a single server in Turkey means a delay of thousands of kilometers for each request.

CDN (Content Delivery Network) solves this problem. It distributes your site's static files to servers worldwide, allowing visitors to quickly receive data from the nearest point. Edge cache keeps processed pages on these edge servers, so production isn't done from scratch for every request.

Especially for brands offering multilingual and international services, this is not a luxury but a necessity. If targeting Turkey, Germany, and another country simultaneously, providing the same speed for everyone requires this.

SSR, SSG, ISR, and Headless Architectures

How a site's pages are produced directly affects performance, SEO, and AI visibility. There are four main approaches.

SSR (Server-Side Rendering): The page is produced on the server with each request. Ideal for dynamic sites with constantly changing content.

SSG (Static Site Generation): Pages are pre-generated as static HTML and served as is. It's the fastest and most secure method; works great if content doesn't change frequently.

ISR (Incremental Static Regeneration): A flexible form of static production. Pages remain static but are refreshed in the background at intervals. Ideal for large sites needing both speed and freshness.

Headless architecture: Separates content management from the presentation layer. Content comes from an API, and the presentation is built with the desired technology, significantly increasing flexibility.

In my blog infrastructure, I'm consciously on the static production side. When I save a post in the panel, the system regenerates the pages as static HTML; the visitor receives a lightning-fast file, not a database query. This gains both speed and AI visibility simultaneously.

Semantic HTML

The meaning of the HTML beneath a page is as important as its appearance. Most sites are visually correct but structurally meaningless.

Semantic HTML means marking each element with the appropriate tag for its function. h1, h2, h3 for headings; main for main content; nav for navigation; article for articles; footer for footers. Instead of building everything with stacks of div, it clearly tells browsers, screen readers, and AI bots the meaning of the page.

Why is this important? Because both Google and AI systems read the page with this structure. A meaningful HTML skeleton makes it easier for your content to be understood and quoted correctly. A poor skeleton can make even the best content invisible.

Accessibility (WCAG)

Accessibility means the site can be used by everyone. From a visually impaired user to someone with trembling hands struggling to hold a phone.

The standard is WCAG, defined at A, AA, and AAA levels; for most projects, the target is AA. In practice, this means: sufficient color contrast between text and background, meaningful alt text for every image, full keyboard navigation, ARIA labels when needed, and an option to reduce animations for those sensitive to movement.

Accessibility is not just a matter of conscience but also reaching a wider audience and strengthening SEO. Google rewards accessible sites because good accessibility often goes hand in hand with good structure.

Schema.org and JSON-LD

A person understands what a page is about by looking at it, but there's a way to clearly tell search engines and AI: structured data.

Schema.org is the common standard that allows you to tag your content with a dictionary that machines can understand. JSON-LD is Google's recommended method for adding this tagging to a page; it sits as a clean data block in the background without disrupting the page's appearance.

Thanks to this data, the search engine doesn't have to guess "this is an article, the author is this, the publication date is that, it belongs to this corporate identity," it reads it directly. Result: rich results, better understanding, and easier quoting in AI systems.

Which Schema Types Should Be Used?

Each page type has its own suitable schema type. The most useful ones are:

• Organization: Brand identity; company name, logo, social media accounts.
• LocalBusiness: For local businesses; address, phone, working hours. The foundation of local SEO.
• Person: Personal identity; the profile of an expert, author, or doctor.
• FAQPage: Frequently asked questions; can appear as expandable answer boxes on Google.
• Article: Blog posts and articles; title, author, date.
• BreadcrumbList: Page hierarchy; shows where the user is on the site.

On my site, some of these are already set up. This blog post also has Article and BreadcrumbList data underneath; that's why both Google and AI can read this content more accurately.

What is llms.txt?

A new standard has entered the web world: llms.txt. As the name suggests, it directly targets large language models, i.e., AI systems.

Its logic is similar to robots.txt but with a different purpose. robots.txt tells bots where they can and cannot go; llms.txt tells AI in plain language what your site is, which are your most important pages, and how to summarize your brand. It's a Markdown file that sits in the root directory of the site and can be read by humans too.

