Content + AI

Colleen Jones Now in its third edition, Colleen Jones's book "The Content Advantage" has become a classic in the content-profession literature. The new edition of the book continues to highlight content intelligence and content effectiveness and adds a new focus on the impact and use of AI in content programs. It also takes a fresh look at the enduring concepts of digital disruption and digital transformation, both of which have been accelerated by the arrival of new AI technology. We talked about: her work at Content Science and how it informs the forthcoming third edition of her book, "The Content Advantage" her take on the concepts of "digital disruption" and digital transformation, both of which have been accelerated by the arrival of AI the title she'd give a movie about pace of organizational adoption of AI: "Slow and Slower" how elevating content concerns to the C-suite has garnered better results for companies lke the pharma giant Pfizer how AI can accelerate the implementation of content visions, strategies, and experiences how AI can improve content intelligence and aid in the assessment of content effectiveness how the structure, framework, and methodology for assessing content effectiveness remains the same in the age of AI her push to get organizations to use digital transformation as the lever to take an end-to-end view of their content how she consciously crafts the language she uses to talk about her consulting services - for example, using the term "end-to-end" instead of "omnichannel" a correlation that she's identified between operational maturity and AI implementation how AI might improve the process of improving content performance her optimism about the prospects for content professionals in the new AI-dominated tech world Colleen's bio A content expert and Star Wars fan, Colleen Jones is the founder of Content Science, an award-winning content firm where she has advised or trained hundreds of the world's leading organizations to become content Jedis. She has worked with many of the Fortune 50, the largest U.S. web properties, the largest nonprofits, and several U.S. government agencies. She also served as the fractional head of content at Mailchimp during its high-growth period before its $12 billion acquisition by Intuit. A member of Mensa, Colleen shares insights about content, AI, and business by writing for Entrepreneur, MediaPost, Forbes, and Content Science Review and by speaking at events around the world. She has earned recognition as a top content change agent by publications such as Technical Communication and a top voice for content strategy and artificial intelligence by LinkedIn. As a top instructor on LinkedIn Learning, Colleen's courses have reached hundreds of thousands of professionals. Connect with Colleen online LinkedIn Resources mentioned in this interview Content Science The Content Advantage, third edition November 2024 Video Here’s the video version of our conversation: https://youtu.be/lumGk_5EH6Q Podcast intro transcript This is the Content and AI podcast, episode number 39. The arrival of generative AI has upended many corners of the content world. As a long-time content consultant and researcher, Colleen Jones is very aware of this phenomenon. But Colleen is equally aware of the enduring value of intelligent, effective content, and the fact that all content efforts must ultimately engage and motivate actual human beings. When applied thoughtfully and strategically at an organizational level, AI can help achieve all of these goals. Interview transcript Larry: Hi, everyone. Welcome to episode number 39 of the Content + AI Podcast. I am really delighted today to welcome to the show Colleen Jones. Colleen is the president of Content Science, and also the author of the forthcoming book, The Content Advantage, in its third edition. It's been out for quite a while and the new edition has a lot of new additions about AI. Welcome, Colleen. Tell the folks a little bit more about what you're up to these days. Colleen: Thank you so much, Larry. It is great to be here, and fantastic to connect with you again. Content Science, we have been doing all kinds of interesting things in and around content. We do a lot of professional services as part of that. We do a lot of research and analysis, and we get the opportunity to do it for clients, but also independently, just delve into things that are of interest to us or that relate to trends that we're seeing. We've been continuing that over the past several years, and I'm really excited with the third edition of the book to bring some of those updated insights, facts, stats, all that kind of good stuff into our current, very interesting situation with AI and content. Larry: Yeah, and I think that very interesting in air quotes is appropriate. And one of the things, I can't remember, I read the second edition

Bill Rogers Bill Rogers is an experienced AI entrepreneur whose latest venture, ai12z, gives web content platform owners tools to build digital assistants and chatbots and to run gen-AI-powered searches. We talked about: his work at his latest startup, ai12z, which builds copilots designed to power content experiences his use of the term "copilot" as a generic AI capability, to distinguish it from branded uses of the word the two main capabilities of their copilot: question answering and ReAct (reasoning and action) his take on RAG architectures and how ReAct fits into them how integrating copilots into content and commerce architectures can guide users through complex interaction flows that are connected to third-party services how to ensure that users have confidence in AI systems and that the systems are technically secure the technical architecture that underlies their copilot platform how copilots help write queries to search utilities and other information and knowledge sources to help with tasks like complex product comparisons the variety of UIs their platform provides: search boxes, knowledge panels, etc. how interactions with copilots can inform an organization's content planning the importance of including image AI in this kind of platform, to both better understand the content and create more robust ALT text Bill's bio Bill Rogers is a visionary entrepreneur with a deep technologist background in AI and digital technologies. Recognized for significantly influencing the evolution of online experiences, Bill founded Ektron and served as its CEO. Under his leadership, Ektron emerged as a pioneering SaaS web content management platform, serving thousands of organizations globally. After Bill sold Ektron to Accel KKR, it merged with Episerver and became part of Optimizely. Bill then co-founded and led Orbita as its CEO, driving innovation in advanced conversational AI. Beyond these startups, Bill co-founded several other ventures and has had an expansive career in digital signal processing and robotics engineering. Bill holds a Bachelor of Science in Electrical Engineering from Boston University. Connect with Bill online ai12z bill at ai12z dot com Video Here’s the video version of our conversation: https://youtu.be/hJPnAvWXBlA Podcast intro transcript This is the Content and AI podcast, episode number 38. You wouldn't try to operate an airliner without a copilot, and you shouldn't operate a modern web architecture one function at a time either. That's the case that Bill Rogers makes for his latest AI startup, ai12z. His company builds AI copilots - in the generic, non-branded sense of that term - that enable robust search and discovery, streamline complex tasks like mulitfaceted product comparisons, improve accessibility, and even help with content planning. Interview transcript Larry: Hi, everyone. Welcome to episode number 38 of the Content and AI podcast. I am really delighted today to welcome to the show Bill Rogers. Bill is a longtime veteran in the content management and technology world. He founded a company called Ektron years ago, which was acquired by Episerver, which is now known as Optimizely. He ran a conversational AI platform long before ChatGPT came out called Orbita, and he's currently the CEO and founder at ai12z. So, welcome, Bill. Tell the folks a little bit more about what you're up to these days. Bill: Thank you, Larry. Yes. So, at ai12z, what we're doing is we're focused on building essentially a copilot, enabling websites and mobile applications, the ability to take advantage of AI to help drive experiences. Larry: Nice. And that's a nice, succinct description of what you do, but a lot of websites have chatbots or things like that. How does a copilot... Well actually, first let me back up because copilot is an interesting term. I first became aware of it when GitHub did their coding assistant thing, and then Microsoft has a whole suite of branded products called Copilots. But we're talking about a generic capability. Is that correct? Bill: That's correct. I think the term copilot, Microsoft has used quite a bit, but it is a generic term. We actually like to refer to it as a website AI assistant. And if you think about it, in the days of Ektron, we had this phrase, "What do you want your website to do?" And now we are talking about, "What do you want your AI to do for your website?" Larry: Interesting. Human needs haven't changed that much, but we have all these new capabilities. I guess what are one or two use cases that have jumped out early in your journey that are really helping people? Bill: So, when you think about, "What does copilot need to do?" So, one of the obvious things is this ability to be able to answer questions. And so when you talk about years back, when people were building chatbots, the challenge was creating the knowledge for that question and answerin

