Product knowledge as scalable digital training

Why product knowledge resists training

Agri-input portfolios are large, technical and specific. The same active ingredient behaves differently by crop, by stage and by region, and the people who need to explain it are usually in the field rather than at a desk.

That combination defeats the usual response, which is to convert the product literature into slides. Literature is written to be referenced by someone who already knows the domain. Training has to work for someone who does not yet.

Structuring before building

The engagement began with content analysis rather than production: reading what already existed, finding where the same fact appeared in two forms, and separating what had to be learned from what only had to be findable.

Product knowledge structuring turned that into a consistent shape across the portfolio, so a new product could be added later without redesigning the programme around it.

Built to be organised, not just uploaded

Digital learning content, assessments and supporting resources were developed against that structure and organised for the LMS — sequenced, named and grouped so a learner moves through them in an order somebody chose.

The same structuring was carried out in an AI-ready form: content organised so it can later be retrieved and answered against, not only browsed. That is groundwork, and it is described here as groundwork rather than as a deployed assistant.