Lance Cummings Education often lags behind tech trends. Not in the case of AI. And not when Lance Cummings is involved. Lance conducts academic research on AI content operations and has worked both with technical communicators and with content entrepreneurs in the creator economy. Along the way he has discovered concepts and practices around structured content that apply across prompt engineering, tech writing, and influencer content creation. We talked about: his work as a rhetoric and writing professor and research on the creator economy his view of content operations and workflow, especially new practices around AI how the introduction of the idea of "AI content operations" clarifies the writing process for content creators of all kinds, including the technical writers that he teaches how a structured-content approach can help writers of all kinds cultivate a garden of ideas how the real value around your content lies in interactions with your community, not necessarily the content itself his approach to collaborative prompting, knowledge management, and development of AI tools how standards and practices like DITA and object-oriented knowledge management how structured content can actually make us more creative why creative writers generally excel in the tech writing field Lance's bio Lance Cummings is an associate professor of English in the Professional Writing program at the University of North Carolina Wilmington. Dr. Cummings explores content and information development in technologically and culturally diverse contexts both in his research and teaching. His most recent work looks at how to leverage structured content with rhetorical strategies to improve the performance of generative AI technologies and shares his explorations in his newsletter, Cyborgs Writing. Connect with Lance online Cyborgs Writing LinkedIn Video Here’s the video version of our conversation: https://youtu.be/lneGOV6tNbY Podcast intro transcript This is the Content and AI podcast, episode number 10. We are quickly discovering that AI can help content professionals across the span of their work. Lance Cummings is a consultant and college professor who is exploring intersections that most content folks haven't had time to ponder. For example, he has found that his approach to AI content operations can clarify and improve the writing process for both technical documentation authors at big enterprises as well as fiercely independent members of the creator economy. Interview transcript Larry: Hi everyone. Welcome to episode number 10 of the Content + AI podcast. I'm really delighted today to welcome to the show Lance Cummings. Lance is a professor of English in the professional writing program at the University of North Carolina in Wilmington. He does a lot of interesting research, and we'll talk about that as we get going. But one of the interesting things in the intersections of his research and academic interests is this notion of applying structured content, looking at structured content, rhetorical strategies, and AI technologies and workflows around that. I'm really excited to talk about all this stuff with you, Lance, but welcome to the show. Tell the folks a little bit more about what you're up to. Lance: Yeah, so I'm a professor in rhetoric and writings, which generally just means that we study how people write, make meaning, get things done with text. And more recently I've been researching the creator economy, actually before AI. That's how I stumbled across AI in 2021. And if you don't know what the creator economy, it's what this podcast is. It's people creating content directly to audiences using the various digital platforms ...

Dave Birss (AI-generated) Dave Birss has had a busy 2023. Since developing his first AI course for LinkedIn Learning early in the year, he has produced five more courses and has become the learning platform's most popular AI instructor. We talked about: his experimental approach to teaching AI how he helps companies understand the true benefits of AI the importance of using AI to augment people's skills rather than just to try and save money the elements of his AI manifesto use AI responsibly be ethical support your employees assign leaders keep learning always add a human layer to AI output the importance of critically consuming advice from anyone who proclaims to be an AI expert the importance of companies learning for themselves because there are few reliable consultants available now how unlocking the true benefits of AI can change companies' perspectives and help them see new opportunities the crucial task of understanding people and addressing their needs as AI is adopted his observation that it "cannot be AI or human, which is the way that a lot of companies are seeing it, it's got to be AI plus human" how the adoption of AI supports his point of view that generalists have an equally important role in the modern workforce as specialists Dave's bio Dave Birss combines the analytical mind of an AI geek with the butterfly mind of a former advertising