Non-commodity content, dialogic communication and goose-bumps on a boat, not counting the knowledge graph

What is alive in you today? What makes you click? Aren’t you a bit content fatigued- all these waterfalls of content?

Faced with infinite streams of content, what would make you stop and read?

This is the question that I have been thinking about lately. What should a text do? How would a text help? In my bubble – where I produce (what a word! ) content daily, why and more importantly, how do I stay true?

It seems to me that these days, somewhere along the way, enterprise content became obsessed with optimization while forgetting dialogue. We optimize headlines, metadata, conversion funnels, we speed up publishing velocity with AI-generated content and work hard to star AI-ing everything.

And that gold rush for eyeballs, traffic and qualified leads, we forget something. Us, our human side. It is so much that we fell in an oblivion of what text does by default, that we now need to say not only create content, but define it with two even three adjectives It is truly remarkable to me  how that the word “content” became so semantically empty and how we need to put modifiers to recover what should have been its essence –  valuable, non-commodity, and even worse – helpful, reliable, people-first. As if those qualities were an enhancement rather than the baseline. 

It is about all that jazz that I just described, that me and Jason Barnard talked about in the Kalicube Summit 2026: Non-Commodity Content, Meaning-Making, and the Living Knowledge Ecosystem. 

It is a talk about knowledge graphs, mess, control and what that means for your content writing practice <3

In our preliminary meeting with Jason  we decided to cover the philosophical foundations behind the intersection between Semantic Web, dialogic communication  and what it takes to create valuable content. 

Of course that was much more ambitious than what we achieved and still, here’s this text with which I want to summarize and elaborate on some of the emergent findings from the talk. Throughout the process I also felt like creating guiding questions to ground that conversation into practical advice.

I hope you will use them in your work and together we will make the Web and its text a better place to collaborate and co-create value in.

The experiential side of knowing

At the beginning of the conversation, we dove straight into the mess of knowing. That’s because I believe we should think about content not as an artifact, but as a vehicle through which we travel our own inner understandings together with the shared understandings of others. And that, to me, is the real “so what” of content when we talk about knowing, knowledge, knowledge graphs, and knowledge retrieval. 

Jason asked me where do feelings come into AI-assisted optimization?

I asked back. Where does AI-assisted optimization fit in the world of feeling, emotions and being human.

I wanted us to reverse the narrative, as it is text that comes first, as an act of poiesis, and emerging extraordinary creature. When this is the starting point of the conversation, it is easier for us, as human beings and as writers, to reconnect with the genuine driver of text. And that driver is not optimization. It is the need, the desire, the act of reaching out to connect. 

That said, before we optimize for search, retrieval, engagement, or conversion, I suggest we reconnect with the human impulse that gives the text its purpose and imbues it with authenticity. 

So what for content (Questions to guide your content writing)

1. What human need, desire, feeling, or question is my text trying to meet?

Before writing, name the real human need behind the search or request: what is this person trying to solve, understand, feel, decide, or become?

2. What do we want the reader to understand, feel, or recognize in themselves as they move through the text?

Define the shift you want the reader to experience, then make every section of the text contribute to that shift.

3. How can AI-assisted optimization serve that human connection rather than become the reason the text exists?
Optimize the language, structure, entities, and retrieval signals only after the human purpose is clear, using AI to make the connection easier to find and understand, not to manufacture one.

Knowledge Graphs and the So What for Content

This is where the conversation arrived at one of my favorite concepts: the technical assemblage. 

he assemblages theory has it that:

An assemblage is comprised of objects and their connections, which combine to make up interconnected arrangements with their own functional properties and capacities. An object can be anything that has an effect on the world: humans, technology, animals, policies, or opinions. An assemblage can be any arrangement of objects: a football team, a zoo, a large-multinational, or a language classroom. Key to an assemblage is its co-functioning; that an object’s capacities only become realised in relation to other objects. For example, a teacher may use a mobile device to revise a particular language point. The technology on its own does not have the capacity to be used for language teaching.

cit. Assemblage theory: coping with complexity in technology enhanced language learning

I find the theory of assemblage particularly useful for thinking about content because it acknowledges two things that exist simultaneously: the deterministic structures we build (that is structured data, facts, taxonomies, knowledge graphs, predetermined ways of relating)  and the living ecosystem of people who use, interpret, enrich, and sometimes unexpectedly transform those structures. 

To put that into the real-world, think about how we can design the park, map the paths, place the benches, and define how everything is supposed to work; but once people enter the park, they create their own paths, find new ways to use the space, sit on the bench in ways we never anticipated. 

The same is true of knowledge systems (the emptiness that holds the content vessel <3). 

There are the structures we deliberately construct, and then there is everything that grows around them: the interpretations, connections, behaviors, questions, and unintended uses that emerge through human interaction. This is where I see the real value of content creation emerging: in noticing that living layer of knowledge and bringing it into communication. Good content does not simply repeat what has been structured. It explores the spaces between the structures, the paths people actually take through the text.

