Content Operations

Good content fundamentals have been the foundation of effective product content for decades, and those same principles are exactly what make content AI-ready today. In this episode, Bill Swallow and Alan Pringle explain how attending to your hierarchy of content needs is the key to AI success. Alan Pringle: Right now, AI is not going to fix bad content problems. It is going to regurgitate that bad information, giving your end users information that’s flat out wrong. If your content at the basic source level is wrong, your AI by extension is going to be wrong. And that is the unglossy, unvarnished, hard truth that is still, I don’t think, seeping in like it should across the corporate world. Bill Swallow: It really does come back to the fact that, despite the world changing on a day-to-day basis, the fundamentals have not changed. Related links: A hierarchy of content needsTechnical Writing 101, 3rd editionStructured content: a backbone for AI success LinkedIn: Alan PringleBill Swallow Transcript: This is a machine-generated transcript with edits. Introduction with ambient background music Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations. Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it. Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change. Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off. End of introduction Bill Swallow: Hi, I’m Bill Swallow. Alan Pringle: And I’m Alan Pringle. BS: And in this episode, surprise surprise, we’re going to talk about content. AP: Really? Who would have thought? BS: But more specifically, what good content means today. Today, everything is all about AI. There is lots of change in progress with regard to AI tooling and content delivery with AI. But have the needs for content really changed? And I would say that off the bat, if you’re doing content right, you really don’t have to reinvent the wheel to make it AI acceptable. AP: No, in this crazy AI-hyped world we’re in, there’s some very basic foundational things that tend to get overlooked because they’re not sexy, and they’re not special and hot and whatever else. All that kind of marketing garbage that just sets me on complete edge and makes me want to say profane things in podcasts. The bottom line is, there are things that the content world, and especially our little subdomain of it, product content world, has been doing for decades now. And I mean decades. BS: Or should have been doing. AP: Correct. There are basic tenants that have been in place for decades. That if you’re following them, you are starting down the road of success with AI. I think to kind of prove our point, we’re going to step back and look at some of the things that Scriptorium has talked about and written in the past and see how it stacks up. And Bill, you found one. And let’s talk about that blog post that Sarah O’Keefe wrote. What was the date on that again? BS: It was 2014. And that is when we came up with the hierarchy of content needs. And it really wasn’t so much an invention as it was just a regurgitation of what it means to create good content. So we have a pyramid of content needs. At the bottom, we have available. So is content available? Does it exist? Can someone get to it? I think that we’ve mostly solved that problem given the dearth of information we have out on the internet. But as we know, that information is not always useful. So we go up a rung or a layer on that pyramid and see whether or not the content is accurate. And if it’s accurate, if it provides the correct information, that’s fantastic. Then we go...

In this episode, Sarah O’Keefe and Alan Pringle explore how AI transforms content delivery from static documents into dynamic, consumer-driven experiences. However, the need for human-led governance is critical, and Sarah and Alan explore issues of accuracy, accountability, governance, and more. They challenge organizations to define AI success by its ability to deliver accurate, high-impact outcomes for the end user. Sarah O’Keefe: The metrics that are being used to measure the success of AI are all wrong. We should be measuring the success of various AI efforts based on, “Are people getting what they need? Are they having a successful outcome with whatever it is that they’re trying to do?” The metric we actually seem to be using is, “What percentage of your workflow is using AI? How many people can we get rid of because we’re automating everything with AI?” It’s the wrong metric. The question is, how good are the outcomes? Related links: AI and content: Avoiding disasterAI and accountabilityStructured content: a backbone for AI successAsk Me Anything: AI in content ops. LinkedIn: Sarah O’KeefeAlan Pringle Transcript: This is a machine-generated transcript with edits. Introduction with ambient background music Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations. Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it. Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change. Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off. End of introduction Alan Pringle: Hey everybody, I’m Alan Pringle, and today I’m here with Sarah O’Keefe, and we want to do something I’ve kind of dreaded to be honest, to do a check-in on AI in the content space. I’m very ambivalent about this topic. There’s still even two, three years in, there’s still a lot of hype, but there’s also been some good things that have emerged. We need to talk about it fairly realistically. So, Sarah, get ready. Let’s see if I can not curse during this. We’ll try. I’ll try my best not to be like that in this. Legitimately, there are some things that we need to talk about, and also about the challenges because I don’t think the content world is completely ready for a lot of what’s going on right now. Sarah O’Keefe: You know that we have AI that can remove cursing from podcasts, so I feel like we’re good here. AP: Well, also, it’s a challenge to me to behave in a PG-13 more family-friendly kind of way. So I’ll do my best. SO: I have no idea what you’re talking about. AP: Yeah. So let’s start with the good and where things are right now with the positives. What is AI doing well right now? And let’s kind of get beyond the summarization. I think we can say objectively right now, in general, AI does a very good job of summarizing existing content. But I think it’s doing a lot more beyond that, and we should touch on those things instead. SO: The first thing that I would say is that summarization, but specifically the use case of a chatbot or a large learning model, an LLM, so now we’re talking about Claude, Gemini, ChatGPT and all the rest of them, which has the ability to provide an end user with a way of accessing information, an information access point that is different than what we had previously. In the olden days, you had a book, and you had to sort of flip it open and look at a table of contents or maybe an index and navigate to a page. Fine. Then along comes online content, and you can do full text search, or you can then go into an internet search, right? You type into the search bar, you get a bunch of results, you click, and you sort of,...

