Content + AI

Rebecca Evanhoe Rebecca Evanhoe practices, teaches, and writes about conversation design, a key UX practice that is taking on fresh importance in the age of chat-based AI applications. Since the publication of her book Conversations with Things (co-authored with Diana Deibel) three years ago, the tech and media worlds have fundamentally transformed, but the conversation-design principles that she teaches remain as relevant as ever. We talked about: the conversation design and UX writing courses she teaches reflections on the book she co-wrote several years ago, "Conversations with Things" and the changes in the conversation-design world since how the focus on principles in a framewwork set out in their book that helps designers decide on whether or not and how to ascribe personality to a chat agent her identification as a UX designer how she's incorporating LLMs into her course curricula her take on the misappropriation of the term "prompt" in new practices called "prompting" and "prompt engineering" and their divergence from traditional use in the conversation design field the differences in the conversation designer role in the LLM world compared with NLP the linguistic concept of "conversation repair" and how it manifests in "bot land" how to adjust confidence level in conversation design how intent classification in NLU works her preference for humans and human conversation the importance of including people with a humanities background in conversation design the ongoing importance of humans in the content and conversation design process for our ability to think strategically about how to maximize the success of conversational technology Rebecca's bio Rebecca Evanhoe is an author, teacher, and conversation designer. With degrees in chemistry and fiction writing, she's passionate about how interdisciplinary thinking can combine arts, humanities, sciences, and tech. She teaches conversational UX design as a visiting assistant professor at Pratt Institute, and co-authored Conversation with Things: UX Design for Chat and Voice (Rosenfeld Media, 2021). Connect with Rebecca online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/xJkB03uH8ek Podcast intro transcript This is the Content and AI podcast, episode number 19. We're all talking to computers a lot more these days - telling Alexa to set a timer, asking Midjourney to create an image for a party invitation, or prompting ChatGPT to draft an outline for a slide deck. Rebecca Evanhoe is an expert on the interaction design practices that guide these conversations. Three years ago, her book "Conversations with Things" set out a principles-based approach to conversation design that remains super-relevant in the age of large language models. Interview transcript Larry: Hi everyone. Welcome to episode number 19 of the Content and AI podcast. I am really happy today to welcome to the show Rebecca Evanhoe. Rebecca is really well known in the conversation design world. She's a conversation designer. She's the co-author of the really excellent book Conversations with Things that came out a few years ago, and she teaches conversation design and other kinds of design work at Pratt University in New York. So welcome to the show, Rebecca, tell the folks a little bit more about what you're up to these days. Rebecca: Yeah, hi Larry, it's nice to be back. Yeah, these days I am teaching, I think you said conversation design, and specifically this semester I'm teaching a class in UX writing, which I love because it doesn't matter what kind of writing I'm teaching, it's like a chance to think about language and celebrate how cool language is with my students. And yeah, I've been teaching, I am doing some work at a cool place that I won't get into here. But yeah, it's been a really interesting couple of years. Larry: Yeah, because we last talked right before your book came out,

