I did not plan to become an SEO strategist. Like most people in digital marketing, I stumbled into it — curious about why some websites appeared at the top of Google and others did not. That curiosity turned into an obsession, and that obsession eventually became my career.

My name is Muhammad Naqash. I am an SEO and digital marketing strategist, and over the past several years I have built a freelance practice around one core belief: that the way people find information online is changing faster than most marketers realize — and the ones who adapt early will have a significant advantage over those who wait.

This article is my story. It covers where I started, what I learned along the way, how I built my freelance practice, and how I eventually developed a specialized approach to AI search visibility that I now call Hybrid Engine Optimization, or HEO. I am writing this not to impress anyone, but because I genuinely believe the lessons I have learned — including the mistakes — are useful for anyone trying to build a real career in SEO and digital marketing.

Where I Started

When I first got into SEO, I had no formal training and no mentor. I learned by doing. I read everything I could find — Google’s documentation, industry blogs, case studies, forum threads. I tested things on small websites I built myself. I failed a lot. Things that looked straightforward in theory turned out to be more complicated in practice. Rankings that I expected to improve did not move. Content I was proud of got ignored completely.

But I kept going. Slowly, the patterns started to become clear. I began to understand why Google ranked certain pages over others. I started to see the relationship between content quality, site structure, and link authority. I learned that SEO is not about tricks or shortcuts — it is about genuinely making a website more useful, more trustworthy, and more relevant to the people searching for it.

My first real clients were small businesses — local shops, service providers, small e-commerce stores. They did not have big budgets or complex requirements. They just needed more people to find them online. Working with these clients was the best education I could have had, because it forced me to focus on fundamentals and deliver results with limited resources.

Those early projects taught me something I still believe today: the basics done well beat advanced tactics done poorly every single time. Clean site structure, well-written content, proper internal linking, and a few quality backlinks can transform a small website’s visibility when applied consistently over time.

Building My Freelance Practice

Moving from doing SEO as a side project to building a real freelance practice was not easy. There was no steady income, no guaranteed clients, and no clear path forward. I had to figure out how to find clients, how to price my services, how to communicate results, and how to keep improving my skills — all at the same time.

I started on Legiit. In the beginning, I offered broad, generic services — keyword research, on-page SEO, meta tag optimization. The work was straightforward but not particularly exciting, and the clients were mostly looking for the cheapest option available. I quickly realized that competing on price was a race to the bottom. There would always be someone willing to charge less.

So I changed my approach. Instead of offering generic SEO services, I started positioning myself around specific outcomes and specific types of clients. Instead of “I will do SEO for your website,” my gigs became more focused — on SaaS content, on featured snippet optimization, eventually on AI search visibility. This shift changed everything. The clients who found me through more specific offerings were different. They understood what they were buying. They valued expertise over price. And they were far more likely to become long-term clients.

One of the most important things I learned during this period was how to communicate with clients about SEO. SEO results take time, and clients who do not understand why that is can become frustrated quickly. I developed a habit of explaining my reasoning for every decision I made — why I was targeting certain keywords, why I was restructuring certain pages, why I was building links from certain sources. This transparency built trust, and trust turned one-time projects into ongoing relationships.

I also learned that a freelance practice is not just about doing good work. It is about building a reputation that attracts good work. I started writing about what I was learning — posting on LinkedIn, contributing to forums, publishing articles on platforms like Medium and dev.to. This content did two things for me. It forced me to clarify my own thinking, and it put my name and ideas in front of people who might need my services.

The Moment Everything Changed: Discovering AI Search

Around 2023 and 2024, I started noticing something that did not sit right with me. I had clients who were ranking well on Google — page one, strong positions, decent traffic. But when I searched for their topics on ChatGPT or Perplexity, their content was nowhere. Other sources were being cited. Competitors who ranked below them on Google were showing up in AI-generated answers.

At first I thought this was just a novelty — AI search was new, it would sort itself out. But the more I paid attention, the more I realized this was not a temporary glitch. It was a structural difference. AI-powered search engines were evaluating content by different criteria than Google’s traditional algorithm. And almost no one in the SEO industry was talking seriously about what those criteria were.

I spent months trying to understand it. I tested different content structures, different schema implementations, different approaches to how entities were defined and connected within articles. I analyzed which types of content got cited by ChatGPT and Perplexity and which did not. I read everything I could find about how large language models were trained and how they selected sources when generating answers.

What I found was both fascinating and actionable. LLMs do not rank content the way Google does. They look for content that is semantically clear — content that states what it is about directly and early, supports its claims with evidence, and establishes clear relationships between the concepts it covers. They prefer sources that are mentioned consistently across multiple trusted platforms. They respond well to structured data that removes ambiguity about what a page is and who created it.

These insights completely changed how I approached content strategy. And they led directly to the framework I now use for all my client work — Hybrid Engine Optimization.