As AI adoption accelerates, accountability and transparency issues are accumulating quickly. What should organizations be looking for, and what tools keep AI transparent? In this episode, Sarah O’Keefe sits down with Nathan Gilmour, the Chief Technical Officer of Writemore AI, to discuss a new approach to AI and accountability. Sarah O’Keefe: Okay. I’m not going to ask you why this is the only AI tool I’ve heard about that has this type of audit trail, because it seems like a fairly important thing to do. Nathan Gilmour: It is very important because there are information security policies. AI is this brand-new, shiny, incredibly powerful tool. But in the grand scheme of things, these large language models, the OpenAIs, the Claudes, the Geminis, they’re largely black boxes. We want to bring clarity to these black boxes and make them transparent, because organizations do want to implement AI tools to offer efficiencies or optimizations within their organizations. However, information security policies may not allow it. Related links: AI and content: Avoiding disasterAI and accountabilityWritemore AI LinkedIn: Nathan GilmourSarah O’Keefe Transcript: Introduction with ambient background music Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations. Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it. Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change. Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off. End of introduction Sarah O’Keefe: Hey everyone. I’m Sarah O’Keefe. Welcome to another episode. I am here today with Nathan Gilmour, who’s the Chief Technical Officer of Writemore AI. Nathan, welcome. Nathan Gilmour: Thanks, Sarah. Happy to be here. SO: Welcome aboard. So tell us a little bit about what you’re doing over there. You’ve got a new company and a new product that’s, what, a year old? NG: Give or take, yep. SO: Yep. So what are you up to over there? Is it AI-related? NG: It is actually AI-related, but not AI-related in the traditional sense. Right now, we’ve built a product or tool that helps technical authoring teams convert from traditional Word or PDF formats, which would make up the bulk of much of the technical documentation ecosystem and help convert it to structured authoring. Meaning that they can get all of the benefits of reuse, easier publishing, high compatibility with various content management systems. And can do it in minutes where traditional conversions could take hours. So it really helps authoring teams get their content out to the world at large in a much more efficient and regulated fashion. SO: So I pick up a corpus of 10 or 20 or 50,000 pages of stuff, and you’re going to take that, and you’re going to shove it into a magic black box, and out comes, you said, structured content, DITA? NG: Correct. SO: Out comes DITA. Okay. What does this actually … Give us the … That’s the 30,000-foot view. So what’s the parachute level view? NG: Perfect. Underneath the hood, it’s actually a very deterministic pipeline. Deterministic pipeline means that there is a lot more code supporting it. It’s not an AI inferring what it should do. There’s actual code that guides a conversion process first. So going from, let’s say, Word to DITA, there are tools within the DITA Open Toolkit that allow and facilitate that much more mechanically, rather than trusting an AI to do it. We know that AI does struggle with structure, especially as context windows expand. It becomes more and more inaccurate. So if we feed these models with far more mechanically created content, they become much more...

What happens when AI accelerates faster than your content can keep up? In this podcast, host Sarah O’Keefe and guest Michael Iantosca break down the current state of AI in... Read more » The post Futureproof your content ops for the coming knowledge collapse appeared first on Scriptorium.