Jeff Coyle Generative AI tools and LLMs bring the need for a new kind of content awareness in organizations of all sizes. While some have focused on content creation, Jeff Coyle has grown and accelerated his content-marketing capabilities by leveraging the content discovery and operations improvements that AI can deliver. We talked about: his decade-long history in working with NLP, AI, and content his overview of the rapid progression of AI technology over the past two years the importance to businesses and enterprises of doing a data inventory to understand their unique strengths the exponential increases in both the capabilities of the AI services he uses and their affordability the importance of creating high-quality content in this new AI landscape how to capture your org's knowledge and use it to fuel your content plans how journalists are crucial for capturing that knowledge his take on the current state of content-industry employment the importance of aligning content and its performance to organizational KPIs the crucial differences between how you wish people would consume your content versus how they are consuming it and how they might be the ongoing difficulties of marketing attribution and how new predictive models that AI affords can help address them how a "process inventory" is even more important than a conventional content inventory Jeff's bio Jeff Coyle is the Co-founder and Chief Strategy Officer for MarketMuse. Jeff is a data-driven search engine marketing executive with 20+ years of experience in the search industry. He is focused on helping content marketers, search engine marketers, agencies, and e-commerce managers build topical authority, improve content quality and turn semantic research into actionable insights. His company is the recipient of multiple Red Herring North America awards, multiple US Search Awards Finalist, Global Search Awards Finalist, Interactive Marketing Awards shortlist, and several user-driven awards on G2, including High Performer, Momentum Leader and Best Meets Requirements. Prior to starting MarketMuse in 2015, Jeff was a marketing consultant in Atlanta and led the Traffic, Search and Engagement team for seven years at TechTarget, a leader in B2B technology publishing and lead generation. He earned a Bachelors in Computer Science from Georgia Institute of Technology. Jeff frequently speaks at content marketing conferences including: ContentTECH, Marketing AI Conference, Content Marketing World, LavaCon, Content Marketing Conference and more. He has been featured on Search Engine Journal, Marketing AI Institute, State of Digital Publishing, SimilarWeb, Chartbeat, Content Science, Forbes and more. Connect with Jeff online LinkedIn MarketMuse Twitter jeff at marketmuse dot com Video Here’s the video version of our conversation: https://youtu.be/Ij18O07YnYc Podcast intro transcript This is the Content and AI podcast, episode number 37. The label "generative AI" has led many to focus on using this new tech for content creation, while the real benefits may lie in different capabilities that LLMs and other AI tools afford. In his work, Jeff Coyle has enthusiastically adopted AI, using it to identify new content repurposing opportunities, to capture and leverage unique organizational knowledge, and to dramatically reduce the costs of content operations, discovering along the way new opportunities for content professionals. Interview transcript Larry: Hi, everyone. Welcome to episode number 37 of the Content and AI podcast. I'm really delighted today to welcome to the show Jeff Coyle. Jeff is the co-founder and Chief Strategy Officer at MarketMuse. We talked on my other podcast, Content Strategy Insights, a couple of years ago, and I'm really excited to have him back because one or two things have changed since then. Welcome, Jeff. Tell the folks a little bit more about what you're up to these days. Jeff: Oh, thanks, Larry. And I am glad to be back. I am the co-founder and Chief Strategy Officer for MarketMuse, as you mentioned. I'm working on building artificial intelligence and content strategy offerings so that teams can make better decisions about what content they create or what content they update and then execute a lot faster. And so I'm sure we'll get into the details, but my background, I've been in the search space, building products, building search engines, building lead management systems, or selling them for 25 years. And I've been in SEO for about that long as well. There's probably nothing in the SEO space that you could ask me about that I haven't tackled or got knocked over by and got back up and then tackled. But yeah, I'm looking forward to this discussion. Larry: There's so much going on in that world. I really want to stay focused on the AI stuff that we might have to slip into SEO a little bit because that's an old practice of mine way back in the d

Cennydd Bowles Like most designers who work in technology, Cennydd Bowles has reflected at times on the impact of his work and its ethical implications. After a couple of decades of information architecture and interaction design practice, Cennydd stepped back from his design work to explore philosophy and ethics in depth. His explorations have led him to extensive academic study as well as speaking gigs and writing on the subject, including a book, Future Ethics. We talked about: his transition from interaction design to tech ethics his origins in the information architecture world and his career, including a stint at Twitter how we as designers have missed predictable mistakes and patterns that ethicists have long known about how he got hooked on philosophy and ethics his 2018 book on the connections between the worlds of philosophy and design, Future Ethics the ethical issues that can arise in even a seemingly harmless practice like A/B testing his prediction that AI will in the not-too-distant future permit almost fully automated product development and the risks that that brings how the difficulties of measuring trust might exacerbate the trust issues that arise with AI the "magical" nature of AI his observation that "the problem with magic is it's intentionally deceptive" a new orchestrator role that he sees coming with AI his pessimism about the prospects for humans over the long term in the AI economy how Cory Doctorow's notion of "enshittification" manifests in the design and AI world what he sees coming: "rapidly iterating mediocrity rather than considered excellence" the power, albeit diminished recently, of employees to influence ethical decision-making within organizations three books he recommends (links below) his advice to designers to listen to and connect with philosophers and learn from their prior work on ethics Cennydd's bio Cennydd Bowles is a technology ethicist and interaction designer, author of Future Ethics, and a recent Fulbright Visiting Scholar at Elon University. Cennydd’s views on the ethics of emerging technology and design have been quoted by Forbes, WIRED, and The Wall Street Journal, and he has spoken on responsible innovation at Facebook, Stanford University, and Google. Connect with Cennydd online LinkedIn Cennydd.com Tech ethics books Future Ethics, Cennydd Bowles Design for Real Life, Eric Meyer and Sara Wachter-Boettcher Ethical Product Development, Pavani Reddy Ethics for People who Work in Tech, Marc Steen Video Here’s the video version of our conversation: https://youtu.be/MbfK7AnPa-0 Podcast intro transcript This is the Content and AI podcast, episode number 36. In the flurry of activity launched by AI-technology investment, ethical considerations have been left largely unexplored. Cennydd Bowles is an accomplished interaction designer who has spent the last several years studying and writing and speaking about tech ethics and responsible innovation. What he sees unfolding now concerns him, leading him to predict that the near-term future is more likely to bring "rapidly iterating mediocrity rather than considered excellence." Interview transcript Larry: Hi, everyone. Welcome to episode number 36 of the Content and AI Podcast. I am really delighted today to welcome to the show, Cennydd Bowles. Cennydd is a technology ethicist and interaction designer based in the UK. Welcome, Cennydd. Tell the folks a little bit more about what you're up to these days. Cennydd: Hey, Larry. Well, so let's see. I've just got back from America, so for the last six months, I've been in Elon University, North Carolina as a Fulbright visiting scholar. This is really a large part of my transition, essentially, from the days of UX and product design within industry, and transitioning from that into academia, and particularly philosophy, philosophy of technology, and ethics of technology. Cennydd: These days, I'm now essentially figuring out what's next. I'm finishing up a master's dissertation right now on the topic of the ethics of A/B testing, which I've got a lot of experience seeing inside companies, and think maybe I can offer something about looking at the ethics of it. After that, well, probably a lot more writing, probably a book or two. Then I think I'm probably heading down the academic path, so probably a PhD in some sort of philosophy, of technology, or computer science somewhere in that kind of space. Larry: Oh, great. I'll have to check back in. I'd love to see where... Getting into the details of this. You just mentioned, well, I guess I would love to talk just a little bit more about your transition, because you've been an interaction designer for a long time. I can't remember exactly how long, but we've talked about this and a little bit about your transition, but can you talk a little bit more about what motivated you to go from int