Andy Crestodina Andy Crestodina has been developing high-quality content for his business customers at Orbit Media for more than 20 years. As they have incorporated AI into their workflows at the agency, Andy has discovered that the best use of these new tools is to improve the quality of their content and service offerings rather than simply doing more. We talked about: his work as co-founder and CMO at Orbit Media how he uses AI to do audience research, develop personas, and address their needs through gap analysis his playbook for querying and validating information that AI generates for him: prompt, response, edit how they manage prompts at Orbit Media how their business operations are evolving to incorporate AI practices into their operations how he uses AI in his marketing analytics how the comprehensiveness of coverage that AI brings to his content helps with conversion the essential skills that persuasion copywriters need to develop to work effectively with AI his concern that some LLMs may be getting worse, not better the importance of setting aside a focus on how to be faster and instead focus on how to be better - to focus on quality over quantity of content Andy's bio Andy Crestodina is the co-founder and Chief Marketing Officer of Orbit Media, an award-winning 50-person digital agency in Chicago. Over the past 23 years, Andy has provided digital marketing advice to 1000+ businesses. Andy has written 500+ articles on content strategy, search engine optimization, visitor psychology, analytics and most recently, AI. These articles reach more than three million readers each year. He’s also the author of Content Chemistry: The Illustrated Handbook for Content Marketing. Andy gives up to 100 webinars and presentations per year and is a frequent repeat speaker at many of the top national marketing conferences. Connect with Andy online LinkedIn Orbit Media YouTube Video Here’s the video version of our conversation: https://youtu.be/yNZiusTV5kY Podcast intro transcript This is the Content and AI podcast, episode number 18. Creating content that gets found by Google and then persuades potential customers to act is a core competency for modern marketers. Andy Crestodina and his colleagues at Orbit Media, the agency he co-founded 20 years ago, have built websites for hundreds of businesses and created content for them that helps turn their prospects into customers. Andy uses AI extensively in his work now. His top finding? Focus on how AI can improve the quality of your work, not just your productivity. Interview transcript Larry: Hey everyone. Welcome to episode number 18 of the Content and AI podcast. I am really happy today to welcome to the show Andy Crestodina. Andy is the co-founder and CMO at Orbit Media. It's a Chicago based agency that does website development and a lot of other marketing stuff. So welcome, Andy. Tell the folks a little bit more about what you're doing these days. Andy: Sure, Larry. Well, thanks for having me. 20 however many years ago, 2001, co-founded an agency. An agency totally focused on the website itself. So we build sites and we improve them forever after doing optimization work, both search and conversion optimization. It's a 55-person firm that we grew strictly from organic and content marketing. So I'm someone that you might see if you go to an event like Content Marketing World, Social Media Marketing World, MozCon. I speak at a lot of search events and analytics events, but I'm an old-school content marketer who's built an agency focused on websites. Larry: Nice. Yeah. We must have run into each other somewhere along the line because I ran in that world a lot back around that same time, the early 2000s. But one of the things that's so interesting ... So we've seen this evolution together and seen a lot of the ... There's always been a lot of drudgery associated with our work and a lot of intellectual ...

Markus Edgar Hormess Markus Edgar Hormess offers this advice: "Never prompt alone." Markus was working with AI long before the current wave of excitement. He experimented with early versions of ChatGPT and quickly identified new opportunities to collaborate with both his human colleagues and his new AI coworkers. He's currently building a community - Teaming with AI - to study and share these new practices and to explore the future of teamwork in the age of AI. We talked about: his background in strategic prototyping and how he's applying it in his Teaming with AI initiative his first exploration of AI, in 1986 one his first applications of current AI tech, a use of ChatGPT-2 to accelerate service design prototyping activities his work and experimentation on ways to engage AI tools as collaborators on design teams how to consume research on AI, but also the importance of getting out in the field since research develops more slowly than professional craft his insight that you should "never prompt alone" so that you and your collaborators can eliminate bias and get better answers some of the opportunities that AI creates for real-time research and accelerated implementation of research insights how important it is "to put people in the center of this" the benefits for design practitioners of diving in and experimenting with AI tools, always with collaborators Markus's bio Markus Edgar Hormeß is a well-known consultant, practitioner and educator in the field of service design and design thinking. In his daily work, Markus helps organizations tackle complex business problems and make team cultures more agile and human-centered. The focal point of his work is strategic prototyping, where he constantly pushes the boundaries of what a dedicated team can achieve with limited resources. Markus is a strong believer that we should break down the perceived boundaries between technology, design and business – and that cheap experiments and prototypes are efficient tools to move your company, your strategy, your team, or your project forward. Based on this mindset, he has shaped multi-year programmes to help multinationals shift towards a more hands-on, pragmatic and effective approach to customer experience and innovation. Markus has a passion for good design, human technology, practical experiments, authentic services, and playfulness in all things. He is co-Founder of WorkPlayExperience, a service innovation consultancy which helps organizations worldwide change how their staff, partners, and customers work together – and – how they can strategically discover and create new products and services. His practice builds on his experience of service design and business consulting, and on his background in theoretical physics. In 2010, Markus co-initiated the world’s biggest service innovation event: the award-winning Global Service Jam. This was soon followed by the Global Sustainability Jam and the Global GovJam, and Markus has been a leading figure in establishing the culture of experimentation and prototyping which Jammers worldwide call “DoingNotTalking”. Markus co-wrote “This is Service Design Doing” and “This is Service Design Methods”, top-selling books which have become the standard reference books for many practitioners and academics. He teaches service design, innovation, and sustainability at various universities globally, and is adjunct professor for service design thinking at IE Business School in Madrid. In 2023 he co-initiated the Teaming with AI conference and community. His growing interest centers on how AI influences our approach to teamwork and collaboration, as well as the broader impacts on innovation and the development of strategies that are resilient in the face of future challenges.. Connect with Markus online LinkedIn Teaming with AI website Video Here’s the video version of our conversation: https://youtu.be/HlHhpsr2lW4

