AI in search and marketing
AI tools, search and connected workflows need different kinds of evaluation. These articles explain the business task first, then the model, data access and review steps needed to support it.
Compare a proposal against representative questions and failure cases. Define which actions need approval, what happens when a tool fails and who reviews the output. A vendor benchmark and a measured result from your own workflow are different evidence.
Start with the SEO checklist for how AI Overviews affect click-through page by page, then content marketing after AI answers for what to publish when the summary is free.
Generative Engine Optimization: a practical guide for service businesses
A useful answer starts with a page worth visiting. Keep the SEO foundations, make your service information specific and measure what happens after someone finds you.
Sam K
Agentic AI CRMs: what to automate before the next sales call
A sales agent can prepare the research, update the record and draft the follow-up. Start with a workflow your team can check before handing it the next customer conversation.
Jev AI vs Claude vs ChatGPT (2026): When to Use Decision Models, LLMs and Agents
The useful question is no longer which model is smartest. It is which part of your system needs judgement, which part needs language, and which part should be ordinary code.
AI agents for small businesses: choose a bounded first workflow
Choose a recurring process, define permissions and review, and measure the result before expanding the automation.
Answer Engine Optimization: clearer service pages and measurable enquiries
Start with what a buyer needs to choose a supplier: clear scope, evidence and a useful next step. AI citations are an observation to measure, not an outcome to promise.
Advanced SEO for 2026: entities, internal links and AI citations
A page-level method for diagnosing indexing, reviewing consolidation and measuring a meaningful SEO release.
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