Sharon Ni One of the most engaging aspects of generative AI products is their conversational interfaces. This has led many content designers working on AI products to develop skills in conversation design. Sharon Ni works on both conversational AI products and script-driven chatbots in her content design role at Cisco. She has developed her conversational design and technical AI skills by attending conferences, hackathons, and other events, by networking extensively, and by experimenting constantly with AI and conversation tech. We talked about: her work on chatbots and AI tools at Cisco an overview of the content design guidance chatbot she built her addition of "conversation designer" to her resume the evolution of the people ecosystem she works in, which now includes more engineers and data practitioners the professional development that she's done to prepare her for working with AI and collaborating with her more technical collaborators how participating in hackathons and other events has helped her advance her AI skills some of the tools she uses in her work, including spreadsheets, Miro, and Voiceflow her personal interest in building chatbots and how it's helped her in professional work the content design repository where she stores the conversational content she works with how she helps her colleagues understand how to best use AI her new responsibilities around assessing the technical feasibility of her advice to "just do it," to start building your own AI projects and connecting with others who share your interest Sharon's bio I love writing products. I hate writing about myself. So here’s five quick things about me and my work in AI: I’m a content designer at Cisco. Currently working on the Cisco AI assistant and Cisco.com chatbot. I like trying and building different chatbots myself - I recently built a content style guide chatbot that can help people review their copy and find guidelines. I’m a fierce advocate for content research and like to use data to inform my content design decisions. I have a background in Psycholinguistics and received a master’s degree from Middlebury College in 2023. Huge fan of this podcast. Connect with Sharon online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/4HgM2hp5hpM Podcast intro transcript This is the Content and AI podcast, episode number 35. One of the main attractions of generative AI products is their conversational interfaces. This basic characteristic has drawn many content designers into the adjacent field of conversation design. In her work on chatbots and conversational AI products at Cisco, Sharon Ni has applied conversation design techniques and also learned a lot about the engineering side of AI, sometimes even advising her colleagues on the technical feasibility of their product ideas. Interview transcript Larry: Hi everyone. Welcome to episode number 35 of the Content + AI podcast. I am really delighted today to welcome to the show, Sharon Ni. Sharon is a content designer at Cisco, is doing really interesting stuff with AI and other technologies there. Welcome, Sharon. Tell the folks a little bit more about what you're up to these days. Sharon: Yeah, hi Larry. Very nice to meet you and excited to be here. And as you mentioned, I'm currently working on Cisco AI system for security, which is part of the Cisco AI ecosystem. And I'm also working on a chatbot that's on the cisco.com website right now. Sharon: And other than that, I am also working with the Voiceflow team to build an AI powered content design, style guide chatbot that can help our design partners to find the right guidelines and also review copy based on the guidelines, basically. It's not going to write the copy for them, but it will provide recommendations based on the good examples and bad examples that I fed into the chatbot and also the templates. So yeah, that's what I do. Larry: Well, it sounds like you're definitely earning your paycheck, at least three major things going on there. I would love to start with the content design guidance chatbot that you mentioned, because that's like... I think that'll be of interest just probably a lot of people are working on similar kinds of things. Can you talk a little bit just in general about... You mentioned that it's not so much doing, writing for people, but it's more like style and voice and tone and stuff. Anyhow, can you talk a little bit about how that chatbot works? Sharon: Yeah. So basically, I injected all of our guidelines into this chatbot. I kind of rewrite it because you can't just put the same... the guidelines into the chatbot. It's not going to recognize it very easily. Sharon: And so I work with the Voiceflow team. They help me to write the code part. And then right now I'm just adding more examples from our product, the copy and our product, and also some good examples and we also ne

Andrew Stein Like many content designers in the fall of 2022, Andrew Stein was concerned about the possible negative impact of generative AI on content and design practice. And his concern was heightened by the large number of content designers on his team. Since then, Andrew has discovered many ways to apply AI in his content design work, both in conventional digital-product design and in content work on AI products. He has also discovered a happy additional benefit of taking the lead on AI. His expertise has led to exciting new collaborations and leadership opportunities. We talked about: his work as a content design and AI leader his take on the best ways to use AI in content-design practice how to maintain focus on the fundamentals of content as you work with AI to create new content or manage and validate existing content, and a tool he is developing to automate this new content-employment opportunities that he sees emerging the clean slate on which content people can create their new AI roles and responsibilities some of his techniques for demonstrating how your content skills can help your AI collaborators: find opportunities to serve adopt a learner's mindset "just do" - experiment with tools on your own some of the people he follows and resources he has consulted as he has developed his AI expertise: Noz Urbina Leah Krauss the conversation design community, in particular Maaike Groenewege his encouragement for all content designers to find a balanced approach to incorporating AI into their career Andrew's bio Andrew is a Director and Principal Content Designer at a financial services company. He’s led content in smart home, social media, AI robotics, and FinTech. Andrew’s experience includes both consulting, and companies like Lowe’s, Wells Fargo, Truist Bank, and Meta. Andrew is currently focused on the way AI tools serve the content design process, and bringing a content-first approach to the development of new AI products and services. Connect with Andrew online LinkedIn ADPList Video Here’s the video version of our conversation: https://youtu.be/hxoMSzyDCFk Podcast intro transcript This is the Content and AI podcast, episode number 34. When generative AI burst onto the scene there were plenty of reasons for content designers to be anxious. Andrew Stein channeled his concern into a deep exploration of AI tech and how it might be applied in content work. As a design leader, he has discovered a number of ways that content designers can use AI tools, and build AI products. As an advocate for content practice, he has found that his AI expertise opens many new doors for influencing his business collaborators. Interview transcript Larry: Hi everyone, welcome to episode number 34 of the Content and AI Podcast. I am really happy today to welcome to the show, Andrew Stein. Andrew is an independent content design leader. He works currently for a big financial services firm. He also has his own consultancy on the side, does various content things including AI stuff for folks. So welcome, Andrew. Tell the folks a little bit more about what you're up to these days. Andrew: Yeah, very cool. Well Larry, super-happy to be here and as I mentioned earlier, I've seen all the episodes and get so much out of them every time, so really happy to be here. Yeah, right now, like you mentioned, I'm doing quite a bit of work both for the company I work for and on the side, working in both AI projects and traditional content design projects and really where those two merge together, both helping to build teams and build structure around how we approach AI from a content perspective, which I think is really key with all of this. And also how to bring AI into the work that we do as well as content designers working on traditional products and services as well. Larry: Yeah, I think that latter is probably the more familiar scenario for most of my listeners, I guess. I do know a number of people who are working on AI products, but I think the more common use case for many people is using AI in their day-to-day, just good old-fashioned content design work. Especially as a leader, how are you implementing that and encouraging your folks and just tell me a little bit about that. Andrew: Yeah, well I think at first, all of us were wondering does this do the writing for us? Does this replace us? There was quite a bit of fear and trepidation or looking at it very cynically like, "Oh, this thing can't do anything for me. It's not a writer, I'm the writer in the room." I think there's been a spectrum of views on it, but all looking at it as the writer. Is it going to be the writer? Can it replace the writer? No, it can't. And what I've really landed on, or at least at this point in time is that, no, it's not the writer, but it's a really great assistant to the writer. And so that's really the perspective that I'm coming at it from with the te