Dan Porder A few years ago, Dan Porder was teaching poetry to university students. Now he's at IKEA training large language models to generate useful, usable content for user experiences. He's picked up new skills along the way, like Python programming, but much of his work still relies on well-established content and design crafts like content strategy and inclusive design. We talked about: his role as a senior content designer at IKEA, where he focuses on AI some of his early experiments in composing and evaluating poetry his longstanding interest in AI and the development of his tech skills how content designers can leverage their skills to work in AI his perception that there is currently more opportunity than threat to content professionals in the AI world the make-up of the cross-functional teams he works with: data scientists, engineers, developers, content people, designers, subject matter experts how to brief and guide generative AI to get the outputs your users need how writing abilities prepare content designers to do prompt engineering the stack of data and technology that underlies AI and the orchestration mechanisms that connect them some of the tools he uses in his AI design practice the role of data in content design for generative AI the importance of staying aware of bias in training data and always wearing your inclusive design hat the role of explainability in AI ethics the importance of knowing how to ask data scientists and engineers questions that reveal as much as possible the inner workings of the "black box" in which AI content is generated his take on democratization opportunities that arise with the arrival of AI tech Dan's bio Dan Porder is a Senior Content Designer and Content Engineer at IKEA. His recent work focuses on the intersection of AI, structured knowledge, and experience design. Outside of work, he runs an international writing community. Connect with Dan online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/VFXLG4h6ylE Podcast intro transcript This is the Content and AI podcast, episode number 16. AI is quickly changing the way content designers work. New content duties are emerging that require fresh skills, but at the same time traditional skills like content strategy are becoming more important. In his work as a content designer at IKEA, Dan Porder has developed new skills, like Python programming, and has applied the writing skills he perfected as a poetry teacher as well as the inclusive design practices he developed earlier in his content design career. Interview transcript Larry: Hey everyone. Welcome to episode number 16 of the Content and AI podcast. I'm really happy today to welcome to the show Dan Porder. Dan is a senior content designer at IKEA, where he's currently focusing on AI stuff, and his title is content designer, but he is really more of a content architect. So welcome to the show, Dan. Tell me a little bit more about your AI and content adventures. Dan: Hey Larry. Thanks for having me on. Yeah, maybe I could just start by giving a little bit of background. I think at heart, despite what I'm doing now, I think of myself as a writer, and that's been my life's focus since I was young. Writing poetry, writing fiction. I did my bachelor's in English literature and later did a masters, masters of fine arts, actually, in poetry. Some of it was more on a conceptual side, thinking of language as data. So there was some unusual experiments in the tech world even then for me. Using Google data to create poems. So imagining Google queries as a representation of the collective zeitgeist, and how can we leverage that data to create meaning in poetry? Or using NLP to find meaningful relationships in texts where you didn't know they were there. But all of that then led me into copywriting, so like brand copywriting, product copywriting, ads,