creative director. This helps him make the ever-changing world of AI approachable, relevant, and occasionally entertaining. At the start of 2023, he launched his first LinkedIn Learning course on Generative AI. Since then, he’s released another five courses, all of which have gained fantastic ratings and reviews. In July LinkedIn announced that he’s now the most popoular AI instructor on the platform. But Dave isn’t just about online courses. He’s also a globe-trotting educator and public speaker, helping companies and individuals get more value out of Generative AI. He’s also a best-selling author with several books on creativity and innovation. And a former broadcaster and film-maker. As a sought-after keynote speaker, Dave speaks about AI, innovation, and creative thinking with a blend of science and dad-jokes. He’s a Scotsman who lives in London with his Haitian-American wife and two delightfully confused children. Connect with Dave online LinkedIn DaveBirss.com Video Here’s the video version of our conversation: https://youtu.be/2QL01qN6uzY Podcast intro transcript This is the Content and AI podcast, episode number 9. Over the past year, we've all been getting up to speed on AI. Over that time span, Dave Birss has become the most popular AI instructor on LinkedIn Learning. Dave would be the first to tell you that he's not an expert on artificial intelligence. But he's a very experienced technology professional who has witnessed several major earlier tech revolutions, and he's an experienced teacher and consultant, so he brings a very pragmatic approach to incorporating AI in your work life. Interview transcript Larry: Hi, everyone. Welcome to episode number nine of the Content and AI podcast. I am really delighted today to welcome to the show Dave Birss. Dave is an educator, author, and consultant currently focusing on AI and AI education. He's the most popular AI instructor at LinkedIn Learning. Welcome, Dave. It's great to have you here. Tell the folks a little bit more about what's going on these days. Dave: Thanks, Larry. Yeah, I've been creating courses on AI this year, really. And I can't really call myself an AI expert.

Lisa Jennings Young Over the past five years, Lisa Jennings Young has pioneered the adoption of AI tools in content-design practices at Twitter and Microsoft. Lisa has watched in real time the realization of the benefits of natural-language AI tools to help govern and create content, as well as to assist with content-design research and operations. We talked about: her pioneering work with AI when she as at Twitter her thoughts on the important role that natural language processing (NLP) plays in content-design governance now natural language generation (NLG) can help content designers how she sees NLP and NLG helping her scale content-designer operations the principles that guide the implementation of AI at Microsoft: is it good for Microsoft? is it good for individual teams? is it good for our customers? how her work aligns with Microsoft's strategic objectives some of the work that content designers do that she doesn't see AI replacing anytime soon: stakeholder alignment, customer research, journey mapping, content ecosystem analysis, etc. how implementing AI tools has resulted in new communications opportunities with cross-functional partners the importance of prompt engineering skills her hot take on AI and content design: "It's not about replacing writers, it's about affecting them. So AI won't replace writers, but writers working with AI will replace writers working without AI." Lisa's bio Lisa Jennings Young is the Head of Content Design for Microsoft Teams. She has over 20 years of experience creating content strategies that scale, with a passion for bringing life and voice to digital products. With extensive experience in process design, tooling, writing AI, and content moderation, she helps teams do more than write digital interfaces. She helps them create human experiences. Before heading up Content Design for Microsoft Teams, Lisa was Head of Content Design at Twitter. While there, she built a team that set a global example for how social media can be more inclusive, accountable, and equitable for everyone. When not spending time with her husband and four kids, Lisa loves to read nonfiction, tend her Oakland garden, and cook for crowds. Oaktown Spice is her home away from home. Her spice game is on point. Connect with Lisa online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/gVFsTiSuxWs Podcast intro transcript This is the Content and AI podcast, episode number 8. Few people have had as good a front-row seat as Lisa Jennings Young to see the emergence of AI tools for content-design practice. First at Twitter, where she pioneered some of the earliest use of natural language processing tools in a content-design operation, and now at Microsoft, where she leads a team of content designers and technical writers, Lisa has led the way in showing how AI technology can both help content professionals and democratize writing skills for non-experts. Interview transcript Larry: Hey everyone, welcome to episode number eight of the Content and AI podcast. I'm really happy today to welcome to the show, Lisa Jennings Young. Lisa is a principal content design director at Microsoft Teams, and welcome to the show, Lisa. Tell the folks a little bit more about what you're doing these days. Lisa: Thank you so much, Larry. It's great to be here. So yeah, so I am at Microsoft Teams right now, leading content design for that product. I've been there six months. I resigned from Twitter last November, so almost a year now. And yeah, I've been settling into Microsoft. It's a huge company, getting to know the lay of the land,