What Is Hybrid Engine Optimization and Why I Developed It

I developed Hybrid Engine Optimization, or HEO, because I needed a way to describe and systematize what I was doing. My clients needed to understand why I was making certain content decisions, and I needed a framework that could be applied consistently across different projects and different industries.

HEO is a search strategy that targets three discovery channels simultaneously. The first is traditional search — Google, Bing, and other search engines that rank pages algorithmically. The second is generative AI search — systems like ChatGPT Search, Perplexity AI, and Google’s AI Overviews that generate answers by synthesizing and citing web content. The third is answer engines and voice systems — featured snippets, position zero results, and voice assistants that pull direct answers from structured content.

Most SEO strategies only address the first channel. HEO addresses all three. The reason this matters is that users increasingly rely on all three channels when searching for information. A website that is only optimized for traditional Google search is invisible to a growing portion of its potential audience.

The core insight behind HEO is that the practices required to perform well across all three channels overlap significantly. Content that is well-structured, entity-rich, semantically clear, and supported by proper schema markup tends to perform better across all three channels simultaneously. You do not have to choose between optimizing for Google and optimizing for AI search. When done correctly, optimizing for one supports the other.

How I Structure Content for AI Search Visibility

One of the most concrete things I changed in my content strategy was how articles are structured. Traditional SEO content often builds gradually toward a main point — an introduction, some background, the key information, a conclusion. This structure can work well for readers who want to understand a topic in depth. But it performs poorly with AI engines, which are looking for a clear, direct answer they can extract and cite.

I now structure every article I write or oversee around a five-part framework. I start with a Definition — a direct, clear answer to the primary question the article addresses, written in the first 50 to 70 words. This is what I call the Answer Block, and it is the single most impactful change I have made to content strategy in the past two years. After the Definition comes Context — background that explains why the topic matters. Then Evidence — data or referenced claims that support the article’s main argument. Then an Example — a concrete illustration of the concept. And finally, an Implication — what the reader should understand or do differently.

This structure works because it mirrors the way authoritative reference material is written. LLMs are trained on enormous amounts of text, and they have learned to associate this kind of structured, encyclopedic writing with reliable, citable sources. Content that follows this pattern gets cited more often. It is that simple.

I have tested this across dozens of articles and multiple clients. Articles restructured around this framework consistently show higher citation rates in AI-generated answers than articles that cover the same topics in a less structured way.

Building the LLM Rank Analyzer

One of the frustrations I ran into early in my AI search work was measurement. Traditional SEO has clear, trackable metrics. Google Search Console shows impressions and clicks. Ahrefs shows rankings and domain authority. But AI search visibility had no equivalent dashboard. There was no way to know how often a client’s content was being cited in ChatGPT answers or how their citation rate compared to competitors.

So I built a tool to solve that problem. I called it the AI Visibility and LLM Rank Analyzer. The tool works by sending a structured set of queries to multiple AI engines — including ChatGPT, Perplexity, and Gemini — and analyzing the responses to determine whether the client’s brand, content, or entity is cited or referenced. It tracks citation frequency over time, identifies which topics generate the most AI citations, and allows me to compare a client’s AI visibility against their competitors.

Building this tool was one of the best investments I have made in my practice. It gave me something almost no other SEO freelancer could offer — concrete, quantifiable data on AI search visibility. When I present this data to clients, it transforms how they think about content strategy. Suddenly, AI search is not an abstract concept. It is a measurable channel with trackable performance.

The tool also helps me make better strategic decisions. When I can see which content is getting cited by AI engines and which is not, I can identify patterns and apply them more deliberately to future content. It turns AI optimization from guesswork into a data-driven practice.

Cross-Platform Entity Building: Why It Matters

One of the things I learned about how LLMs evaluate authority is that they do not just look at a single website in isolation. They synthesize information from across the web. A brand or expert that is mentioned consistently and accurately across multiple high-authority platforms builds a pattern of entity association that AI systems recognize as a signal of credibility.

This is why I include cross-platform entity building as a standard component of every client engagement. The platforms I focus on are not chosen arbitrarily. They are platforms with high domain authority that are well-represented in LLM training data and frequently crawled by AI search systems. These include Medium, dev.to, Hackernoon, Hashnode, LinkedIn, Quora, and Reddit.

The goal is not just to build backlinks — although that is a beneficial side effect. The goal is to create a pattern of consistent, accurate entity mentions across the web that signals to AI systems that this brand is a recognized authority in its domain. When an AI engine encounters multiple high-quality sources that all associate a brand with a particular topic, it increases the probability that the brand will be cited when that topic comes up in a user query.

I have seen this work consistently across different clients and different industries. The combination of well-structured on-site content and deliberate cross-platform entity building produces AI visibility improvements that neither approach achieves alone.

What Freelance Growth Actually Looks Like

I want to be honest about what building a freelance practice looks like in practice, because most of what gets written about freelancing online makes it sound easier than it is.