Anna Potapova Generative AI creates new opportunities to create and manage content at scale. And scale is definitely required when crafting content experiences for one of the world's largest ecommerce companies. Anna Potapova is incorporating gen-AI across the span of her work at AliExpress: content creation and management, localization, personalization, and other areas where her strategic-content mind guides her. We talked about: her recent promotion to a new leadership role at AliExpress which types of content are most amenable to being generated by AI the standards they use to guide the creation and ensure the quality of AI content the crucial role of content designers and localization experts in the ongoing iterative improvement of AI content at a large scale how AI enables the democratization of content creation the large percentage of user-generated content on the AliExpress platform how AI helps her team with personalization how gen-AI content helps them scale their marketing personalization efforts the importance of inviting yourself to machine learning and data science meetings to show the value you bring the value of case studies when communicating with internal stakeholders to show the value you can bring the importance of staying grounded in business objectives when developing relationships with your collaborators how a strategic approach to your work can help your org use AI most productively how the shift from hand-crafted content to AI content at scale manifests in content operations her plans to explore how AI can help evaluate content quality and conduct content audits the concept of hyper-localization, which addresses very specific regional and cultural differences the importance of proactively engaging with product and tech colleagues to ensure that standards-backed content powers AI products going forward Anna's bio Anna Potapova is Staff Content Strategist at AliExpress (part of Alibaba Global Digital Commerce group). She changed team positioning from pure localization to Content Design, built a style guide and a system to maintain it, established standards for AI generated content in multiple languages and improved business metrics while reducing production costs. Anna has been featured on several podcasts (Content Strategy Insights, Writers of Silicon Valley, Localization Leaders), joined UX Evenings @ Google and helped to build a content community in China. Connect with Anna online LinkedIn Video Here’s the video version of our conversation: lkjsdf Podcast intro transcript This is the Content and AI podcast, episode number 33. When you create, manage, personalize, and localize content at scale for a global ecommerce giant like Alibaba, you need all of the automation help that you can get. In her role as a content strategy and design leader at AliExpress, Anna Potapova is harnessing the power of generative AI tools and techniques to address customers' individual preferences, to help third-party vendors create better content, and to streamline their internal content design operation. Interview transcript Larry: Hi, everyone. Welcome to episode number 33 of the Content and AI podcast. I'm really delighted today to welcome to the show, Anna Potapova. Anna is a staff content strategist at Alibaba, the big e-commerce merchant in China. She works specifically for AliExpress. Welcome to the show, Anna. Tell the folks a little bit more about what you're doing these days. Anna: Thanks, Larry. Happy to be here again. Should I mention that since the last appearance on your podcast, I was on Content Strategy Insights with Arnaud. Since my last appearance I was promoted, I attributed exclusively to your podcast. Thank you so much for having me again. Larry: That's too awesome. Thank you. Anna: Recently, I've been talking a lot about AI and my team has been doing a lot of work in this area. Last week I actually spoke in front of front the audience of over 200 people in Chinese about how my team is harnessing the power of AI as we need to generate a lot of content every day. Larry: Nice. And you as one of the biggest commerce, maybe the biggest on the planet, I mean, there's a lot of content. Every one of those products needs something said about it. And every correspondence you have, there's so much going on there. And a lot of it I'm imagining is either routine or data-driven or in some way amenable to the use of AI. Can you talk just a little bit at a high level about how you're using AI? And also, I just want to note for folks that all of these conversations, we're going to dance around anything remotely proprietary. We're just going to talk in general about how big enterprises can work with big, vast content repositories and how AI can help. Can you talk a little bit about how you use AI to generate content? Anna: Well, first of all, it all comes down to what types of content can really be, dare I say, outsourced, can be created w

