GenAI training and the search engine parallel

Doing the monthly update for our GenAI foundation course today gave me a strong sense of déjà vu.

It took me back to the early 2000s, when I was first involved in building training around how to use search engines effectively. At the time, there was much discussion about which search engine people should use. But what mattered far more was whether people knew how to ask a good question, how to choose the right keywords and phrases, and how to adjust their approach when the results weren't quite right.

Very quickly, you'd realise that the first query was rarely the best one. You'd scan the results, notice patterns, tweak the wording, try a different angle. And then you'd do something else just as important: evaluate what came back. Was the source credible? Was it relevant? Was it current? Sometimes that meant digging deeper, sometimes discarding it entirely and starting again.

In other words, it was an iterative process. Question, response, evaluation, refinement. Over and over again.

What struck me was how closely this mirrors what we're teaching with GenAI today. Prompting, iteration, experimentation, critical thinking, judgement. The tools are very different, but the underlying capability we're trying to build feels remarkably familiar.

Back then, the challenge wasn't about deploying search engines. The technology was already there. The real work was helping people develop the habits and mental models needed to use those tools well. To think clearly about what they were looking for, to interrogate the outputs, and to adapt their approach based on what they were seeing. Recognise this pattern?

Today, there's a lot of focus on rolling out AI tools across organisations, but the presence of the tool is not the hard part. What determines value is whether people know how to work with AI capably and thoughtfully. Once again, the challenge isn't deploying the technology. It's building the capability to use it well.