My regular writing lives on Substack under the name Duane Forrester Decodes.
I cover the shift from traditional search to AI-driven discovery. How retrieval systems work. What’s changing for practitioners. Where the industry is headed and what to do about it. Occasional detours into career strategy, leadership, and the realities of building a professional reputation in a field that keeps reinventing itself.
New posts typically land weekly. Some are free, some are for paid subscribers.
Recent Posts
The Shortcut Behind Some AI Optimization Tools
Why products built on undocumented platform data eventually collapse when the platform evolves
March 8, 2026
Grab a Copy of My New BookOn March 3, 2026, OpenAI pushed GPT-5.3 Instant to all ChatGPT users, free and paid, with no fanfare about what else might have changed beneath the surface. Within days, SEO and AI search practitioners began documenting something unexpected: the internal metadata that had allowed third-party tools to observe ChatGPT’s query fan-out behavior (the sub-queries the model generates behind the scenes before composing a response) was no longer visible.A German SEO publication, SEO Südwest, published a detailed account on March 7th, noting that researchers Chris Long and Jérôme Salomon had independently observed the same thing...
The Verified Source Pack Agents Trust First
The practical guide to shipping a verified source pack that turns your policies and product truth into machine-consumable facts
March 1, 2026
Structured data helped machines interpret pages. It reduced ambiguity. It made entities and attributes legible to crawlers that were otherwise guessing.Agents change the job because they do not just interpret pages. They decide, summarize, recommend, and sometimes execute. That means they need more than “this page is about X.” They need “this is the official truth about X, it is current, and you can verify it.”That is the gap most teams have not addressed yet.If you are a technical SEO, you’ve already done the hard part of this job in other forms. You’ve built crawl paths, canonicalization systems, change control...
When Google Is No Longer a Verb: Search Becoming Infrastructure
As agents improve and spread across more surfaces, discovery turns into a subscription habit, and the work of search gets delegated.
February 22, 2026
Before we get into this week’s article, are you looking to learn more about AI, LLMs and search, to find new ways to track results and define new metrics to describe what you’re seeing happening with traffic? My new book, The Machine Layer, has all that and much more. It’s worth checking out. OK, now let’s dive into this week’s article!Most people do not wake up one day and decide they are done with a product category. They leave when the workflow starts to feel like work.Think about something mundane. Planning a trip, picking a new doctor, comparing two insurance...
Why AI Misreads the Middle of Your Best Pages
Why models drift in the middle, why systems compress it away, and what to change without rewriting everything.
February 15, 2026
Frameworks, guidance & more at AmazonThe middle is where your content dies and not because your writing suddenly gets bad halfway down the page and not because your reader gets bored. But because large language models have a repeatable weakness with long contexts, and modern AI systems increasingly squeeze long content before the model even reads it.That combo creates what I think of as dog-bone thinking. Strong at the beginning, strong at the end, and the middle gets wobbly. The model drifts, loses the thread, or grabs the wrong supporting detail. You can publish a long, well-researched piece and still...
The Classifier Layer: Spam, Safety, Intent, Trust Stand Between You and the Answer
SSIT is the invisible funnel that decides what gets retrieved, used, and cited.
February 8, 2026
Get My New Book on AmazonMost people still think visibility is a ranking problem. That worked when discovery lived in ten blue links. It breaks down when discovery happens inside an answer layer.Answer engines have to filter aggressively. They are assembling responses, not returning a list. They are also carrying more risk. A bad result can become harmful advice, a scam recommendation, or a confident lie delivered in a friendly tone. So the systems that power search and LLM experiences rely on classification gates long before they decide what to rank or what to cite.If you want to be visible...