The Problem Is Often Complexity, Not a Lack of Tools

The short version

When results decline, businesses often add something: more advertising, more content, another SEO platform, another AI workflow, or more automation. Sometimes that is the right answer. But often the real problem is friction. Before adding a tool, find out what can be removed.

The first question should not be “What should we add?”

Over the past few days, while reviewing several projects and some of my own decisions, I returned to an old problem:

When we do not get the result we want, we usually start adding instead of removing.

Sales are down? Add more advertising.

Traffic is falling? Publish more content.

Google rankings are weak? Buy another SEO tool.

The brand is missing from AI answers? Add Schema, llms.txt, more pages, and another AI product.

Company processes are slow? Automate everything.

Each response can be correct in the right context. But there is a more important question we often ask too late:

What can we remove?

That is where SEO strategy, GEO, and automation should begin: by locating friction.

Maybe the sales problem is not a lack of customers

Imagine a customer must complete six steps to buy a product from your website. You can increase the advertising budget and bring more people into the funnel. But if many of them abandon the same six-step process, you are simply paying more to send more people into an inefficient system.

The answer may be much simpler:

Turn six steps into three.

One fewer form field, one fewer checkout screen, one unnecessary confirmation removed, or one clearer button can improve sales more than a new campaign.

This is not only a UX or conversion-rate optimization issue. It is a way of thinking: before adding something to a system, ask which source of friction can disappear.

We make the same mistake in SEO

One common response to stalled SEO growth is to produce more content. A site has 500 articles and is not growing? Publish 500 more.

But the problem is not always a shortage of content. Sometimes the site has become a warehouse: hundreds of pages with no clear relationship, weak information architecture, important pages buried deep in the site, and several URLs targeting the same intent.

In that situation, daily publishing can make the problem worse. Before a new content plan, an SEO project may need:

• Removing or merging weak and overlapping pages
• Rebuilding the information architecture
• Repairing internal linking
• Defining pillar pages and core commercial pages
• Reducing cannibalization
• Improving crawl and discovery paths
• Strengthening the entity and topical relationships between pages

SEO is not always a contest to see who has more content. Sometimes the winner is the site with the clearer structure. Search Engineering explores this idea in more depth.

Being AI-friendly is not the same as earning AI visibility

As ChatGPT, Google AI Overviews, Perplexity, and other answer engines grow, a new market of advice has appeared: add Schema, create llms.txt, write for AI, publish more FAQs, and make the pages longer.

These actions can help in some projects. They do not usually solve the central problem. The more important question is:

Can a machine understand who you are at all?

What topic does the brand have authority in? Which independent sources discuss it? What original data, experience, research, product, or content has it created? Can its claims be checked? Do the website, authors, organization, products, social profiles, and outside sources describe one coherent entity?

A website can be technically readable to machines and still give an answer engine no strong reason to cite it. What Is AI Visibility? explains the distinction simply, while Evidence Architecture for AI goes deeper.

Automation can make a bad process worse

With n8n, APIs, agents, and AI models, a business can automate a large part of its operations: lead collection, content production, data classification, reporting, and first responses.

But one principle matters:

Automating a bad process does not make it a good process. It can simply make the bad process run faster.

If a process has 12 steps when it could have five, automating all 12 is not automatically a good decision. Before automation, ask:

• Are all the steps necessary?
• Which approvals create no real value?
• Which data is entered more than once?
• Which decisions are repetitive?
• Which step could disappear completely?

Automation becomes powerful after simplification, not before it.

AI should not become a new layer of complexity

Sometimes a company has a simple problem and builds an agent, several workflows, a vector database, multiple APIs, and a library of prompts to solve it. The architecture may be technically interesting. But did the business actually need all of it?

I face this temptation too. When powerful tools are available, adding a feature feels more exciting than removing an old one. But good architecture is not only the art of building. It is also the art of removing.

A system with 20 features that a team uses five of is not necessarily better than a system that performs those five jobs exceptionally well.

The sequence of decisions matters more than the tool

I am not against tools, AI, SEO, automation, or content. Much of my professional work is in these areas. The issue is the order in which we decide.

Instead of:

Problem → new tool → more complexity

Try:

Problem → understand friction → remove → simplify → optimize → automate

Only then, if something is still missing, add a tool.

This is also connected to the question of founder behavior and digital authority. In How Founder Personality Shapes SEO and AI Visibility, I write about how scattered decisions can make real expertise harder for the web to recognize.

A simple test for your business

Choose one important process: a customer purchase, lead intake, content publication, reporting, customer support, or creating a new website page.

Write down every step. Then, instead of asking “How can we improve this process?”, ask:

If we had to remove 30 percent of the steps, which ones would go?

The question forces a useful distinction between what you have always done and what is genuinely necessary. After that, you can decide whether SEO, AI, automation, or another tool is needed.

The future does not belong to the most complicated system

We will have more tools, more agents, cheaper content production, faster software development, and more accessible automation. Almost everyone will be able to add another capability.

The more valuable advantage may be knowing what should not exist.

Sometimes business growth does not need another campaign. SEO is not always fixed by article number 1,001. AI visibility is not always fixed by another file. And automation is not always the answer.

Sometimes something needs to be removed. Less complexity, less friction, and more clarity can become a competitive advantage by themselves.

Key takeaways

• Find unnecessary friction before buying or building another tool.
• In SEO, information architecture and internal linking can matter more than more pages.
• Technical AI-readiness is not the same as evidence-backed citation and visibility.
• Simplify a process before automating it.
• Removing things is part of good architecture, not a sign of doing less.

Author: Taqi Molavi

Focus: SEO, GEO, AI Visibility, and digital systems architecture