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, a tech veteran, discusses the rapid AI advancements, open-source impact, and knowledge graph technology. He compares building AI products to a risky endeavor and stresses staying nimble. Topics include LLMs, tokenization, and the democratizing AI ecosystem. Kurt's advice: be aware of AI developments and avoid getting stuck with one technology.

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,

AI is impacting technical documentation through support agents, generative content, and changing delivery methods. Sarah O'Keefe discusses the importance of governance, scalable documentation, generative AI concerns, chat-based interfaces, and trust in online interactions. She also explores AI integration, metadata usage, ethical challenges, and the need for strategic thinking in content practices.

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, an AI expert since the 1980s, shares insights on using graphs in AI, structured content benefits, and the tech stack of AI tools. He discusses sequence-to-sequence and diffusion technologies, preferring SSM over LLMs. Nathan also talks about the impact of LLM chat agents on content, the importance of using personal data sets, and detailed task analysis in building AI models. He contrasts AI developments at big companies with the open-source AI ecosystem.

Dan McCreary, experienced in selling AI solutions to executives, discusses the importance of storytelling in making enterprises intelligent and nimble. He uses a jellyfish and flatworm metaphor to visualize competitive environments. Topics include knowledge graphs, micro-personalization, labeled property graphs, and the significance of freeing data from spreadsheets for AI productivity benefits.

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...