Your organization’s content debt costs more than you think. In this podcast, host Sarah O’Keefe and guest Dipo Ajose-Coker unpack the five stages of content debt from denial to action.... Read more » The post The five stages of content debt appeared first on Scriptorium.

How can global brands use AI in localization without losing accuracy, cultural nuance, and brand integrity? In this podcast, host Bill Swallow and guest Steve Maule explore the opportunities, risks,... Read more » The post Balancing automation, accuracy, and authenticity: AI in localization appeared first on Scriptorium.

AI, self-paced courses, and shifting demand for instructor-led classes—what’s next for the future of training content? In this podcast, Sarah O’Keefe and Kevin Siegel unpack the challenges, opportunities, and what... Read more » The post From classrooms to clicks: the future of training content appeared first on Scriptorium.

What if you could escape copy-and-paste and build dynamic learning experiences at scale? In this podcast, host Sarah O’Keefe and guest Mike Buoy explore the benefits of structured learning content.... Read more » The post From PowerPoint to possibilities: Scaling with structured learning content appeared first on Scriptorium.

Every time someone views your product content, it’s a purposeful engagement with direct business value. Are you making the most of that interaction? In this episode of the Content Operations... Read more » The post Every click counts: Uncovering the business value of your product content appeared first on Scriptorium.

In this episode of the Content Operations podcast, Sarah O’Keefe and Bill Swallow unpack the promise, pitfalls, and disruptive impact of AI on multilingual content. From pivot languages to content... Read more » The post AI in localization: What could possibly go wrong? (podcast) appeared first on Scriptorium.

Is AI really ready to generate your training materials? In this episode, Sarah O’Keefe and Alan Pringle tackle the trends around AI in learning content. They explore where generative AI... Read more » The post Help or hype? AI in learning content appeared first on Scriptorium.

Tempted to jump straight to a new tool to solve your content problems? In this episode, Alan Pringle and Bill Swallow share real-world stories that show how premature solutioning without... Read more » The post Tool or trap? Find the problem, then the platform appeared first on Scriptorium.

Struggling to get the right content to the right people, exactly when and where they need it? In this podcast, Scriptorium CEO Sarah O’Keefe and Fluid Topics CEO Fabrice Lacroix... Read more » The post Deliver content dynamically with a content delivery platform appeared first on Scriptorium.

Are you considering a structured approach to authoring and distributing your learning content? We built LearningDITA.com as an example of what DITA and structured learning content can do! In this... Read more » The post LearningDITA: DITA-based structured learning content in action appeared first on Scriptorium.

In this episode, Alan Pringle, Bill Swallow, and Christine Cuellar explore how structured learning content supports the learning experience. They also discuss the similarities and differences between structured content for... Read more » The post The benefits of structured content for learning & development content appeared first on Scriptorium.

In this episode, Alan Pringle, Gretyl Kinsey, and Allison Beatty discuss LearningDITA, a hub for training on the Darwin Information Typing Architecture (DITA). They dive into the story behind LearningDITA,... Read more » The post LearningDITA: What’s new and how it enhances your learning experience appeared first on Scriptorium.

In our last episode, you learned how a taxonomy helps you simplify search, create consistency, and deliver personalized learning experiences at scale. In part two of this two-part series, Gretyl... Read more » The post Building your futureproof taxonomy for learning content (podcast, part 2) appeared first on Scriptorium.

Can your learners find critical content when they need it? How do you deliver personalized learning experiences at scale? A learning content taxonomy might be your solution! In part one... Read more » The post Taxonomy: Simplify search, create consistency, and more (podcast, part 1) appeared first on Scriptorium.

Ready to deliver consistent and personalized learning content at scale for your learners? In this episode of the Content Operations podcast, Alan Pringle and Bill Swallow share how structured content... Read more » The post Transform L&D experiences at scale with structured learning content appeared first on Scriptorium.

In episode 179 of the Content Strategy Experts podcast, Sarah O’Keefe and Alan Pringle share the inside scoop on how to write an effective request for a proposal (RFP) for... Read more » The post Creating content ops RFPs: Strategies for success appeared first on Scriptorium.