Duane Forrester SEO has always been difficult, but generative AI takes things to an entirely new level. Duane Forrester has been immersed in the search world for more than 20 years, including stints as the Product Manager for the Bing Webmaster Program and Vice President of Industry Insights at Yext, where he developed company AI strategy. He also helped launch the schema.org structured-data standard. Duane offers plenty of AI-specific advice about how to navigate the new search landscape. But he also says that the foundations of good SEO are still grounded in timeless digital best practices: understanding your customers' needs and intentions and consistently giving them good content and helpful user experiences. We talked about: his long history as a search-industry expert and leader his high-level take on the current state of AI the true benefits of AI for content and how they relate to SEO the title of his content-and-genAI cookbook: "Common Sense" the importance of understanding the kinds of content that are resonating with your customers an interesting AI-driven SEO-localization case study that was presented at PubCon last year that demonstrates the power of understanding user intent an overview of the knowledge graph tech that underpins the search infrastructure at tech companies and big enterprises his predication that the future of search will be knowledge graph to knowledge graph conversations between companies and search engines the rapidly evolving new world of SEO and the imperative for businesses to leverage AI to keep up with the increasing need to scale SEO operations the enduring importance of providing a good user experience at the end of a search flow the importance of delivering content in video format into a search landscape increasingly driven by social media new search behaviors created by Google's Circle Search and AR tech like Meta's Ray-Ban glasses his observation that search is infinitely more complex than most SEOs can imagine the secret to search success: attracting attention from consumers, by deeply understanding their behaviors and intentions his prediction that Apple will launch an AI-powered Siri in September that will thrust ChatGPT into the mainstream Duane's bio Duane Forrester is a distinguished figure in the search industry, with a career that spans digital marketing, authorship, and leadership roles at prominent companies such as Microsoft Bing, Bruce Clay Inc. and Yext. His expertise in digital marketing is complemented by a strong understanding of AI/ML, consumer behavior and customer experience, making him a well-rounded and sought-after professional in the field. During his tenure at Microsoft, Duane was instrumental in the development and launch of Bing Webmaster Tools and Schema.org, focusing on the needs of webmasters and digital marketers. His deep knowledge of search engines and user behavior contributed to Bing's growth and success. Beyond his work at Microsoft and Bing, Duane has showcased his knowledge as a prolific author in the digital marketing sphere. He has written for most industry publications and his two books, "How to Make Money with Your Blog" and "Turn Clicks into Customers," have provided invaluable insights and guidance to numerous businesses navigating the competitive online landscape. Today, he, continues to share his extensive knowledge of digital marketing, AI, and customer experience, shaping the future of the search industry and empowering businesses to thrive in the digital era. Connect with Duane online LinkedIn Facebook Threads Twitter Duane's books How to Make Money with Your Blog: The Ultimate Reference Guide for Building, Optimizing, and Monetizing Your Blog Turn Clicks into Customers - How to deliver conversions across all online marketing activities Video Here’s the video version of our conversation: https://youtu.be/OjCH0b3isrs Podcast intro transcript This is the Content and AI podcast, episode number 32. For almost as long as people have been building websites, SEO practitioners have tried to get their content to the top of the search results. Search has always been a rapidly evolving field, but generative AI takes change to a whole new level. Duane Forrester has been immersed in the search world for more than 20 years. He offers this timeless advice for coping with the new AI and search landscape: understand your customer's intentions, and serve them with good content and helpful experiences. Interview transcript Larry: Hi everyone. Welcome to episode number 32 of the Content and AI podcast. I am really delighted today to welcome to the show Duane Forrester. If you work in anything adjacent to search, you know Duane. Years ago, he was the Bing Webmaster tools, I guess advocate or program manager. He helps launch Schema.org, that ontology that schema that you're all working towards when you try to promote your content online. He worked with Bruce Clay for a w

Leah Krauss New AI products like Microsoft's Copilot can be powerful productivity enhancers, but if designers aren't careful they can inadvertently introduce into the product the bias and other hazards that can come with large language models. As a content designer working on Microsoft's Copilot for Sales product, Leah Krauss helps her colleagues understand and follow the responsible-AI principles that the company has developed. Leah's advocacy helps her design and product teams create a product that balances the need for transparency about the use of AI with the prerogative to keep customers in flow as they use the product. We talked about: her work as a content designer on Copilot for Sales at Microsoft and her advocacy there for responsible AI how she collaborates with her data science team, which had established a relationship with the content team even before Copilot on other products the evolution of their AI product-development process how their design system supports the implementation of responsible AI the six principles that guide responsible AI at Microsoft: fairness reliability and safety privacy and security inclusiveness transparency accountability how she advocates for responsible AI on the Copilot for Sales product team the balance between keeping customers in their flow and being transparent about AI features the concept of the "human in the loop" and how they apply it in the Copilot for Sales product the importance in AI product design of always being aware of edge cases and possible misuses of the product her encouragement to anyone working on AI products to stay curious, ask a lot of questions, and to bear in mind the importance and relevance of our language expertise Leah's bio Leah Krauss is a senior UX content designer at Microsoft. She works on Copilot for Sales, Microsoft's AI software for salespeople, where she also collaborates closely with the data science team. She champions responsible AI to anyone and everyone who'll listen, including inside Microsoft and at various UX conferences. Outside of work, you can usually find her reading, or spending time outside with her family - hiking, exploring cities, and hanging out on the beach. Connect with Leah online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/VItdSUgzkZE Podcast intro transcript This is the Content and AI podcast, episode number 31. The introduction of AI tools like Microsoft's Copilot creates new opportunities for content designers. But as with any innovation, the new technology can be a two-edged sword. For every customer workflow that is streamlined there may also be an opportunity for bias or hazard to get into the product. As a content designer and champion for responsible AI, Leah Krauss helps her colleagues at Microsoft understand and apply responsible AI principles in their product design work. Interview transcript Larry: Hi everyone. Welcome to episode number 31 of the Content and AI podcast. I'm really delighted today to welcome to the show Leah Krauss. Leah is a senior UX content designer at Microsoft where she works on Copilot, which many of you may have heard of. So welcome Leah. Tell the folks a little bit more about what you're up to these days. Leah: Hi Larry. It's so nice to be here. So yeah, as you mentioned, I'm working on Copilot for Sales, which is a flavor of Microsoft Copilot, and that's been really exciting to be in on kind of the ground floor of AI at Microsoft. And responsible AI, which is what we're going to talk about today, is one of my most favorite topics to talk about. I've done some conference talks about it and my coworkers are really tired of hearing me go on about it. I actually serve, no, that's not true. It's only half true. I serve as actually a responsible AI champion, one of the responsible AI champions on my team. So it's sort of my thing and I think it's so exciting the moment we're at here and how big a part content designers can play in it. Larry: Yeah, I think when you're working with language models, you think the content people would have a leg up on some, but that's really, first thing I want to follow up on is that Copilot, I think it's sort of like multiple products then. It's a suite, well I guess Microsoft knows about suites with the Office suite, so there's integrations of copilot with each of the Office elements, Word and Excel and all that. And then there's also specific tools like Copilot for sales. How big is that little budding empire at Microsoft? Leah: Well, so there yeah, like there's one Copilot and then the different flavors depending on the user's needs. So as you said, if people are using Office, they'll see Copilot in Word and they'll see it in PowerPoint and Outlook of course. And if they have more specific needs like a salesperson, then they can use our more specif