Why is it important? Because if AI doesn't know you when answering a question, it won't mention you. llms.txt is the cleanest way to introduce your brand to the model. I've already prepared this file on my site; it clearly tells AI who I am, what services I offer, and my important pages.

How Should robots.txt Be?

robots.txt is the doorman at the entrance of your site. It tells which bot can go where. In 2026, the importance of this file is greater than ever because we're now managing not only the Google bot but also AI bots.

The classic approach only considered search engines. Today, it's necessary to add open permission lines for AI bots like ChatGPT, Claude, Perplexity, and Google's AI bots to the file. Because if these bots can't read your content, they can't cite you in any answer.

There's an important balance: while closing off areas that need to remain private (like admin panels), keep AI access open to the content you want to be visible. A wrongly configured robots.txt can make even your most valuable content invisible.

sitemap.xml

sitemap.xml is a table of contents that your site presents to search engines. It regularly informs them which pages exist, when they were last updated, and their priority.

This file is critical, especially for multilingual and multi-page sites. It ensures that a newly published blog post or a category page is discovered more quickly. For multilingual sites, it tells Google with hreflang information that different language versions of the same content are translations of each other.

My blog infrastructure automatically updates the sitemap when a new post is published. It should be like this; a sitemap shouldn't be a manually updated file but part of the system.

How AI Bots Read Your Website

Here's a critical fact most people don't know. The vast majority of AI bots do not execute JavaScript; they only read raw HTML.

This means if your site's content only appears when JavaScript runs in the browser, AI likely won't see it. Google's advanced bot can process JavaScript to some extent, but most AI bots are much more limited in this regard. The only thing that matters to them is the initial HTML from the server.

That's why static and server-side generated sites have a clear advantage in AI visibility. When content is ready in the initial HTML, the bot reads it without issue and turns it into a quotable source. One of the main reasons I consciously set up my blog to produce static HTML is exactly this.

Appearing in ChatGPT, Gemini, Claude, and Perplexity

People no longer just ask Google. They ask ChatGPT, Gemini, Claude, or Perplexity directly for an answer. And these tools provide sources when they answer.

The rules of the game have changed here. The old question was "what rank am I in Google?" The new question is: "Does AI mention me when discussing this topic?" When a user asks "someone who does custom code web design in Istanbul," appearing in the model's answer is a completely different visibility.

This visibility relies on three things. Clean and static content that the machine can read. Information that genuinely answers questions, not brochure text but value. And most importantly, brand signal: your name appearing on other sites, real reviews, consistent identity. AI mentions sources it trusts and sees repeatedly.

GEO: Generative Engine Optimization

All this new visibility effort has a name: GEO, or Generative Engine Optimization. In Turkish, optimization for visibility in generative AI engines.

GEO is built on top of classic SEO but has a different goal. The aim is not just to rank high in search results but to be cited as a source in AI-generated answers. In practice, it requires three things. Structured content that the machine can easily read, like schema, fast pages, and signals like llms.txt. Content that genuinely answers questions. And the one thing synthetic text can't imitate: lived experience.

GEO isn't even on the agenda for most businesses right now. That's exactly why there's a big opportunity window for those who move early. I've already set up the GEO infrastructure on my site; we'll see the benefits of this in the coming years.

The Difference Between SEO and GEO

They are often confused but are different things. It's worth clearly distinguishing them.

SEO (Search Engine Optimization) targets classic search engines. The goal is to rank high for a keyword on Google and attract visitors from the results page to your site. Success is measured by ranking and clicks.

GEO (Generative Engine Optimization) targets AI engines. The goal is to be cited as a source in the model's generated answer. Here, the user doesn't see a list of results; they receive a direct answer, and you're either in that answer or you're not.

They are not competitors but complements. The technical foundation of SEO (speed, semantic HTML, schema) is also the foundation of GEO. The difference lies in the intent of the content: SEO is written to be clicked, GEO is written to be quoted. Those who consider both together will win in 2026 and beyond.

Why Real Experience is More Valuable Than AI

Amidst all this technology, there's one thing that remains unchanged: lived experience. AI can write anything, but it can't write what you've learned in the field.

A model doesn't know what convinces a dental clinic's patient. It doesn't know what percentage of questions a car dealership receives are about price. It doesn't know which photo angle gets a real estate agent more appointments. These aren't written in books; they're learned over years, project by project, mistake by mistake.

