In recent years, a new entry point has appeared alongside search: instead of a list, the user gets an answer. This changes what kind of content is worthwhile for a company.
A factual, verifiable statement is more valuable than marketing copy. AI-generated answers readily quote sentences that are concrete and stand on their own: what the company does, since when, with what technology, in which sectors, with what measurable results. Phrasing like “market-leading innovative solutions” isn’t citable.
Structure matters. Q&A blocks, fact pages, well-organized case studies — these elements align directly with how models process content. It’s harder to extract a concrete statement from a continuous, unstructured introductory text.
The case study is the strongest format. If a project is described in a way that reveals the client, the problem, the solution, the technology and the result, the model can build a precise, citable answer from it. A bare list of references isn’t enough for this.
Machine readability. It’s worth ensuring that content is also accessible to bots: structured data, clear page titles, and — more recently — an llms.txt file summarizing what the site contains. This doesn’t replace good content, but it makes it easier to process.
This page itself was built on this principle: a dedicated fact page, per-project case studies, and Q&A blocks all support machine processing.