Jack Molisani As the founder of the long-standing LavaCon conference and the principal at a technical content staffing agency, Jack Molisani gets a deeply informed view of the world of technical communication. While he sees the opportunities that generative AI presents, he raises several concerns for technical content strategy practitioners, among them the inaccuracy of generative AI content and the inability of AI tools to comprehend subtle human communication clues. We talked about: his work as the Executive Director of the LavaCon Content Strategy Conference and at ProSpring Staffing, a technical communication job agency how a change in the LinkedIn messaging interface inspired him to spend more time at in-person events his observation that many product features that are promoted as "AI" are actually capabilities that have been around for years his concerns about the ability to identify and vet the sources that AI tools cite his assessment of the job prospects for technical communicators in 2024 his exasperation with the decline in quality of applicant tracking systems (ATS) some of the tasks in technical communication that AI can help with the inability of AI tools to account for subtle human communication dynamics like facial expressions how using AI writing tools can misrepresent your own writing ability how a speed networking event that troubled introverts at a prior LavaCon led to the introduction of calming therapy animals at the event, including a therapy llama Jack's bio Jack Molisani is the President of ProSpring Staffing, an employment agency specializing in content professionals (both contract and perm). He's the author of Be The Captain of Your Career: A New Approach to Career Planning and Advancement, which hit #5 on Amazon's Career and Resume Best Seller list. The first printing is sold out. Watch for a soon-to-be-released second edition. Jack also produces The LavaCon Conference on Content Strategy, which contains an AI track. The 2024 conference is 27–30 October in Portland, Oregon. Register using referral code LSPODCAST for $200 off in-person tuition. Connect with Jack online LinkedIn LavaCon content strategy conference Prospring Staffing Video Here’s the video version of our conversation: https://youtu.be/RsgY89El1Aw Podcast intro transcript This is the Content and AI podcast, episode number 30. The rise of generative AI affects every type of content practice, including the venerable institution of technical communication. Jack Molisani runs both a tech comms staffing agency and the annual LavaCon content strategy conference, which he's organized for more than 20 years. Jack brings a deeply informed perspective to the conversation around the introduction of AI into content practice, especially its impact on employment prospects for technical communicators. Interview transcript Larry: Hi, everyone. Welcome to episode number 30 of the Content and AI Podcast. I'm really excited today to welcome to the show Jack Molisani. Jack is a legend in the textbook, communication, and technical content strategy world. He's the executive director of the LavaCon Content Strategy Conference. He also runs a staffing agency called ProSpring Staffing. Welcome, Jack. Tell the folks a little bit more about what you're up to these days. Jack: Wow, okay. As you said, I'm running around two spheres. One is producing the LavaCon Conference in content strategy. The other one is running a staffing agency for technical writers and other content professionals. Although we also have a division that does engineers, and there's some crossover there. What's interesting, and it's almost a side note but since you asked what I've been up to, is I've discovered that it's almost impossible for me to land new staffing clients over the internet anymore. Larry: Interesting. What's going on there? Jack: It used to be that someone would post a job on LinkedIn, and I'd wait two weeks. If it's still there I said, "Hey, could you use some help finding someone?" And they'll tell me yes or no. Jack: Well, a couple things happened. One is LinkedIn bifurcated your message inbox. It now has two labels, focused and other. It didn't announce this. Suddenly, all my responses were going to other and I thought I had an empty inbox. Where once I discovered this other tab, had people responding to me for two years saying, "Yes, we need help." Larry: Oh, God. Jack: By then, they don't need help anymore. Two, LinkedIn opened an API so people could use tools to email thousands of people at a time. Suddenly, mine and every other inbox is just filled with spam. Trying to weed all through that to find the real communication piece. And then, they added a third option on their reply screen, a pre-populated answer that says, "Thanks, we're not interested. Thanks, call me. Thanks, but not interested," and delete

Lisa Welchman Over the past 25 years, Lisa Welchman has established and codified the field of digital governance. With an enterprise consulting career that spans the emergence of the web, the arrival of social media, and the rise of mobile computing, she is uniquely positioned to help digital practitioners, managers, and executives understand and manage the governance issues that arise with the arrival of generative AI. Lisa is the author of the leading book in her field, Managing Chaos: Digital Governance by Design. We talked about: her career in enterprise digital governance her concern about the lack of transparency in the existing governance practices at AI companies an analogy she sees between WYSIWYG and AI tools the contrast between more mature governance models like the UX field has developed and newer digital practices like the adoption of GPTs governance lessons that new tech implementers can always learn from prior tech eras her call to action for technical experts to alert executives of possible harms in the adoption of new technology the elements of her digital governance framework: understanding team composition and the organizational landscape in which digital practitioners operate having a strategic intent articulating governance policies establishing practice standards the range of digital makers she gets to interact with in her work the importance of accounting for the total business and organizational environment when jockeying for a seat at the table the responsibility of experienced digital makers and managers to call out potentially troublesome patterns in the adoption of new tech the importance for digital practitioners of staying aware of how much agency they have right now Lisa's bio Lisa Welchman is a digital governance trailblazer with over two decades of experience. She's passionate about helping organizations manage their digital presence effectively and sustainably. Known for her practical approach, Lisa has worked with a variety of clients, from global corporations to non-profits. She’s also a popular speaker and the author of "Managing Chaos: Digital Governance by Design." A mentor and educator at heart, Lisa is dedicated to helping leaders make the digital world a safer and kinder place for everyone. Connect with Lisa online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/-UIj0YWxLaI Podcast intro transcript This is the Content and AI podcast, episode number 29. Whenever new technology like generative AI emerges, organizations have to deal with both the opportunities and the challenges that arrive with it. It often falls to practitioners like content strategists and designers to alert the C-suite of potential governance concerns that arise with the adoption of new tech. Lisa Welchman sees in this situation an opportunity for digital makers to take the lead on educating their organizations about these important issues. Interview transcript Larry: Hi everyone. Welcome to episode number 29 of the Content + AI Podcast. I am really happy today to welcome to the show Lisa Welchman. Lisa is a true legend in the field of digital governance. She pretty much established the discipline, I think it's safe to say, over the past 25 years. She wrote what I would argue is the leading book on it, Managing Chaos: Digital Governance by Design. But welcome Lisa, and the reason I wanted to talk to you this week is we're right in the middle of Rosenfeld Media is doing a conference on design and AI, and it seems like AI is an area that's really ripe for a conversation about governance. Does that make sense? Lisa: Yeah, it does. I will contextualize myself a little bit in saying that digital governance is a really broad term, and my focus is really around enterprise digital governance, how digital governance manifests inside of an organization that's making and putting things online. And there's a lot of other governances around there in the internet web space that are equally interesting, but not where I specialize. Larry: That idea of enterprise. And what's interesting about that is that the big companies that are doing this stuff, that are most prominent in the field, it's all Google and Anthropic and Microsoft and OpenAI and huge organizations like that. Do you have any feel for what governance is happening inside those orgs? Lisa: I don't actually have any kind of feel. I think the types of organizations that you describe have in some capacity mature governance inside of the organization because of the nature of the types of products and services that they offer online. And just from evidence. Now, whether or not we like the decisions that are being made within that governing framework that they have, that's an entirely different concern. I am concerned about those larger organizations married with the newness of this version of AI, that's like the iceberg, the AI iceberg is finally poking its h