Claudia Francesca Mueller At Trusted Shops, Claudia Francesca Mueller and her colleagues have built an AI-powered chatbot called Piuma that lets non-writers access content guidance through a natural-language interface. It took just a few weeks to launch the initial version of Piuma, building the chat interface with Voiceflow and using the LangChain development framework to access both their content design guidance and OpenAI's API. Even though the chatbot's functionality matched their users' expectations almost perfectly, they still find that they have to constantly collaborate with their partners to fully understand their needs and communicate the benefits of the product. We talked about: her work as a content design and localization lead at Trusted Shops Piuma, the AI chatbot they have built at Trusted Shops how Piuma arose from research and discovery work they did around how to best share their content-design guidance how they developed Piuma using Voiceflow with guidance from a conversational design expert the learning curve around incorporating LLMs into a chatbot like Piuma how they decided which parts of their voice and tone guidance to include in the chatbot how Voiceflow works with the OpenAI and Langchain the need to sometimes adjust the source documentation that the LLM is consulting to get the answers you want in the chatbot how her multilingual background helps her understand computer languages the challenges of getting designers to adopt a new tool like Piuma her ongoing communication with designers to understand their needs and how to address them how she balances evangelism and outreach with collaboration around improving Piuma the tendency of humans to stay with familiar patterns and routines Claudia's bio Claudia Francesca Mueller is a multilingual content designer living in Amsterdam. She speaks Swiss-German, Italian, German, English and Dutch daily, and feels at home when languages are mixed up in one sentence. That’s how she has also learned to bridge culture gaps with style and the right tone. Her love for languages, words, culture, shapes and colours brought her to content design. A discipline that became her passion and that she loves to live as an expert, leader and coach. Her background and career in multiple content roles have strongly shaped her thinking. She believes content is a holistic discipline where words are only one of many tools to convey a message. Currently, Claudia works at Trusted Shops as Principal Content Design and Localization. Connect with Claudia online LinkedIn Video Here’s the video version of our conversation: https://www.youtube.com/watch?v=43688rk97rc Podcast intro transcript This is the Content and AI podcast, episode number 7. On any one digital product team, there are never enough content designers or UX writers. So when interaction designers or engineers have to write interface copy, they typically have to consult content-design documentation. AI creates new ways to share this kind of content guidance. At Trusted Shops, Claudia Francesca Mueller and her colleagues have built an AI-powered chatbot that lets non-writers access content guidance through a natural-language interface. Interview transcript Larry: Hi, everyone. Welcome to episode number seven of the Content and AI podcast. I am really delighted today to welcome to the show Claudia Francesca Mueller. Claudia is a multilingual content designer and a localization lead at Trusted Shops. Welcome, Claudia. Tell the folks a little bit more about what you're doing these days. Claudia: Hi, everybody. Thanks a lot for having me, Larry. As you said,