So what for content (Questions to guide your content writing)

1. What is already structured, known, and predetermined  and what is happening around it?
Start with the facts, categories, entities, and relationships, but look beyond them to the human behavior and interpretations that are emerging around them.

2. What unexpected paths are people taking through this knowledge?
Look for the questions, associations, behaviors, language, and connections that do not appear in the formal structure but reveal how people actually understand and use the subject.

3. What can we create in the space between the structure and the lived experience?
Use content to capture emerging connections and turn them into something useful, relevant, and meaningful for the people navigating the knowledge landscape.

Mess And Control: It Is Not Either Or, It’s Both and So What for Content

This is where Jason mentioned Google’s Knowledge Graph, which is built intentionally, and there is control over it, versus the open web. Jason was curious about that uncontrolled mess versus the controlled Google’s Knowledge Graph. My take on this with content is again around that constant dynamics, which we need to turn into an equilibrium. 

Two things come right away to my mind (and I couldn’t voice that in my 30 minutes :)). The first is is what Atanas Kiryakov taught me in my work with building the Ontotext Knowledge Graph – you don’t have to reinvent the wheel, it is always a good idea to reuse existing knowledge. And the second thing is something that the author of Connected Content, Mike Atherton, once said: If you don’t have content, steal it from the hippies. 

These said, for content, the real opportunity I see in the communication between the above two notions – both converging in the point of sharing knowledge.

A controlled knowledge graph does not need to reinvent everything it contains. If we are creating a concept such as SEO, for example, we can connect to existing definitions and relationships in sources such as Wikidata or other Linked Open Data cloud, and then build on that shared knowledge with our own context and perspective. 

And this is how content becomes dialogic: it does not speak in isolation, but participates in an ongoing conversation with other people, other sources, and increasingly, other machines. The point is not to choose between control and mess, but to create an equilibrium in which structured knowledge can remain connected to the living, changing ecosystem around it. 

So what for content (Questions to guide your content writing)

1. What existing knowledge, concepts, and relationships should this content connect to rather than recreate?
Identify the authoritative sources, entities, definitions, and related concepts already available, and connect your content to them.

2. What does this content add to the conversation, what is its unique perspective, interpretation, or connection?
Clearly identify the insight, experience, interpretation, or new relationship that makes your content meaningfully different from what already exists.

3. How can we make the content understandable and meaningful to both humans and machines, so it can participate in a larger ecosystem of knowledge?
Use clear and plain language and structure, explicit entities and relationships, and appropriate links and metadata so both readers and machines can understand how the content fits into the wider knowledge ecosystem.

Non-Commodity Content as Maintaining a knowledge Garden (or Graph, as you like it)

This is where, at the end of the conversation, Jason woke up 🙂

We talked about non-commodity content. To me, in its simplest form, non-commodity content is statistically improbable. It is what happens when writing goes beyond reproducing the patterns that already exist and pushes the writer to the edge of their domain, to the edge of what they know, where genuine thinking begins. 

We are surrounded by an enormous sea of knowledge, and AI can increasingly produce perfectly plausible content from that sea. 

Where the value of writing (and thinking) lies is in creating unexpected relationships to make the person on the other side of the text stop and think differently. That is the experience we are looking for. It is not about time spent on a page or about generating giant fields of text that say nothing. It is about creating conditions for a genuine dialogic communication to emerge.

We are emotional beings, not purely logical ones, and what makes content memorable or meaningful is not always what is most statistically likely; sometimes it is precisely what surprises us. Non-commodity content, then, is not about being different for the sake of being different. It is about thinking deeply enough to produce something that could not have been predicted from the existing pattern and will enrich your reader.

So what for content (Guiding questions)

1. What can I say that is genuinely mine to think?
Push beyond the obvious answer and write from your own experience, observation, interpretation, or unresolved question.

2. Where can I interrupt the expected pattern?
Look for the assumption everyone makes and explore the unexpected connection, tension, example, or perspective that could make someone think differently.

3. What do I want to invite in the mind of the person reading this?
Give the reader something to notice, question, feel, or reconsider rather than simply giving them more information.

Epilogue: You say Data, I say Dialogue (Again)

Content should not merely be an output machine. It should be the artifact of knowledge exchange. A drop in the sea of shared knowledge (reminder the Web is not a giant TV, ref. https://www.w3.org/community/webhistory/2018/01/07/links-fractals-and-information-plumbing/)

We should more often ask:

• What is genuinely alive in this organization today?
• What are we trying to understand together?
• What uncertainty are we willing to acknowledge?
• What conversation are we inviting people into?

Let’s do it. Let’s make the Web a better text!

Want to take these ideas from theory into your own writing? If you want to explore what it means to write content that is meaningful to people, legible to machines, connected to knowledge, consider joining my self-paced course Content Writing for the Web of People and Machines.