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When machines can do almost everything, which parts of your SEO work are you deliberately choosing to keep human? For years, SEO has trended toward scale. AI and agents are assumed to be here to finish the job. By 2026, most of what we’d describe as “commodity SEO” will be easy to replace. Keyword coverage, basic content, schema, internal links, meta tags. All solvable, often "well enough". Sometimes better than humans can to do. Which raises an uncomfortable question: If eve

For most of the web’s history, the assumption was simple: humans browse, websites respond. Search engines mediated discovery, but the interaction itself was human-to-site. Agents aren't just answering questions, they’re comparing options, checking availability, monitoring prices, filtering constraints, and increasingly acting on behalf of users. In many cases, they don’t need a visual interface at all - they just need reliable information. This isn’t the sudden arrival of a “

Bot management used to be a relatively contained problem. A small number of well-understood search engine crawlers, a handful of bad actors, and some fairly blunt controls were usually enough. Not any more. Today, there are more bots that matter for visibility, discovery, and commercial outcomes than ever before. It’s no longer just Google and Bing. It’s a growing ecosystem of crawlers, scrapers, training bots, AI search providers, agents, and hybrid systems operating on beha

A lot of the work many of us do can already be done by AI agents. Not perfectly, not end-to-end, but well enough to be useful. For a long time that gap between “useful” and “reliable” was where human job security lived. What’s different as we move into 2026 is that the capability is finally catching up with the hype. The tooling is better. Models are better. Orchestration is better. Memory, retrieval, tool use, scheduling, retries, and guardrails are no longer research projec

How are we going to handle attribution as clicks disappear? AI search is going to reduce clicks. That part is not controversial. The uncomfortable consequence is what follows: fewer clicks means fewer people trigger web analytics, which is still how most organisations measure performance and assign value. The inevitable outcome is that SEO will look like it is getting worse, even when it isn’t. ...likely one of the most important problems we need to solve in 2026. This is not

ChatGPT 5 has been launched and Josh from Profound was quick off the mark  to help provide some more insights into how the search service works. After seeing Charlie share potential System Prompts  (I say “potential”, I’m still not convinced that we can get a super accurate level of information for this) for GPT5, I wanted to sit down and see what was going on in the Conversations event stream, is it any different from ChatGPT 4.1 and does this change anything for how we do o

Splitting SEO (Search Engine Optimisation) and what some are calling “GEO” (Generative Engine Optimisation) is, in most cases, a new...

Is "writing for AI" Just optimising content for chunking? One common recommendation I have started to see when preparing content for AI...

Much has been written about Google's new AI Mode - some of which is particularly awesome. But what it often isn't is super...

TL;DR LLMs.txt simplifies website content into a markdown file for easier AI crawling, bypassing technical issues like JavaScript...

It's surprisingly easy to set yourself up to fail at SEO, despite the best of intentions. Overselling expectations, undervaluing the...

Love them or loathe them, large language models (LLMs) like ChatGPT and Google Gemini have the potential to make fundamental changes to...

Most major LLMs (like ChatGPT, Gemini, Co-Pilot etc) can cite their sources when returning answers. This means links in outputs -...