Google and AI are now looking for this "experience signal." What they call E-E-A-T (experience, expertise, authority, trustworthiness) measures exactly this. Case studies, real numbers, real stories. This is what synthetic content can never produce, and it's the real material of a good website.

Trust Signals

When a visitor enters your site, even if they don't consciously ask, their mind is constantly weighing one question: "Can I trust this place?" Trust signals are the answer to this question.

Things that build trust are often small but decisive. Real photos, not stock images. Transparent and honest prices, or at least a transparent process. Real customer reviews and case studies. Clear contact information and a promise of quick response. Complete legal texts (GDPR, privacy). Consistent brand identity.

Each of these signals may seem small on its own, but together they can fundamentally change a site's conversion rate. In 2026, trust is the scarcest and most valuable currency.

Real Photo or AI Visual?

AI visuals have become incredibly advanced. Should we use them everywhere? My answer is clear: it depends, but never in places requiring trust.

AI visuals are a great tool for abstract concepts, decorative backgrounds, and places requiring illustrations. Fast, cheap, flexible. But when it comes to you, your team, your workplace, or your product, it's a different story. A clinic's real doctor photo, a gallery's real car, a craftsman's real hand; these cannot be replaced with a synthetic image.

Because people sense fakeness. A face that looks too perfect, too polished, "unreal" doesn't increase trust; it breaks it. The strongest differentiator of 2026 is reality. That's why I always tell my clients the same thing: we can use AI in decor, but let's be real in what makes you, you.

Conversion Optimization (CRO)

Driving traffic to a site is half the job. The other half is turning that traffic into customers. This second half is called CRO (Conversion Rate Optimization).

CRO is concerned with this question: how many of the hundred people who visit the site perform the desired action? Fill out a form, call, purchase. Increasing this rate is often more profitable than attracting more traffic because it means better utilizing the visitors you already have.

CRO's material is small but powerful details. A clear and singular call to action. Simplified forms, removing unnecessary fields. Properly positioned trust signals. Fast page, because slowness directly reduces conversion. Flawless mobile experience. And continuous measurement: finding out what works not by guessing, but with data.

A site that looks good but doesn't sell is an expensive sign. Good CRO turns that sign into a working sales team.

What a Modern Website Should Have: 2026 Checklist

Let me distill this entire article into a practical list. In 2026, a serious website should include the following.

• Clean, semantic, and valid HTML skeleton.
• Real speed meeting Core Web Vitals (LCP, CLS, INP) targets.
• Images in AVIF or WebP format, correctly sized and lazy-loaded.
• Self-hosted, woff2, swap optimized fonts.
• Minimal and controlled JavaScript, without unnecessary framework load.
• Static or server-side generated content readable by AI.
• Complete Schema.org / JSON-LD data (Organization, Article, FAQ, Breadcrumb).
• Open robots.txt for AI bots and ready llms.txt.
• Automatically updated sitemap.xml and hreflang for multilingual sites.
• WCAG AA level accessibility.
• Real photos, real reviews, and clear trust signals.
• Simplified forms and clear calls to action for conversion.
• Complete GDPR and privacy texts.
• Flawless mobile experience.

Most of this list is invisible to the eye. But these are exactly what determine whether a site will win in the long run.

Web Design Isn't Dead, Average Web Design Is

Twenty-two years ago, getting a website to work was an achievement in itself. Today, everyone can run something. The challenge is no longer producing, but being noticed.

AI hasn't ended web design. It has only made the easy part free for everyone. What's left is the hard part, namely strategy, experience, trust, and the real human touch, which are still the most valuable things. And this part is exactly what AI can't do.

If you're a business owner, my advice for 2026 can be summarized in three sentences. Avoid templates, because if you blend in with your competitors, even the most expensive ad is like taking the stage with a rented face. Show what's real, because trust is the scarcest currency of this era. And don't reject AI, place it correctly; leave strategy to humans, repetition to machines.

AI has killed average web design. And frankly, I can't say I'm sorry about it. Because what's left is a wider space for those who truly do good work.

If your site is getting lost in this average, let's talk. Let's plan together how we can apply 22 years of experience and all this technical infrastructure to your project.