Rebecca Nguyen In her work as a content designer at Indeed.com, Rebecca Nguyen is finding new opportunities to assume a leadership role on teams working with generative AI. Rebecca feels fortunate to work with teams that recognize the value of writing and design skills. She's also finding that generative AI is the perfect place for content design to take the lead. We talked about: her work as a senior UX content designer at Indeed and her recent shift to focus on product teams using generative AI how well-suited content designers are to AI products the unique challenges of working with non-deterministic large language models their process for designing prompts and how they evaluate them her learning curve around the loss of some language control that you get in conventional content design the main differences between prompt engineering (the how) and content design (the what) her ability as a content designer to lead more in the AI space than in prior design roles how they balance the use of outsourced LLM solutions like OpenAI versus developing their own models the lack of genuine intelligence in LLMs how her fear and concern about AI is eased the more she works in the LLM world how the evaluation component of designing content for AI creates more work for content folks one of the main benefits of LLMs - their ability to take on tedious rote content work the child-like nature of LLMs the surprising liberating effects of simply not worrying about whether or not you have a seat at the proverbial table Rebecca's bio Rebecca Nguyen (she/her/hers) is a Senior UX Content Designer at Indeed. She’s been part of marketing, UX, and product design teams at Bankrate, Northwestern Mutual, and LPL Financial, where she established the content strategy practice. A Confab speaker and workshop instructor, Rebecca is also an award-winning memoirist. Connect with Rebecca online LinkedIn RebeccaAnneNguyen.com Video Here’s the video version of our conversation: https://youtu.be/8WnxlXXKxeY Podcast intro transcript This is the Content and AI podcast, episode number 15. Just as content design was emerging as its own craft and profession, along came generative AI. At first it looked like ChatGPT and large language models might displace content designers (unfortunately, it appears from recent layoffs that some executives may still think this is the case), but at Indeed.com, Rebecca Nguyen has found that working with LLMs has given her more work, not less, and that her content design efforts are now more interesting, rewarding, and impactful. Interview transcript Larry: Hi everyone. Welcome to episode number 15 of the Content + AI podcast. I'm really happy today to welcome to the show Rebecca Nguygen. Rebecca is a senior UX content designer at Indeed. Welcome, Rebecca. Tell the folks a little bit more about what you do at Indeed. Rebecca: Hey, thank you so much, Larry. Great to be here. Yeah, I'm a senior UX content designer at Indeed. I've been there for a couple of years now, going on two years, and I work on product teams to make sure their content is useful and useful and accessible and inclusive and all those goodies that we're used to. And in the past six months or so, my role has really shifted and I've been almost exclusively focused on working with product teams who are using generative AI in their products. Larry: And that's why I wanted to have you on the show is we talked about this a while back. And that's one way to think... One way I think about that is all of a sudden we have new collaborators in two senses. One, we have these new, we're talking to machines in our work because they're generating some of the language we work with, but there's also a lot of other new collaborators. Tell me a little bit about how the people around you have changed over the last six months. Rebecca: Yeah, that's such a great point. So we're probably,

May Habib May Habib is the CEO at Writer.com, a generative-AI platform that has been helping enterprises use AI since 2020. Her company builds its own award-winning large language models and is pioneering approaches like "headless AI" to help employees across an enterprise use AI to be more creative and productive. We talked about: her work as CEO at Writer.com, a "full-stack generative-AI platform," for the past four years her decade-long work in the AI and NLP space, beginning with translation solutions her take on the "over-chat-ification" of AI products, the reliance on chat interfaces as opposed to other ways to access AI capabilities her prediction that 2024 will the "get real" year for AI the use of fine-tuning and/or RAG to connect learning models the inadequacies of vector databases for knowledge retrieval and their exploration of knowledge graphs to fill the gap a new role, the "AI ontologist" another new role, the "AI program director" which includes a mix of left- and right-brain thinking and technical skills some of the use cases for "headless" AI their approach to securing and protecting the various kinds of data used in their LLM how she sees the role of data scientists in AI their tactical approach to building knowledge graphs for specific business use cases their work at Writer on no-code and low-code tooling to help their customers build solutions and tooling on the platform new content job roles that are emerging as AI takes hold in enterprises May's bio May Habib is CEO and co-founder of Writer, the only fully-integrated generative AI platform built for enterprises. Leading companies, including Vanguard, Intuit, L’Oreal, Accenture, Spotify, Uber, and more, choose Writer to help them deploy generative AI across their businesses, allowing them to automate and augment key operational activities and increase employee creativity and productivity. Writer’s family of large language models (LLMs) are state-of-the-art, topping leaderboards for natural language understanding and generation. The company’s security-first approach means that Writer’s large language models and generative AI platform are deployed inside an enterprise’s own computing infrastructure. Launched in 2020, Writer has seen immense success with customer adoption, has grown revenues by 10x in the last two years, and has over 150% net revenue retention. May and the Writer team have successfully raised over $126M in funding from notable investors, including ICONIQ Growth, Balderton Capital, and Insight Partners. May began her entrepreneurial journey as a teenager, and founded her first language startup, Qordoba, a localization software company, 10 years ago. May is an expert in AI-driven language generation, AI-related organizational change, and the evolving ways we use language online. She has been recognized for many different awards, including the recent 2023 Forbes AI 50 and Inc.'s 2023 Female Founder Award. She is a MELI Fellow with the Aspen Institute. She graduated from Harvard University and spends her time between San Francisco, where Writer is based, and London, where her two children live. Connect with May online LinkedIn email may at writer dot com Video Here’s the video version of our conversation: https://youtu.be/lFTfA4X8CkA Podcast intro transcript This is the Content and AI podcast, episode number 14. Over the past year and a half, innovative artificial intelligence startups have taken the tech and content worlds by storm. In her position as the CEO of the generative AI platfom Writer.com, May Habib has been right in the middle of the excitement, and out in front of it. Writer and their clients were deploying LLM-driven generative AI programs inside of large enterprises long before OpenAI's ChatGPT 3 captured the headlines and launched the current wave of AI disruption. Interview transcript Larry: Hey everyone.