Rob Hoeijmakers LLM-based conversational tools are revolutionizing all parts of the content ecosystem, including blogs by independent professionals. Rob Hoeijmakers is an independent web strategist based in Amsterdam. He's using AI tools like Whisper and Perplexity to streamline and improve his research and writing workflows. This lets him spend more time on his websites' information architecture and improves the business results he gets from his blog. We talked about: his work as a web strategist and his multiple blogs his happiness with being able to delegate tasks to his LLM colleagues the freedom that AI tools like Whisper give him to research, think, and ideate as he walks how the abundance of content that AI tools provide helped him abandon his old scarcity mindset around information the huge time savings he realizes from using AI-generated summaries of transcripts of interviews how he uses AI tools to draft his blog content his insight that the real value in his blog is in its information architecture his preference for using his own images over AI-generated ones the details of his content "knitting" which stitches together his current and prior content the analytics tools he uses to track traffic to his blog how he uses his blog as a conversation starter Rob's bio Rob Hoeijmakers is a passionate web strategist with over 30 years of experience. Known for his curiosity and love for recognising patterns, he excels in crafting engaging content and innovative web solutions. Rob writes insightful blogs and is a hands-on builder of content, chat, and messaging platforms. A dynamic public speaker, he frequently discusses web strategy, digital marketing, and AI, always focusing on enhancing user experiences and client success. Connect with Rob online LinkedIn Instagram Twitter Web Strategies Web Strategies (Netherlands version) Chat voor Bedrijven (Chat for Business) Video Here’s the video version of our conversation: https://youtu.be/FRaHqLRWT9k Podcast intro transcript This is the Content and AI podcast, episode number 28. Many of the stories you read in the media about the adoption of AI tools cover enterprise workflows and other uses in large organizations. It turns out that LLM-based applications can also help tiny, one-person companies. Rob Hoeijmakers is an independent web strategist based in Amsterdam. AI tools like Whisper and Perplexity have revolutionized his research and writing workflows, letting him focus on his websites' information architecture and the business of blogging. Interview transcript Larry: Hi everyone. Welcome to episode number 28 of the Content and AI podcast. I am really happy today to welcome to the show Rob Hoeijmakers. Rob is a web strategist based in, are you in Amsterdam? I forgot. Rob: Yes. Amsterdam. Larry: Amsterdam. Yeah, in Amsterdam here in the Netherlands. I'm also here in the Netherlands. And also as part of any web professional nowadays, he blogs a lot and we were talking at an event a few weeks ago about his blogging and I said, Oh, tell me more. And I'm like, wait, I have a podcast. Let's talk about it on the podcast. So anyhow, welcome Rob, tell the folks a little bit more about what you're up to these days. Rob: Yeah. My name is Rob Hoeijmakers. I'm a web strategist and for content marketing, I blog a lot. It's not only marketing, it's also way of learning and keeping up. I am into LLMs driven chat bots. I did it with the ReSViNET, which is on the, which is RS virus thing. So that's something I'm working on currently. And then of course for my blogging, I write a blog in English, I write a blog in Dutch and I have another one in Dutch on chat for companies. That's what I do. Larry: Oh, nice. And the main thing, you do a lot, like all of us these days, but what I really wanted, hoping we can focus the conversation around is the way AI has helped you in your blogging workflow. Larry: Because when you think about blogging is like the old thing about the power of the press belongs the person who has one. We all have a printing press now. We have our own blogs, but we don't have the whole editorial staffs that giant publishers do. Is that how it feels with AI? Does it feel like you have a team now? Rob: Yeah. Absolutely. Absolutely. I feel like being the manager of a rather big team, and it's really a joy because it's so many chores I've been able to delegate and I've been able to be more productive. I. Rob: I've been able to be more deeper into things because I can have conversations, I can do research things if you have to do that through Google, and I'm basically doing all those things alone. I don't have a big group of people. I don't have a big office with all sorts. Of course, I have friends and colleagues who are into this as well, but they have busy lives. Rob: So I have loads of conversations with the LLMs to deepen my knowledge, to b

Chelsea Larsson The arrival of generative AI gives content designers a whole new toolkit. As with any new set of gear, there's some learning that comes with the new capabilities that the tools afford. At Expedia, Chelsea Larsson is leading her team of content designers into the AI design future with fresh takes on the planning, design, and evaluation skills that designers have always relied on. We talked about: her work as a senior director of experience design at Expedia how she is facilitating with her teams the shift from product development design to AI design how she has identified new capabilities that AI brings and is incorporating them into product road maps how content strategists and architects help them decide whether to use generative AI or structured-content methods their shift from front-end content design to working with back-end engineers and architects how new LLM-driven applications of conventional content-evaluation criteria permit them to scale up their content design work their goal of creating good-quality content at scale how content designers are shaping the future of conversational ecosystems how AI lets content designers do more strategic thinking, in particular about how to apply their insights at scale her take on the recent rounds of tech layoffs one of the new roles that are emerging for which content professionals are well-suited, like the new position of model designer the origins of their AI program in a simple application of gen AI to partner content creation how to bootstrap the implementation of AI content practices in your org how to identify opportunities to help your customers by matching their content use cases with your AI capabilities her message to content designers: "don't be afraid" and keep learning Chelsea's bio Chelsea Larsson is a Sr. Director of Experience Design at Expedia Group where she leads the B2B Content Design team, partners on strategic design initiatives, and builds AI travel tools. Chelsea loves to chat about Content Design in genAI and UX design for travel. She shares her thoughts on both topics via the Smallish Book newsletter and conference stages around the world. Her favorite book to gift loved ones is the delightful Chirri and Chirra series. Her favorite sandwich is a turkey club. Connect with Chelsea online LinkedIn Smallish Book Video Here’s the video version of our conversation: https://youtu.be/qKr7o5aKQrM Podcast intro transcript This is the Content and AI podcast, episode number 27. The arrival of generative AI tools gives content professionals a whole new palette of design capabilities. Learning how to take advantage of these new opportunities so that they can shift from product-development design into content-driven AI experience design challenges many content folks. Chelsea Larsson sees these challenges as a chance for both her and her team at Expedia Group to stretch and grow and to scale their impact as design professionals. Interview transcript Larry: Hi everyone. Welcome to episode number 27 of the Content and AI Podcast. I am really delighted today to welcome to the show, Chelsea Larsson. Chelsea is a senior director of experience design at Expedia Group. And welcome Chelsea, tell the folks a little bit more about what you're up to these days. Chelsea: Thanks for having me, Larry. As you said, I'm a senior director of experience design. I lead the B2B content design team at Expedia Group. So we call that the partner content design team, because we work with Expedia partners. I also lead the Generative AI Experience Design Program, which we'll get into later and lean in on a couple of strategic initiatives at Expedia. Larry: Cool. And I think one way we were talking before we went on the air is we were talking about the idea of these AI learning machine, and that seemed to resonate with you as a way to describe what you're up to. Can you tell me about the machine you're building there? Chelsea: Yeah, so when I first started getting into AI, which I think was around a year ago, and talking about generative AI here, of course, I saw a kind of paradigm shift in how content designers specifically could work in AI fields, and it kind of led me to create what you called the learning machine, because when you're working with AI features, the planning is different, the designing is different, and the evaluating is different. It's not fundamentally different, but there are new layers to consider. Chelsea: And those layers led to a lot of questions on, well, how do we plan for the right AI opportunities in our product roadmap? How do we design these AI interactions, questions, when do we disclose that AI is being used? How do we signify that AI technology is being used without words? So what kind of iconography do we use? And then how do we evaluate the output differently than we would evaluate the output if humans had generated the content? So, when you think about those three d