Kurt Cagle(AI-generated image) Kurt Cagle has been reporting on and participating in the tech world for several decades. He's never seen anything like the pace of change around AI. His advice for staying ready to work with AI: stay nimble, pay attention to what's going on, don't get tied to any one technology, and always bear in mind that your work will have an impact. We talked about: his interest in the intersection of AI and knowledge graphs the rapid and vast advancements in AI tech, especially recent developments at OpenAI [referring to the product announcements in early November, not the Sam Altman excitement later in the month] how building AI products in the current environment is "like building a luxury hotel on top of quicksand in an earthquake zone" the impact of open-source and component-based thinking in the AI ecosystem and how those dynamics are democratizing AI how a Disney character can help you understand LLMs how tokenization work the difference between how a query to a typical database works and how vectorization identifies things that are similar how knowledge graph technology can help solve some of the problems in the LLM space his advice for staying ready to work with AI: be nimble, pay attention to what's going on, and don't get tied to any one technology Kurt's bio Kurt Cagle is managing editor of The Ontologist, Generative AI, and the Cagle Report, and is a thirty-year veteran in the knowledge management space with twenty-five books and several Fortune 500 clients and government agencies. He lives in Bellevue, Washington with his family and cats, where he likes watching the rain fall. Connect with Kurt online LinkedIn kurt dot cagle at gmail dot com Video Here’s the video version of our conversation: https://youtu.be/enaZSqj5vkM Podcast intro transcript This is the Content and AI podcast, episode number 6. Developing software has always been challenging. AI takes things to a whole new level. Kurt Cagle says the current pace of development in the generative AI world is "like building a luxury hotel on top of quicksand in an earthquake zone." Kurt has reported on and participated in many eras of technology advancement, but he's never seen anything like this. His advice for thriving in uncertain times like these: stay nimble, pay attention to what's going on, and don't get tied to any one technology. Interview transcript Larry: Hi, everyone. Welcome to episode number six of the Content and AI podcast. I'm really happy today to welcome to the show Kurt Cagle. Kurt, he's the editor for The Ontologist. He's a managing editor for the Cagle Report. He's been a technologist for more than 35 years. He's written 25 books. He's been blogging for 20 years. He knows one or two things about AI, so welcome, Kurt. Tell the folks a little bit more about what you're up to these days. Kurt: Thank you for having me on the show. I really appreciate it, Larry. I am busy in AI land and in the intersection of AI and knowledge graphs, and have been trying to find out where the two meet and otherwise contributed to one another. I do run a small consulting company. I have a Calendly account if someone wants to contact me directly for setting up an open office hour, and always looking for opportunities. Thank you very much. Larry: Yeah, cool. Well, and speaking of opportunities, we met through the knowledge graph community which I've been involved with for a few years now, and as the LLM explosion of the last year has come along, I've been like, "Where's the connection between these?" And all of a sudden, the last, I don't know, few weeks it almost seems... We're recording this on November 7th,

Tane Piper "Leading-edge technology" may not be the first thing that comes to mind when you walk into an IKEA store, but maybe it should be. IKEA is using AI technologies across its vast collection of businesses to deliver better content experiences to its customers. Tane Piper leads an engineering team at Inter IKEA - the business unit that owns the IKEA brand - that is building their next generation of content and artificial intelligence tooling. We talked about: his role at Inter IKEA the scope of AI activities at IKEA how their knowledge graph provides a "ground reality" for the info they share enterprise uses of AI at IKEA how narrowing the scope of models to your own enterprise improves quality and reduces costs the importance of testing implementations of AI technology how their knowledge graph helps connect content across the enterprise - and offers new content metrics and analytics benefits how their systems facilitate content discovery and reuse how he uses ChatGPT to accelerate his business research his thoughts on AI technologies can add a qualitative dimension to content metrics how AI and machine learning practices may reduce the amount of data that enterprises need to collect and store how they are developing prompt engineering skills at IKEA the importance of taking a pragmatic approach to AI adoption Tane's bio Tane Piper is a self-taught software developer with over 22 years of experience. He has worked across a diverse set of environments, from startups and creative agencies to his current role as a Software Engineering Leader at IKEA. Here, Tane focuses on projects that blend content strategy, knowledge graphs, and artificial intelligence. His approach to leadership is centered on teamwork, innovation, and nurturing growth within his team. He enjoys experimenting with a wide range of technologies. He is involved in the open-source community, releasing various libraries over the year, and writing technical articles sharing his findings. When not engaged in software development, Tane can often be found in his garden, a hobby that provides him with a peaceful counterbalance to his professional life. Alongside