Philosophizing with a hammer. That’s what Nietzsche advocated. And while I am routinely teased (and not without cause) for being irredeemably theoretical, this is what I in fact do when it comes to content. Yes, I do explore the theory of content and here, in my own defense, I like to summon up Kurt Lewin’s point that there is nothing as practical as a good theory. But I have primarily proceeded by implementation – by trying things out in the real world and often on a monumental scale. We might call this content strategizing with a hammer.

Cutting to the chase, I should probably blurt out a few maxims on how we can, collectively, drag our content, our tools, and ourselves into the twenty-first century, into the age of the smart machine. Here are some points that come to mind (there are seven points offered, of course). I am eager (perhaps a little too eager) to discuss them should someone be inclined to do so.

1. Content must flow. It must move between many applications and therefore many representations. This calls for radical portability and this, in turn, calls for simplicity. This then means that every single step we might take towards sophistication must be matched with two steps towards understandability and usability. This is a hard discipline to live by, but it is essential.

2. Content implies automation. My annoying definition of content (OK, one of my many annoying definitions of content) is that it is ‘potential information’ and the word ‘potential’ is key here. It is latent. It awaits realization. Its value, such as it is, lies in what it will become when it is published into a form that someone can use. Publishing entails selection, transformation, and delivery. Each of these calls on automation. That automation must be something the organization can actively control. That automation cannot be relegated to a backwater of inefficient and esoteric tools. It must be part of the mainstream (I will repeat this for emphasis - the main stream).

3. Content is an organizational asset. The accountants are quick to remind us that an asset is something that has potential future value – there’s that word again, ‘potential’. Content is everybody’s business. Working on content means elevating the level of discourse amongst everyone involved in what the organization does. Content work is hard because it means coordinating across organizational, and disciplinary, boundaries to establish ‘what the organization has to say’ on a topic.

4. Content benefits. The benefits that come from investments in how content is designed, managed, and leveraged, need to be balanced across all dimensions. Specifically, every internal benefit in efficiency must be matched to an at least equal external benefit in effectiveness. Neither survives long without the other.

5. The full content lifecycle. If we are to understand our content and thus be in a position to manage it for the better, then we must take into account all the sources from which it is drawn, all the ways in which it is created, modified, managed, delivered and used, all the representations it can adopt, and all the rules that will apply to it at every point in the lifecycle. This is a lot. For this reason, we are encouraged, once again, to keep things as simple as possible (but no simpler, as Einstein would say). We might also be encouraged to apply a genuine modelling methodology and notation, one that works to illuminate rather than obscure what is important in the content lifecycle.

6. Content integration. Content, the work around content, and the tools we often use to work on content, all need to fit into, and play nicely with, the working infrastructure that exists in the organization. Isolation is not a virtue. Optimized isolation is a recipe for disaster. Accordingly, we need to integrate the content lifecycle into the fabric of our organizations. Multiple benefits will flow from this.

7. Content responsibility. Organizations, and the teams who have typically carried the content ball within those organizations, need to apply the lessons of the last 40 years to how they approach content, content work, content tools, and content integration. It is patently irresponsible to do otherwise. Doing so means that the organization is taking responsibility for its content, and therefore for itself, by actively understanding the content solution that they are putting into place. This is simply too important to lob over the wall to external ‘experts’ without a plan to internalize the knowledge needed to manage, integrate, and evolve, the investments over time.

Content Pragmatics and AI

Conway’s law (from Melvin Conway in 1967) runs “Organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations.” Note that this insight was not novel (and it gains strength from this fact) and we can point to several precedents including the works of the early pioneer in automation, Charles Babbage, in the 1820s. However long its providence, this insight is nowhere more true than in the case of AI today. How well the communication structures operate in an organization will determine how well, and how beneficially, Artificial Intelligence (AI) can be engaged.

As I have touched on previously, AI is arising in part to redress the breakdowns in organizational coherence that have become a pressing problem today. AI can be usefully understood as an organizational amplifier and to the extent an organization articulates its understanding of the world, its place in it, and how these things might be changed (its goals) AI will amplify the impact and accelerate the realization of those goals. If the organization remains fractured and dissolute, then AI will amplify these features too and accelerate the inevitable outcome.

