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.

Not all technical debt is worth paying off. A way to decide which problems to fix, which to contain and which to ignore.

Agent costs are driven by steps, context size and model choice, not by the number of users. Each can be measured and limited.

Data readiness is not about volume. Six checks show whether your information can support an AI system, and what to fix if it cannot.

A demo proves an agent can work once. A test set built from real cases shows how often it works, and where it does not.

A handful of checks covers most real incidents. What to monitor first, what to alert on, and how to keep alerts from being ignored.

An agent that can act needs limits that do not depend on the model behaving. A practical way to sort actions into free, approved and forbidden.

Most lead scores are ignored because nobody can explain them. A score built from a few visible rules and checked against real outcomes gets used.

Leads go cold while they wait. A dependable capture, a useful first reply and fast routing to a person fix most of the delay.

Structured data tells search engines what a page is about in a form they do not have to guess. A short list covers most business sites.

Have a problem you're trying to solve?

We're always happy to talk it through, no pitch required.