Shifting Roles - From Content Professionals to Ontologists

By Mark Wentowski

Content pros are encountering new challenges in the Large Language Model (LLM) and agent era, highlighting the need for a different approach to authoring tools. Trust in LLM-generated content is the next hurdle, and transparency about the LLM’s information sources is needed.

Underscoring this, LLMs’ answers are only as good as the source content, which, in most cases, will be proprietary and will not be part of an LLM’s general intelligence about non-proprietary sources like blog posts. So the LLM needs to be an expert on your product, and someone needs to author this content, either with or without AI assistance.

The Current Paradigm

Right now, most authoring is aimed at publishing content for people. While chatbots can use this information to answer questions, the content isn’t designed with agents in mind. Humans remain an important audience, but we also need source content that works well for both LLMs and people. Similar to how web design shifted to a “mobile-first” approach, we could move to an “agent-first” design for documentation. This doesn’t mean humans are less important; it just means that focusing on agents is more challenging but will still meet human needs.

Related: AI-Powered Authoring: Will Machines Replace Technical Writers?

The Shifting Role of Authors

Authors should always retain the freedom to “just type something” in an editor, but moving forward, a bit more discipline will be required. As LLMs and agents become more adept at generating content (especially when supplied with verifiable facts) the role of the human author is evolving. Their primary responsibility will shift toward establishing a foundation for content verification. This includes building taxonomies, which might be generated automatically from source material and then refined by the author, or created manually for maximum control by a discerning analyst. Additionally, authors will help map product concepts to ontologies to enable deeper and more meaningful interconnections.

Taxonomies: How to Find Things

A taxonomy organizes items into categories within a clear hierarchical structure, much like a tree with branches and sub-branches. Each item is assigned to a category, making it easier to find by moving from broad groupings to more specific ones. These relationships typically take the form of parent-child or sibling connections.

We see taxonomies every day—for example, website navigation menus that let us drill down from broad categories to more specific items.

Why do taxonomies matter?

According to Earley Information Science:

Related: What Is the Difference between Taxonomy and Ontology?

Consider a grocery store: its organization is a practical example of a taxonomy in action. Products are grouped into clear categories:

• Produce → Fruits → apples and bananas

• Dairy → milk and yogurt

• Meat → Chicken and beef

• Bakery → Bread and cookies

This system shows you exactly where to find items. It’s hierarchical and structured, so you won’t find yogurt in the cereal aisle. The main benefit is efficient organization and quick retrieval.

If the grocery store had a website, its taxonomy would guide how you browse and filter products online. The site’s navigation and structure often match the store’s taxonomy, helping users find what they need.

For writers, setting up a taxonomy gives a clear framework for structuring content, building page hierarchies, and making internal tables of contents. Rather than starting from scratch, a good taxonomy gives you an organized starting point for creating content.