his wife, he is also dedicated to the ethical breeding of Polish Hunting Spaniels, reflecting their shared passion for animal welfare. Connect with Tane online LInkedIn Video Here’s the video version of our conversation: https://youtu.be/9qX8fUpWFgQ Podcast intro transcript This is the Content and AI podcast, episode number 5. When you think of the iconic furniture retailer IKEA, leading-edge technology may not be the first thing that pops into your mind. But it should. Like most enterprises now, IKEA is exploring the many ways that LLMs, machine learning, knowledge graphs, and other AI technologies can help them sell more furniture and understand their business better. Tane Piper leads an engineering team at IKEA that is building their next generation of content and artificial intelligence tooling. Interview transcript Larry: Hey, everyone. Welcome to episode number 5 of the Content + AI podcast. I'm really delighted today to welcome to the show Tane Piper. Tane is a software engineering leader at Inter IKEA. And that's the first thing I want to ask you about Tane, is IKEA is this big sprawling complex organization. Tell me about Inter IKEA and how that fits in with the overall IKEA brand. Tane: Yeah. Thanks, Larry. So Inter IKEA, as many people know, you go to IKEA, you go to a shop, but what a lot of people don't know is it is actually a franchise system. So, Inter IKEA is the owner of the IKEA concept, so it owns the furniture side,

Sarah O'Keefe The arrival of AI affects every area and aspect of content practice. In the technical documentation field, Sarah O'Keefe sees three immediate impacts on the work she does for her clients: how AI agents can support technical documentation workflows, the ability to create content with generative AI, and the ways that AI is changing the delivery of technical content And wherever she looks in the content and AI landscape, she sees the need for governance guardrails and strategic thinking. We talked about: her work at Scriptorium, which focuses on scalable, efficient technical documentation her take on the current impact of AI on technical content the unique concerns about generative AI that arise in the technical communication world how chat-based user interfaces will change the delivery of technical content how users will always hack systems to use them as they wish the looming role of trust and reputation as important factors in online interactions how techniques like RAG (Retrieval Augmented Generation) can help LLM-based applications deliver better results the importance of thinking about the content life cycle as you assimilate and integrate AI into your practices and workflows a very simple AI-risk-analysis heuristic open questions - many of them complex and non-obvious - around copyright issues in the AI world Sarah's bio CEO Sarah O’Keefe founded Scriptorium Publishing to work at the intersection of content, technology, and publishing. Today, she leads an organization known for expertise in solving business-critical content problems with a special focus on product and technical content. Sarah identifies and assesses new trends and their effects on the industry. Her analysis is widely followed on Scriptorium’s blog and in other publications. As an experienced public speaker, she is in demand at conferences worldwide. In 2016, MindTouch named her as an “unparalleled” content strategy influencer. Sarah holds a BA from Duke University and is bilingual in English and German. Connect with Sarah online LinkedIn info at scriptorium dot com Video Here’s the video version of our conversation: https://www.youtube.com/watch?v=FOfdOSD8C1A Podcast intro transcript This is the Content and AI podcast, episode number 4. The arrival of generative AI, large language models, and other AI technologies obviously affects us all. In the world of technical documentation, Sarah O'Keefe sees three immediate impacts on the work she does for her clients: how AI agents can support technical documentation workflows, the ability to create content with generative AI, and the ways that AI is changing the delivery of technical content - and across them all, the need for guardrails and strategic thinking. Interview transcript Larry: Hi, everyone. Welcome to episode number four of the Content + AI podcast. I'm really happy today to welcome to the show Sarah O'Keefe. Sarah is the CEO and founder at Scriptorium, which is a company that does technical communication and documentation stuff. Sarah, tell the folks a little bit more about your work there at Scriptorium. Sarah: We're interested in the question of how do you apply systems and technology to what we call enabling content, which is technical product learning, knowledge base, all of the things that are content that enables you having purchased a product or service to actually successfully use that product or service. And we do a ton of work around content management systems, translation management systems, and basically helping companies scale their content operations into something that works....