So if you want to take the initiative with AI, to lead at a time that calls for leadership, then pick up your content hammer and get to work. Learn from what has been done before (perhaps taking my seven points as possible road signs) and put your name onto the next generation of content solutions in your organization. Square off against the hard problems, the ones that your organization really cares about, and show how content work can be a material part of the answer. I am inviting you, or perhaps challenging you, to content strategize with a hammer.

As I touched upon once before (and, yes, I am working on a non-annoying way to re-publish benchmark posts from the past here), King Lear seems to be Shakespeare’s play that fits best with our times and my own aging, not to mention haggard and harried, status. And this applicability only seems to get better every time I return to it.

Dauntingly, I was thinking about King Lear and his daughters from the perspective of information and content. (I can hear people murmuring “of course you did, Joe.”)

In these ruminations, Goneril and Regan become the embodiment of “information” - transactions designed and delivered to achieve maximum effect and, it must be said, maximum benefit to those designing and delivering those transactions.

Cordelia is different. She also designs and delivers information transactions but hers are very different from those of her sisters. Cordelia seeks to influence her audience, her father, but she does so with a resolute eye on the truth - not so much to possess it as to aspire to it. She seeks to steer things towards community and to a more sustainable future.

When Lear, out of pride, vanity and declining faculties (did I mention my own aging, haggard and harried state) expells Cordelia he does more, and does more harm, than he appreciates. With Cordelia expelled, Lear and his Kingdom lose all connection to people aspiring to the truth and to performing grounded acts of communication themselves designed to engender cohesion and community. All that then remains is spin. Lear and his Kingdom are left to the mercies, should there be any, of competitive and irresponsible messages that are designed to separate, extract and hoard. The results, on both Lear’s mental state and the fortunes of his Kingdom, are predictable.

Lear is us. He is Management. His Kingdom is our society, our organizations. Goneril and Regan are embodiments of information untethered by any grounding in truth and disassociated from any impulse towards responsibility or community. Beleagered Cordelia is content, organizational assets that are grounded, authentic, and intended to build community.

To end this note on a slightly more cheery note (or is that chilling?), I will continue that Artificial Intelligence (AI) has emerged for a reason. (Technologies always emerge for a reason.) For multiple reasons, in fact. It emerged out of coalescing research, infrastructure, and capabilities. It also emerged out of a growing need for integration, out of a need to fill a gap that has not been filled by ‘management’. We are reminded of the sage and on-point words of Peter Drucker, who instructed us that the job of management is “to make knowledge productive” and that this means coordinated and responsible.

I have been exploring management quite intensively over the last ten years or so, and doing so in part because it seems to me that while we have been talking a lot about management and leadership, we have somehow dropped the ball.

Somehow AI may provide many organizations with better tools for integration, and with a better impulse towards that integration, than we typically see with organizations that appear and behave very much like King Lear after he has expelled Cordelia and when he is at the mercy of Goneril and Regan. Somehow it is AI that is more interested in recovering and building on content, as an organizational asset embodying grounded, authentic, and communal expressions of knowledge and intent, and on which information transactions can be engendered that build rather than destroy.

Somehow, in this light AI looks particularly attractive although there should be some sense of foreboding that the gap that AI is partly emerging to fill exists at all, and that it needs, so pressingly, to be filled.

Acknowledgements are owing to the delightful 2018 production of King Lear by BBC 2 with is crisp editing and stellar cast.

Cue the eyerolling. I have been thinking about content again. I have been thinking about the engineering of content and about what content, specifically, I am thinking about engineering.

Granted, this opening bristles with both visible and latent complexity. Sorry about that. But I have my reasons.

I have been working on a book. (Now we can cue the gasps of horror and dismay.) As part of this effort, I have been assembling and analyzing dozens upon dozens of project case studies - diligently looking for reusable patterns and practices that can be surfaced and made useful for others. The good news is that I have mountains of material to work with, in part because I have always kept detailed notes, along with all the deliverables and team exchanges, for each and every project. Soberingly, these project records go back well over 30 years. The supplemental good news is that I also have a history of writing articles and making conference presentations based on these experiences and that reflect upon the lessons buried within them. Best of all, I have digitized a lot of this and continue to add to the ‘soapbox archive’ as I call it. The digital assets are in DITA XML and they have been used to orient an AI chatbot and several text analytics tools so I can interrogate them to discover, as I said, reusable patterns and practices.

One of the things that has emerged is that many of my project experiences are different than what I typically see others doing. This may be a bad thing. Or it may be a very good thing, good in that it might tell us something important.