Laura Costantino Laura Costantino is watching the emergence of AI in content professions from two interesting and valuable perspectives: as a content designer working on LLMs at Google and as an active participant in the social-media communities where content professionals gathers. In their work at Google, they have returned to their roots as a content strategist to manage the challenges that come with designing content at a massive scale. Through their interactions in the community, they have had the chance to hear the concerns of content designers who are navigating the new world of AI - and to inspire them with advice and success stories. We talked about: their work at Google as a senior content designer training LLMs how their content strategy background is helping in their current work the difference in working with content at a huge scale, as is required in their work with large language models how their work is operationalized in the ever-changing workflows at Google the community of knowledge sharing that has arisen organically among a variety of content crafts at Google their advice on how to cope with the rapid pace of change in the world of AI how they works with data scientists, machine-learning engineers, and other AI collaborators their cautiously optimistic view of future of the content-design profession their advice to content designers for taking a proactive and curious approach to new AI technologies and practices Laura's bio Laura Costantino (they/them) is a senior content designer and strategist working on AI and large language models (LLMs) at Google. For the past ten years, they have worked at the intersection of UX, content, and marketing for some of the world's largest tech companies. Laura developed a passion for storytelling early on and received a MA in Cinema Studies in San Francisco, where they worked as a curator for a range of film festivals and cultural institutions around the Bay Area. Outside of work, Laura is committed to mentoring people transitioning into UX and tech, advocating for content, and sharing advice on LinkedIn. They currently live in NYC, were born in Southern Italy, and speak both English and Italian fluently. Connect with Laura online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/EdgyXGC3xlI Podcast intro transcript This is the Content and AI podcast, episode number 12. The arrival of large language models and chatbots like OpenAI's ChatGPT, Anthropic's Claude, and Google's Bard is creating both existential concerns and new opportunities for content professionals. In their work as a content designer at Google and through their extensive professional networking, Laura Costantino has the chance to witness the full range of work experiences and personal emotions that come with the rapid adoption of new artificial intelligence practices. Interview transcript Larry: Hi everyone. Welcome to episode number 12 of the Content and AI podcast. I'm really delighted today to welcome to the show Laura Costantino. Laura is a Senior Content Designer at Google, doing really interesting work around AI and content stuff. So welcome Laura. Tell the folks a little bit about your role there at Google? Laura: Hi, Larry. Thanks for having me. It's so nice to be here. Yeah, so I've been at Google for about a year and a half, but somewhat recently, maybe three and a half, four months ago, I moved from my previous team to my current team, and I am at the moment working as a senior content designer, training large language models. So that's my new job. Larry: Well, training large language models at one of the biggest tech companies in the world, that's pretty interesting, especially for folks in the content world. There's so much to ask about that. I guess the first thing I'd ask is what's the biggest change? What's the biggest difference in training a language model versus the content design work ...