Noz Urbina Modern content projects begin with research to create lifelike customer personas and build detailed customer journey maps. Whether you're on a tight budget or have a team of UX researchers at your disposal, AI can help accelerate and improve the development of these personas and journey maps. Noz Urbina has developed the RAUX (Rapid AI-powered UX) method to help omnichannel content strategists develop realistic personas and craft effective customer journey maps. We talked about: his work at his consultancy, Urbina Consulting, and his learning hub, OmnichannelX the RAUX AI method he has developed to accelerate user research, customer journey mapping, content design, and content development and drafting his simple equation for doling out information in complex content environments how AI can help you aggregate and understand your sources of customer information to help build personas how he looks at customer journeys and journey mapping how content fits into his customer journey maps, and how AI facilitates the tedious work that precedes and informs how to address key customer needs the AI-driven persona-development prompt methodology at the core of the RAUX methodology how to prompt AI agents in ways that mitigate the biases that often come with public data sources how you can query an AI persona that you have developed with the RAUX prompt methodology to help you fill in the details of a customer journey map how LLM's propensity to hallucination is actually a benefit when you're trying to conjure human feelings, questions, and queries how AI lets us all become programmers without becoming coders how AI can help with content creation, especially tasks like brainstorming and drafting the importance of thinking about how to use AI at every stage of the content lifecycle Noz's bio Noz Urbina is one of the few industry professionals who has been working in what we now call "multichannel" and "omnichannel" content design and strategy for over two decades. In that time, he has become a globally recognised leader in the field of content and customer experience. He’s well known as a pioneer in customer journey mapping and adaptive content modelling for delivering personalised, contextually-relevant content experiences in any environment. Noz is co-founder and Programme Director of the OmnichannelX Conference and Podcast. He is also co-author of the book “Content Strategy: Connecting the dots between business, brand, and benefits” and lecturer in the Master's Programme in Content Strategy at the University of Applied Sciences of Graz, Austria. Noz's company, Urbina Consulting, works with the world’s largest organisations and most complex content challenges, but his mission is to help all brands be able to have relationships with people, the way that people have with each other. Past clients have included Johnson & Johnson, Eli Lilly, Roche, and Sanofi Pharmaceuticals; Microsoft; Mastercard; Barclays Bank; Abbott Laboratories; RobbieWilliams.com; and hundreds more. Connect with Noz online Urbina Consulting noz at urbinaconsulting dot com Video Here’s the video version of our conversation: https://youtu.be/svFi95biaSU Podcast intro transcript This is the Content and AI podcast, episode number 3. These days, designing content experiences starts with detailed customer persona development and extensive customer journey mapping. Whether you've got a six-figure budget or you're doing scrappy do-it-yourself customer discovery, AI can help you accelerate and improve your research process. Noz Urbina has developed a detailed methodology that he calls RAUX (Rapid AI-powered UX) to help you develop realistic personas and craf...

Paco Nathan Most of us are learning about AI on the fly and just got started in the past year or two. Paco Nathan has been working with AI since the 1980s and has been doing digital business nearly as long. His background in both the technical and commercial sides of artificial intelligence gives him a unique perspective on the field that can help newcomers like me and you get oriented to this new landscape. We talked about: his extensive history in the AI field, including work with some of the earliest chatbots how graphs can serve as a way to ground and contextualize unstructured content how content that is structured properly can help help users and drive action the tech stack underlying the current generation of AI tools two technologies at the base level of the stack: sequence-to-sequence and diffusion the benefits of SSM, small specialized models, over LLMs his take on the impact of LLM chat agents on content and editorial practice four take-homes from his recent immersion in AI conferences and gatherings: the superiority of small, specialized learning models (SSMs) over LLMs the issue of losing domain knowledge as experts age and retire the importance of using your own data sets the need for detailed task analysis as you begin building any AI model the contrasts and interplay between AI developments at large, well-funded entities like Alphabet, Meta, and Microsoft and the smaller, more diverse ecosystem around open-source AI projects Paco's bio Paco Nathan, Managing Partner at Derwen, Inc., and author of Latent Space, along with other books, plus popular videos and tutorials about machine learning, natural language, and related topics. Known as a "player/coach", with +40 years tech industry experience, ranging from Bell Labs to early-stage start-ups. Werner Herzog is his spirit animal. Board member for Argilla.io; Advisor for KUNGFU.AI. Lead committer on PyTextRank, kglab. Formerly: Director, Community Evangelism for Apache Spark at Databricks. Long, long ago, when the world was much younger, Paco led a media collective / indie bookstore / performance art space / large online community called FringeWare. Beginning in 1992, this was one of the first online bookstores and likely the first commercial use of a chat bot on the Internet. Connect with Paco online Derwen.ai Argilla.io Video Here’s the video version of our conversation: https://youtu.be/bjU_q36cggw Podcast intro transcript This is the Content and AI podcast, episode number 2. You'd think from news stories and social media that AI is mostly about large language models like ChatGPT and big companies like Microsoft and Google. In fact, there's a large, well-established community of open-source AI projects and a variety of technologies in addition to LLM-based chat agents. With more than 40 years of experience in artificial intelligence and in the tech business world, Paco Nathan is uniquely qualified to orient us in the current AI landscape. Interview transcript Larry: Hey everyone, welcome to episode number two of the Content and AI Podcast. I'm really happy today to welcome to the show Paco Nathan. Paco, we could talk literally for 20 hours about this stuff we're going to talk about today. But what Paco and I are going to talk about today just kinda get you grounded in making sense of the AI ecosystem. Paco's been doing this stuff forever. He's studied AI back in the, what, the 80s or something like that. Anyhow, welcome, Paco. Oh, and one last quick thing. Paco is the managing director of Derwen.ai, his consulting company. So welcome, Paco. Tell the folks a little bit more about your work at Derwen.

