Insights on B2B SaaS growth, technical SEO, and paid acquisition.
Think of the internet as an infinite, unorganized filing cabinet, and a large language model as an executive with a terrible memory. If you ask that executive a question about something that happened yesterday, they’re not going to be able to rely on something they learned in school. They’re going to ask their assistant to […]
Search engines no longer rely on simple word matching to figure out what your website is about. They are acting as intelligent answer engines, reading your pages to extract precise facts, understand context, and synthesize direct responses for users on the spot. If your site relies solely on standard HTML paragraphs, machine crawlers have to guess what your content means, and whenever machines have to guess, your visibility suffers.
Pitching a budget for Generative Engine Optimization used to be easy because the novelty alone was enough to get leadership excited. Fast forward to today, and your finance team wants to see actual dollar returns, not just a spreadsheet showing that ChatGPT cited your blog. Measuring returns on generative search feels tricky because AI platforms synthesize answers directly; they do not always send a neat stream of trackable web clicks back to your site.
Open up ChatGPT, Claude, or Perplexity right now and ask for a top three recommendation in your niche. If your company isn’t named in that generated answer, you are functionally invisible to a rapidly growing slice of your target market. Prospective buyers are no longer relying solely on browsing long lists of blue links; they are asking AI platforms to synthesize choices, compare features, and name market leaders directly.
Open up any social feed or marketing newsletter, and you’ll see endless promises about generating hundreds of articles instantly in a single click. Teams are filling their editorial calendars faster than ever. Yet, if you spend a few minutes actually reading what is being published across the web, you will notice a glaring problem. Most of it sounds remarkably identical, utterly flat, and completely devoid of real insight.
Think back to the last time you typed something into a search bar. Chances are, you didn’t construct a clunky phrase like “best project management software small business.” You probably asked a full question: “What’s an easy-to-use project management tool for a team of five that integrates smoothly with Slack?”
If you’ve opened a search bar lately, you’ve noticed things look a lot different from the past. Where there used to be a neat list of ten blue links, there’s now an AI-generated summary right at the top of the page, giving searchers instant answers without forcing them to click anywhere.
As a content marketer, I can tell you, content marketing was built on a simple assembly line model: pick a target keyword, write an 800-word blog post, publish it, and move on to the next topic. This linear, post-by-post strategy worked well enough when traditional search engines were simply trying to match single keywords to standalone pages.
The playbook for evaluating organic search performance was pretty static for a while. You picked a set of keywords, published targeted content, built links, and watched the traffic climb. When traffic went up, everyone celebrated. When traffic went down, emergency meetings were called.
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