Practical experiments and analysis of AI in analytics, marketing and search. Topics include hands-on tool testing, AI traffic and visibility measurement, agents and the real effects of emerging technologies.
In September 2018, I wrote the first version of an article about how to become a web analyst. I recommended building your own test website, using Google Analytics, Google Tag Manager, working with spreadsheets, learning step by step, gaining experience in online marketing, staying technically curious and being willing to help others. Eight years later, […]
Marek Prokop asked a simple but important question on LinkedIn (discussion in Czech): do we still need Google Tag Manager now that an AI agent can implement tracking? For the first time in thirteen years, he left it off a new website. AI can inspect a repository, find the right place, modify the code, run […]
Short version: I expected more from Google. Not because Gemini 3.5 Flash is an unusable model or because Antigravity has no direction. The problem is elsewhere: Google showed a lot of things that look like major steps forward from the outside, but in real-world use they currently feel more like a more expensive, more closed, […]
Does llms.txt actually make sense? For an ordinary website, probably not today. As a documentation hub for LLMs and agents, perhaps. But there is a major difference between the file existing, a crawler downloading it, and an LLM provider actually using it to make production decisions. Public evidence for the last point is still missing.
AI in the browser sounds like a convenient feature. Page summarization. Writing assistance. Searching across open tabs. An agent that browses the web for you, compares offers, or fills out a form. Technologically, it makes sense. The problem isn’t AI in the browser itself. The problem is who is introducing it, how they are introducing […]