Dan McCreary Dan McCreary has years of experience selling AI solutions to executives. He uses a metaphorical story to show the importance of making your enterprise as intelligent and nimble as possible. His story of the the evolutionary heritage of jellyfish and flatworms seemed to me like a great way to kick off this new podcast. We talked about: the importance of helping an executive audience visualize the benefits of any technical solution, in particular the role of storytelling that will help your message stick the jellyfish and flatworm metaphor that he uses to help executives visualize their competitive environment how a knowledge graph lets companies build internal maps of their company and environment how a knowledge graph can enable micro-personalization how adding precision to a model improves your ability to predict customer behavior his simple description of embeddings: a way that we find when two things are similar his take on the benefits of labeled property graphs over knowledge graphs the idea of "reference frames" articulated by Jeff Hawkins and how knowledge graphs come closest to modeling them how three main ways of representing data - neural networks, knowledge graphs, and reference frames - are all based on graph network models the importance of freeing data from spreadsheets to enable the full productivity benefits of AI his insight that knowledge representation is the hardest part of AI Dan's bio Dan McCreary is a solution architect focusing on AI and generative AI architectural patterns. In the past, he worked at Bell Labs with the creators of the UNIX operating system, with Steve Jobs at NeXT Computer, and founded his own consulting firm with over 75 employees. His background includes topics such as scale-out enterprise knowledge graphs, high-performance computing, and NoSQL databases. He is the co-author of the book "Making Sense of NoSQL" and is a frequent blogger on AI strategy. He has been closely following the growth of knowledge graphs and generative AI. He is a huge fan of GPT-4. Connect with Dan online: LinkedIn Video Here’s the video version of our conversation: https://youtu.be/SwK73iQ7_j8 Podcast intro transcript This is the Content and AI podcast, episode number 1. As I was getting ready to launch this new show, Dan McCreary shared on LinkedIn a story that he uses to help executives understand why they need a smarter approach to their data and knowledge management. I always appreciate a good origin story - especially when I'm in the process of starting something new - so his comparison of the evolutionary heritage of jellyfish and flatworms resonated with me. I hope you like the story, too, as well as Dan's take on knowledge representation, which he thinks is the hardest part of AI. Interview transcript Larry: Hey everyone. Welcome to episode number one of the Content and AI podcast. I'm delighted to start off the series with Dan McCreary. Dan is an AI consultant based in Minneapolis, Minnesota in the US. Welcome to the show Dan, tell the folks a little bit more about what you're up to these days. Dan: Thank you very much for having me. I have been working on the field of knowledge representation for most of my career. My background is - early on I did chip design for Bell Labs. I worked in the super computing industry, worked for Steve Jobs for a couple of years, and then I've been doing a lot of starting my own companies and consulting. And then I just recently left a Fortune five healthcare company where I ran a generative AI center of excellence there. Larry: Nice. Yeah, so you've been doing this stuff for a little while and that's why I wanted to start off.