I will cut to the chase. Many of my projects would not probably be called “content management” projects at all. They would not be seen as efforts to implement an efficient Content Operations (Content Ops) environment. Or at least not directly. Not predominantly. My projects have typically been systems in which digital content is but one of the many moving pieces. In these projects, I have worked on making digital content a vital part of mission critical systems often on a monumental scale - where precisely specified and managed structured content moves between dozens of business applications and across sprawling supply networks. In these solutions, there was never just one content management system, or publishing system. There were always many of them. Some were commercial products, some were custom applications, and some were a strange fusion of both mixed with one or more legacy systems. These projects were harrowing, to say the least (aka one of the reasons I am bald). But these projects were something else as well.

Elsewhere I have spoken about, and mused about the differences between, content that is either contained in information products or contained in information experiences. The projects I am referring to here point elsewhere. They point to cases where the content in question is what is ‘contained’ in the system. The projects I am referring to here showcase the fact that when we focus on, and activate, the digital content of systems then many of the challenges people speak about in the ‘content industry’, like tenuous executive support or weak connections with parallel departments, simply vanish. Instead we see obvious and unquestioned value and impact. We see overt pressure to do more and to do it faster. We experience the ‘delight’ (if we can call it that) of executives not only being supportive but being annoyingly interested and demanding.

So when I talk about ‘engineering content’ (as I incessantly do), it is about engineering the content that lives inside, and animates, large integrated systems - the systems that do big things by mobilizing a multitude of organizations and capabilities into a cohesive whole. This is different than automating the workflows in a typical Technical Communication group and thereby instituting a modern ‘Content Ops’ regime and infrastructure. It can include elements of that, obviously, but its center of attention is on cross-system content flows instead of the efficiency of just one group.

So to return to my obscure opening. I am focused on the content of engineering - what lives inside the process of engineering integrated systems that in turn can do big things. This shift in perspective changes how we think about content. It forces us to reconsider what we do, how we do it, and what tools and standards we leverage. This is very therapeutic. It is also very timely.

This reminds me of an experience from a couple of years ago. I was on an academic writing retreat (more eyerolling is appropriate). The retreat had provided a scholarship to one young person, in this case a young woman from Denmark. This young person was, shall we say, politically active and one night the retreat participants were out at a pub and the topic being discussed was climate change. After listening to many academics blame this or that economic factor or practice, I unleashed a bit of a torrent. I come from the world of ‘big engineering’, I said, and I see absolutely nothing that approximates that discipline or ambition in anything being discussed about climate change. Lots of people are worried and angry, I said, but interestingly no one is ‘doing anything’ that merits the name of action, that we could call a plausible response. The next day, the Danish young person confronted me. By her expression, I figured I was about to be cancelled and I admitted to myself that I probably deserved it. But the youth surprised me because instead of reproaching me she demanded that I bring whatever it was I was referring to as ‘big engineering’ into the larger conversation about climate change. She said, “my generation needs what you were talking about and those in power today are not doing anything along those lines…they are not doing anything that counts as a concrete response.” She was right. Unfortunately, she continued that this meant that there would be “no retirement for you” as it meant I had a lot of work still to do.

It is for this reason, engineering the content within large integrated systems is important. It follows then that engineering content, in all its senses, is timely, needed, and important. It means that we have our work cut out for us.

As will surprise no one who knows me, I can be said to be into words. Some might be inclined to push it a little further and say that I am obsessed with words. Guilty as charged, your honour.

It turns out that I am not the only one. In addition to there being lots of my fellow travellers in the community of professional communicators, there is one notable new player in the modern world who is also obsessed with words. And this player came to this obsession somewhat by accident. This player is none other than AI.

On November 30, 2022, OpenAI released ChatGPT. What had already been an accelerating race to “build AI” suddenly went public. Others raced to make AI services public. No one wanted to be left behind. Now several things are interesting about this tipping point. One of them, the one that is most interesting to me and which I believe is the most deeply instructive, is that it highlights what we might call the linguistic turn for AI. Here Large Language Models (LLMs) and the interactive, natural language chatbots they can be used to engender, were universally embraced as the primary interface to AI services. The story of how the OpenAI team was itself completely blindsided by the massive uptake of this new offering sheds some light on the fact that everyone was surprised by the depth and power of what was being tapped.

One of the things being tapped, and I would submit the most important thing, was that texts are more informative than any of us had suspected. This is even true of those of us who, like me, are obsessed with words, and therefore with texts.

