From the lab

Ideas, engineering, and lessons from the field.

Practical thinking on AI, software, infrastructure, and building technology that works in the real world.

Keyword Research: Start with Search Intent, Not Volume

A keyword with high volume and the wrong intent brings visitors who leave. How to pick searches that match what you sell.

Most ranking losses after a relaunch are avoidable. A checklist for before, during and after the move.

The handover is the part of a chatbot customers remember. Clear triggers and a handover that carries the conversation make the difference.

Three numbers describe how a page feels to load and use. What each one means, what counts as good, and the fixes that move them.

Releasing without taking the site offline is mostly a database problem. The main approaches and the one technique that makes them work.

A chatbot can only be as good as the content behind it. A short content audit before the build prevents most quality problems later.

A backup that has never been restored is a hope, not a safeguard. What to back up, where to keep it and how to prove it works.

When a chatbot answers wrongly from your own documents, the model is rarely at fault. The search step in front of it usually is.

The questions that reveal how a development company really works: ownership, people, estimates, quality and what happens when you leave.

A working demo is the easy part. Pilots stall on integration, ownership, evaluation and trust, all of which can be planned for.

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