There were months early in my career when income was inconsistent and client acquisition felt like a constant struggle. There were projects that did not go the way I planned, clients who were not satisfied despite my best efforts, and strategies that I was confident in that simply did not produce the results I expected. These experiences were frustrating at the time, but they were also the most educational.

What I learned from the difficult periods is that sustainable freelance growth comes from a small number of things done consistently over a long time — not from clever tactics or shortcuts. It comes from genuinely improving your skills so that your work gets better. It comes from treating every client relationship as a long-term investment rather than a transaction. It comes from being specific about who you serve and what you offer, so that the right clients can find you and recognize that you are the right person for their needs. And it comes from being patient enough to let your reputation build gradually through the quality of your work.

The shift toward AI search specialization was the single biggest accelerator of my freelance growth. Not because it was a trend I jumped on, but because it was a genuine area of expertise that very few people had developed. When you know something that most people in your field do not yet know — and you can demonstrate that knowledge through documented results — clients will find you.

Results and What They Represent

Across my client engagements over the past year, the HEO framework has produced results that I am proud of. Organic search impressions have increased by an average of 180 to 220 percent within 90 days of full implementation. Featured snippet captures have increased significantly across every client in informational niches. AI engine citation frequency, tracked through my LLM Rank Analyzer tool, has grown from zero to measurable, trackable levels within 60 to 90 days for every client who has followed the full strategy.

But I want to be clear about what these results represent. They are not magic. They are the outcome of a structured, disciplined approach applied consistently. The framework works because it is built on a genuine understanding of how search systems — both traditional and AI-powered — evaluate and select content. It is not a collection of tricks. It is a methodology grounded in how these systems actually work.

The results also represent something more personal to me — evidence that the years I spent learning, testing, failing, and refining were worth it. Every improvement in a client’s visibility is a validation of the work that went into understanding why search works the way it does.

Frequently Asked Questions

Muhammad Naqash, how did you get started in SEO?

I got started in SEO out of curiosity — I wanted to understand why certain websites ranked at the top of Google. I learned through self-study, experimentation on my own websites, and eventually through client work. There was no formal training or mentor. Most of what I know came from testing things, observing results, and reading everything I could find about how search engines work.

What is Hybrid Engine Optimization (HEO) and why did you develop it?

HEO is a search strategy I developed to address the reality that modern users find information through multiple channels — traditional Google search, AI-powered engines like ChatGPT and Perplexity, and answer or voice systems. I developed it because I noticed that traditional SEO was not enough to achieve visibility in AI-generated answers, and I needed a framework that addressed all three channels simultaneously.

What is the most important thing you have learned about AI search visibility?

The most important thing I have learned is that structure matters more than most people realize. Content that states its main point directly and early, supports it with clear evidence, and establishes explicit relationships between the concepts it covers gets cited by AI engines far more consistently than content that covers the same topics in a less organized way. The Answer Block — a 40 to 70 word direct answer at the beginning of every article — is the single most impactful technique I have found for improving AI citation rates.

How do you measure AI search visibility for your clients?

I use a custom tool I built called the AI Visibility and LLM Rank Analyzer. It sends structured queries to multiple AI engines and analyzes the responses to track how often a client’s brand or content is cited. This gives clients concrete, quantifiable data on their AI search visibility — something most SEO professionals cannot currently offer.

What advice would you give to someone starting a freelance SEO career today?

Specialize as early as you can. The generalist path is harder and slower than it looks. Find an area of SEO where you can develop genuine expertise — technical SEO, content strategy, local SEO, AI search optimization — and go deep. Build a portfolio of specific, documented results in that area. Be transparent with clients about what you are doing and why. And be patient. Sustainable freelance growth takes longer than most people expect, but it compounds over time in a way that rewards consistency.

Is HEO suitable for small businesses and individual freelancers?

Absolutely. The core principles of HEO — semantic content structure, Answer Blocks, schema markup, entity clarity, and cross-platform mentions — do not require a large budget. They require knowledge and discipline. A small business owner or freelancer who understands and applies these principles consistently can achieve significant improvements in both traditional and AI search visibility without expensive tools or large content teams.

Conclusion: What I Know Now That I Did Not Know Then

If I could go back and give my earlier self one piece of advice, it would be this: pay attention to where search is going, not just where it is today.

When I started in SEO, the field looked very different from how it looks now. The core principles — relevance, authority, good content — have remained constant. But the systems that evaluate and surface content have changed enormously, and they will keep changing. AI-powered search is not a temporary trend. It is a fundamental shift in how information discovery works, and it is going to continue evolving in ways that none of us can fully predict.

What I know now is that the professionals and businesses who will thrive in this environment are not the ones who mastered the rules of the past. They are the ones who are curious enough to understand what is changing, disciplined enough to develop real expertise in new areas, and patient enough to build that expertise before it becomes obvious to everyone else.

That is what I have tried to do throughout my career. And it is what I will keep doing.

I am Muhammad Naqash. This is my story so far — and there is a lot more still to write.