Chris Cameron At Booking.com, they've been helping travelers with their trip planning for many years. The arrival of generative AI has given them new ways to help travelers with this business-critical task. Over the past year, Chris Cameron has applied his UX writing and content strategy skills in ways both familiar and new to help build a new AI-powered Trip Planner tool that integrates with Booking.com's travel-booking app. We talked about: his work as a principal UX writer at Booking.com on their "writing system," which is sort of like their version of a design system for UX writers his recruitment to a "tiger team" at Booking to develop a new travel-planning AI chatbot for their travel-booking app the key differences between his prior product work and his work on this AI product the new kinds of collaboration that have arisen in his work on a generative AI product, in particular his work with machine-learning engineers the transition from the prototype of the app to its current position as an established product the product-feedback mechanisms that are built into the Booking "Trip Planner" how to jump start your learning if you're new to working on generative-AI tools how they were able to leverage components in their current design system to build the new Trip Planner app the prompt engineering skills he developed by creating an AI "story robot" for his three-year-old son his optimism about the employment prospects for UX writers how traditional content strategy practices like establishing voice and tone and consistent terminology manifest in AI product design how new AI practices are just as likely to show up as enterprise productivity improvements as in customer-facing products and features Chris's bio Chris Cameron has over 13 years of professional writing experience across journalism, marketing, and UX. As a Principal UX Writer at Booking.com, Chris oversees UX Writing Systems, managing the tools and workflows that enable over 80 UX writers to efficiently create high-quality content localised into over 45 languages and dialects. Born in Boston and raised in Phoenix, Chris now lives in Amsterdam with his wife and son. Connect with Chris online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/bptOvimY4uU Podcast intro transcript This is the Content and AI podcast, episode number 11. As generative-AI tools are introduced into consumer products and enterprise workflows, the core work of content designers and UX writers still feels familiar, but the context for the work and many of its details are evolving. Over the past year, at Booking.com, where he has been working on an AI-powered travel-planning app, Chris Cameron has seen first-hand how the traditional concerns of content strategy and UX writing manifest in the world of generative AI. Interview transcript Larry: Hi, everyone. Welcome to Episode #11 of the Content + AI Podcast. I'm really happy today to welcome to the show Chris Cameron. Chris is a principal UX writer at Booking.com, the big travel booking agency based in Amsterdam. Welcome to the show, Chris. Tell the folks a little bit more about what you do there at Booking. Chris: Well, thanks, Larry, for having me. Yeah, I'll give a bit of my background as well. Like yourself, I started in journalism and then got into copywriting. And after moving to Amsterdam from the US at a very young age, 25, I guess, I eventually joined Booking in 2016, a little over seven years ago. And back then, the role was actually called copywriting. There was about 25 of us. And over the years we sort of discovered that we were actually UX writers, and we've become now this community of over 80 UX writers. And now, I am a principal UX writer, and the area I look after we call writing systems. And what that is is sort of like the writing version of design systems, but it's not so much a system,

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 out there, and oftentimes either making some money or a lot of money or making a living even off of doing this. I would say different from influencers, I would say creators are creating useful content for their audiences that they can use a...

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. I guess I'm an enthusiast and I am an experimenter. I guess I do research to find out what works best, and then I share that knowledge with people. Dave: If you told me a year ago that I was going to be doing AI as my main thing, I wouldn't have believed you because OpenAI only released ChatGPT on,

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, really connecting with my amazing team there. So yeah, so it's been a good six months. Larry: Yeah, that's interesting. I think when we talk historically, I think of you and I were just chatting a year and a half ago at Confab, and it was just a normal conversation about work stuff and things.

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, I'm a content design and localization lead at Trusted Shops. Trusted Shops, for the ones that don't know what Trusted Shops is, it is a German e-commerce software as a service company. We certify shops. And if you're a trustworthy shop, you will get a badge and you can start collecting re...

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, just for people's reference because you need an anchor in this rapidly changing thing. This episode probably won't air for a couple more weeks, but we're recording this on November 7th and just either today or yesterday, OpenAI announced a bunch of new product featur...