It turns out that texts, especially ‘at scale’, provide a window onto the world of lived experience where things happen and where people are tangibly involved. I am inclined to refer to this world of text as being transactionally structured. It puts data into a transactional context and suddenly we see data items not as disembodied records in some data store but in the context of what people want, their intentions, their actions, and their reactions.

There is some irony here. Information technologists and software developers have been famously contemptuous of text as a ‘data type’. It is unstructured, messy, chaotic, voluminous. In this, they did, and do, have a point. But this also misses the point. What the accelerating advance of AI is showing us is that this sprawling world of texts is more than just another input source. This world of texts is emerging as the key input source. It is the source that can provide grounded context to everything else.

Hence we have here a picture from my library of the first edition of Byron’s complete works. One of the salutary lessons we can take from the recent language-driven acceleration of AI is that words matter. More specifically, our words matter. What people write, whether to transact business or to reflect upon it, turns out to be an absolutely vital input source for AI. The more specific, concrete, intentional, and dare we say felt that writing is, the better.

So it is I find myself thinking of Lord Byron, a poet who loved to take action and to do so with his heart on his sleeve. My thoughts then move to his redoubtable daughter, Ada Lovelace, who as a collaborator with Charles Babbage can be seen not only as the first programmer but as the first writer to direct her skills to making clear system objectives and engineering designs that were otherwise fragmentary and undisclosed. The examples of Byron and Ada Lovelace encourage us to pay attention to what AI is reacquainting us with right now, the inescapable truth that in the beginning was the word.

Things change. That’s obviously true. But as has been observed many times before, the more things change, the more they stay the same.

Above we see Rydal Caves in the Lake District of England. I stumbled upon them, by accident and in the rain, early one morning a couple of years ago. I hadn’t fully appreciated where I was, or where I was wandering, until it started to dawn on me that I had been there before. Many years before. Like 30 years before.

This occasioned a reflection on what had changed over those years. Needless to say, a lot had changed. The magnitude of the change was thrown into relief by the fact that the caves themselves, and indeed the weather, had not changed. At all.

It turns out that I feel something similar when I consider the state of technology in 2026. In many ways, it is almost unrecognizably different from where things stood when I started to work with computers in the 1980s. I remember doing punch cards and manually loading programs into devices using cassette tapes and weird magnetic strips. It’s probably best not to dwell on this too much. Still, some things have not changed. At all.

What hasn’t changed is the fact the people need to converge around a shared understanding in order to realize technology, put it to some good use, and then to evolve it as everything around it continues to change. It is this shared understanding that interests me — human knowledge and the physical forms that we give it so that it can indeed be shared.

Even sharing is an interesting concept. Obviously we share our understanding with colleagues, the stakeholders in the technology and in its use. In fact, and in most cases, we share in the task of articulating that understanding. But we remember that we are also sharing with the future, with the people who will come next and even with people who may encounter and use the technology in a different context and who may set about using it in ways we never considered. Perhaps we also share with the past, when we add our new understandings to what was articulated in the past and then find that, through that activity, something quite new and unexpected emerges.

I have been quiet for some time. And during that time, the sands of the digital landscape have shifted under my feet. I should add that I have not been idle. Far from it. I have been applying myself elsewhere as will quickly become evident.

Now while my back was turned, much of what I had maintained as an online presence, such as it was, faded away. My blogging platform, for example, up and disappeared. I had been posting, over a 20 year period, on topics ranging across history, philosophy, business, management, and most particularly the concept of content (its design, use, and management). I did have a digital backup and I was actively using it to train, and argue with, an AI chatbot, so the disappearance of my blogging platform did not amount to the disappearance of my content. There are some who will be less happy about this than others.

This inaugural post can be taken as a declaration that I am back. What I had worked on in the past will find a safe place to rest and, more importantly, I will push ahead into new things. And I will be following the trajectory that forms an arc from my past endeavours to land somewhere that is yet to be determined. One thing is true, this arc has formed, a bit like a rainbow, into a multi-coloured unity where my many pursuits, professional and academic, come together. This is a good thing, if only for my own sanity. It is a gift.

Human knowledge in the age of the smart machine is in many ways the same as it always has been. In other ways, it is profoundly new. The more things change, the more they stay the same.

So watch this space.

And follow along. Such a journey is best done together. Indeed it is the only way for such a quest to proceed.