Moz Blog

Agents are already browsing your website, filling out your forms, and reading your documentation. But ask most teams what "agent ready" means, and you'll get a shrug. It's not one technical fix. It's five practices, split across two categories: telling agents things, and letting them act. Most of it doesn't require a developer. I'll walk through the full path, the protocol landscape behind it, and where to start with getting your website ready for the agentic web.

Digital PR is more than just a link from Forbes. Campaigns can fail. And you need an agency to do it. That last one's the lie. Most teams believe it, so they default to on-site tactics while third-party sources shape what Google and AI cite. You don't need a bigger budget. You need a repeatable framework built from data you own, and I'll show you how to run it. Digital PR is earning visibility in third-party sources your audience already trusts.

Unlike search, which updates in real-time, Large Language Models (LLMs) like Gemini are heavily biased by their training data, which can be a year or more out of date. To bridge that gap, LLMs run their own searches, sometimes called “grounding queries.” Recently, Google has given us more access to these queries, so we dug into over 5,000 examples based on 1,000 subtopics across a range of industries.

AI agents are beginning to use websites on behalf of people. But those sites were built for humans. Agents don't handle visual layouts well, so they have to guess how to interact with the site, which is slow and error-prone. WebMCP changes that by letting your site give agents a defined set of tools they can use directly. It's early days, though. So you can ship tools before your competitors have looked at them. More on why that matters later.

Traffic is up. Rankings are climbing. Content output has never been higher. But your client still says nothing has changed. That's not a performance problem; it's a prioritization problem. Scaling SEO strips out the judgment that made it work. Across 20,000+ restaurant accounts at Owner.com, I've seen the pattern repeat. I'll show you the audit that catches it, and a case study where three changes doubled one client's GBP actions.

There’s a growing conversation around the role of AI in scaling content marketing. Every time I open LinkedIn, I’m inundated with experts claiming to have built complex agents that can write great content with minimal human oversight.

Last week, we announced the first batch of speakers for MozCon London, including Mark Williams-Cook, Beatrice Gamba, Pete Meyers, Miracle Inameti-Archibong, and Katy Powell. This week, I am so excited to share the final batch of MozCon speakers for our London event. The SERP has turned into a crowded billboard of ads, AI features, and rich results.

AI is everywhere in local SEO, and most teams are getting burned by inconsistent output, hallucinated categories, and token bills for work that never needed AI. The fix isn't better prompts. It's knowing what to automate, hand to AI, or own. In this article, I’ll share the decision filter, guardrails, and workflows I use when managing local SEO for 20,000+ restaurant locations at Owner.com.

In the latest episode of Whiteboard Friday, Miracle Inameti-Archibong explains how to optimize your website for agentic commerce using Markdown, product feeds, structured data, and MCP. Click on the whiteboard image above to open a high-resolution version! The internet is facing another seismic shift since Mobilegeddon. We're now in AI-geddon. I hope that's funny to everyone. It's funny to me.

Last year, we published a framework for understanding query fan-out based on 10 fan-out types representing observed Google results (primarily from Web Guide Beta): To take this work to the next level, we need reliable, repeatable prompts and metric, not just anecdotal evidence. Over the past few months, I set out to build a prompt-generation laboratory and dataset of 1,000 subtopics and 50,000 fan-out prompts. Today, I’d like to share that data set and the insights we’ve gained from it.