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, the range we call it, the supply, and also the retail concept, which is where I work. So we come up with the ideas behind IKEA, how the store works, what the concept is when you go to an IKEA store, this kind of Swedishness of it all. And when you as a customer go to the store,

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. Right? Because typically, somebody shows up on our doorstep and says, "Well, we're doing it this way and we've been doing it this way forever, but this way isn't working anymore. We acquired a couple of companies. We got a lot bigger. We're doing more and more localization and we're just drowning in cont...

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 craft effective customer journey maps. Interview transcript Larry: Hi, everyone. Welcome to episode number three of the Content and AI podcast. I'm really delighted today to welcome to the show Noz Urbina.

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.ai and some of your discoveries around AI lately. Paco: Oh, fantastic. Thank you very much, Larry, I really appreciate it. Yeah, Derwen, we're really focused on open-source integration to support machine learning in general. But we focus a lot on natural language and graph...

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. I've been thinking of launching this podcast for a couple months now, and I saw this article that you wrote that said, "Aha, there's my trigger here. Let's go." You wrote this brilliant piece that you've been kind of shopping around because just for everybo...

Update 11 November 2023: I've talked with a lot of people, both interviews for the podcast and informational chats, over the past few weeks and have made some interesting discoveries. So, in addition to helping us all understand AI and how to use it in our work, I'm adding to this podcast's scope coverage of people working in content roles on AI products. Like any other software, AI products need content strategy, content design, UX writing, technical documentation, etc., and we'll hear from those folks soon. Here's the video version of this episode: https://www.youtube.com/watch?v=5qAfH0_0h5I Episode transcript Welcome to the Content and AI podcast. This is episode number 0, an introduction to the show. This episode is just me talking about my intention and plans. Going forward, it will be conversations with experts on both AI and content practice. My intent with this new podcast is twofold: one, to demystify the family of technologies and practices known as artificial intelligence and, two, to democratize the use of AI across the span of content use cases, everything from research and discovery, to content creation and authoring, to content design, content engineering, and content operations. All the stuff we do. I'll talk to folks in the AI field of course - and at first that will largely be a bunch of old white guys, which in itself points to some of data sampling and bias problems that AI practitioners face. But I'll also talk to a diverse range of content practitioners working in product content, support documentation, conversational design, website content, marketing content, content-marketing content - anyone who's adding AI to their digital content workflows - which is pretty much all of us at this point. We've already seen the applications of AI all over the place: auto correct and auto fill in forms digital assistants like Alexa, Cortona, Bixby, and Siri search engines social media feeds personalized content in advertising and on websites and digitial products recommendations from ecommerce merchants robots on assembly lines fraud prevention drug discovery medical diagnosis generative AI, the computer-generated text, and image, and videos that are flooding your in box and social media feeds We'll go under the hood (or as they say in England, the bonnet, I'm recording this in London) - we'll go under the hood, behind the scenes top look at the scope of AI. Not all agree on the precise scope - but we'll look at topics like: NLP, natural language processing, and its applications in areas like conversation design machine learning - statistical modeling of data - embeddings and vectorization and predicting which words come next knowledge representation - bringing real-world facts to the table, which we're already seeing with practices like retrieval augmented generation (RAG) neural networks - machine-based augmented decision making expert systems - rules-based ways to augment human decision making since the 70s computer vision robotics AI ethics and Silicon Valley hype To that last point, we'll pay attention to folks like Timnit Gebru and her collaborator Emily M. Bender. Timnit Gebru is the AI researcher who was fired from Google for pointing out the shortcomings in their approach. She and Bender coauthored the now-famous "stochastic parrots" academic paper. And one of my early guests, one of those old white guys, a delightful and remarkably accomplished human named Paco Nathan - will help us see the current state of AI through lens of an industry veteran with deep deep deep experience in the technical foundations of AI and a ton of experience in the tech startup world. So we'll try to balance the tech hype coming out of Silicon Valley. But we can't and won't ignore that hype - regardless of its merits, they've got the attention of executives and decision makers and the media, so we'll definitely keep an eye on the the big pla...