Patrick Stafford Like most tech professionals, content designers are extremely interested in how AI might affect their work and employment prospects in the future. Patrick Stafford and his colleagues at the UX Content Collective recently conducted research to explore the impact of AI on the future of the profession, as well as the attitudes and opinions of content designers about new AI tools and practices. We talked about: his work as the co-founder and CEO of the UX Content Collective the high-level findings of his recent research on the impacts of AI on content design the coincidental timing of the release of GPT-3 and the wave of layoffs in content design and other tech professions his take on the current content design job market, that it's now a more typical market comparisons of the job market in 2016-18, 2019-21, and and from 2022 through now the decline in corporate training budgets recently his take on working "with" AI as well as "for" AI products the emerging critical role of content designers in ensuring the ethical use of AI his observation that most of the new AI jobs being created are being staffed from within companies, not by hiring outside talent the growing importance stated in many job postings of being familiar with AI tools the main benefit of AI for content designers: the ability to scale the important role of content designers applying best practices and design sensibility to gen AI output how the UX Content Collective curriculum has evolved in response to the arrival of AI the surprising finding in their research that 80% of people either feel the same or more hopeful about the industry after the introduction of LLMs and AI the upcoming revival of his podcast Writers of Silicon Valley Patrick's bio Patrick Stafford is the CEO and cofounder of the UX Writers Collective. He is a former Lead Digital Copywriter for MYOB, the largest accounting software provider in Australia, and has consulted with several businesses on UX content strategy. Connect with Patrick online LinkedIn UX Content Collective The Future of AI and Content Design research report Writers of Silicon Valley podcast (reboot coming soon) Video Here’s the video version of our conversation: https://youtu.be/ijMMmsWQZKo Podcast intro transcript This is the Content and AI podcast, episode number 26. The arrival of GPT-3 and the explosion of interest in generative AI caught many in the content-design profession by surprise. Arriving as it did around the same time that mass layoffs hit the tech industry compounded the anxiety around this new tech. Patrick Stafford and his colleagues at the UX Content Collective recently conducted research to explore the true impact of AI on the profession, as well as the attitudes and opinions of content designers about new AI tools. Interview transcript Larry: Hi everyone. Welcome to episode number 26 of the Content and AI podcast. I'm really happy, today, to welcome to the show, Patrick Stafford. Patrick is the co-founder and CEO at the UX Content Collective, which you hope you've heard of. Anyhow, welcome Patrick. Tell the folks a little bit more about what you're up to these days. Patrick: Thanks, Larry. I'm really glad to be talking to you today. It's always a pleasure to speak to you. So yes, as Larry said, I'm the co-founder and CEO of the UX Content Collective. We started in 2019, and we offer a range of courses and workshops related to UX content. So that could be from a broad beginning in UX writing fundamentals to more specialist skills like content ops or even things like systems thinking, which is a workshop we have coming up, and a range of different courses in writing skills and accessibility, localization, a variety of different skills that content designers or content adjacent professionals may get something out of. So that's what we're doing and of course we have a very big interest in AI at the minute, given everything that's going on, and we're starting to delve into that as well. So that's me. Larry: That was sort of the trigger. I always liked talking to you too, but the trigger for this specific conversation was you all just recently did a study on, I can't remember the exact title of it, it was about the impact of AI on our work. And I would love to hear ... I'd love to go through it. I know there's more to it, but you share, in the report, five insights and discoveries that you made. I don't know, maybe walk through the top-level findings of that survey. Patrick: Yeah, sure. And I have to say, Larry, a big round of applause has to go to you for championing this topic, I think, because for a lot of content designers or even just people in content, in general, when generative AI came along, people felt very lost, and they didn't really have an anchor to have to ground them in the future possibilities of what's going on. And so I think your podcast is a great

Wouter Sligter Figuring out how to best adopt new technology is difficult at any time for any organization. AI tech rachets up this challenge to new heights. Wouter Sligter helps companies understand the capabilities and limitations of LLMs and related technologies to create trustworthy experience-delivery platforms. Transparency is a key element in implementing solutions that evoke and support the authentic human experiences that underlie these systems. We talked about: his background as a UX-focused designer and his shift to conversation and AI design the growing number of business use cases that his work supports as well as the growing palette of tech tools that he has to work with how he creates authentic and trustworthy experiences with LLMs and adjacent tech the benefits of RAG (Retrieval Augmented Generation) the growing number of platforms that support building AI experiences the huge failure rate of conversational AI implementations, and how better design might improve the success rate the importance of being genuinely customer-centric when implementing AI projects how his background in language and music helps his AI design work, in particular the benefits of "being comfortable with the uncomfortable" the importance of companies being transparent about their AI implementations how localization manifests in the AI world the growing acceptance of chatbots by consumers his advice to jump into AI now, beginning with due diligence about how you'll implement it in your organization Wouter's bio Wouter Sligter is a Senior Conversation Designer and Generative AI Engineer. He has been a committed team lead and has consulted for a large number of Conversational AI implementations, most notably in Finance, Healthcare and Logistics. He has an innovative mindset and a sharp sense for understanding user needs. Wouter always looks to improve the conversational user experience by following iterative design patterns and verifying outcomes through data analysis and user research. Both predictive NLU and generative LLMs and SLMs are part of Wouter's toolkit. Wouter has a background in ESL and IELTS teaching at language centres and universities in Vietnam. He has developed a strong awareness for language and cultural peculiarities, with native fluency in English and Dutch and good conversational skills in Vietnamese, German, and French. Connect with Wouter online LinkedIn YouandAI.global Video Here’s the video version of our conversation: https://youtu.be/Ak0liSLR8_0 Podcast intro transcript This is the Content and AI podcast, episode number 25. One of main reasons that people have taken so quickly to AI tools like ChatGPT is their conversational nature. People like talking to each other - and to computers. In human conversation, we've developed skills and instincts that help us determine the trustworthiness of the person we're talking with. In tech-driven conversations, we often have reason to mistrust. Wouter Sligter helps companies build conversational systems that express the authentic humanity of their creators. Interview transcript Larry: Hi everyone, welcome to episode number 25 of the Content and AI Podcast. I'm really delighted today to welcome to the show Wouter Sligter. I met him in Utrecht in the Netherlands. He's in the co-working space we both work out of. There, he is a conversational AI consultant. He does conversation design and he's a generative AI engineer. He has his own company called You and AI Welcome, Wouter. Tell the folks a little bit more about what you're up to these days. Wouter: Hi Larry. Very good to be here. Thank you for inviting me. What am I up to? I think you mentioned the three things that I like most doing and that I do most often. I've come from being a self-employed freelance designer really, when in 2018, Facebook started with their chatbots on Messenger. I jumped in and quickly caught on and got a lot of clients worldwide, really building chatbots for them. At that time, I was mostly working on the content side with what you see is what you get kind of flow builders and slowly got pulled into the tech side as well. Wouter: I worked for enterprise as a consultant for a few years in the Netherlands, and then I decided last year to go back to being freelancer, and that eventually culminated in now having my own company, You and AI, with which I'm doing all kinds of outsourcing work from Vietnam. Of course, lately a lot of work is involving generative AI LLMs like RAG implementations and fine-tuning. In my bones I'm still a Uxer, so I'm always looking to build stuff that actually works for people rather than only playing around with tech that no one uses. There's really my strong point, I think. Larry: I love the way you say that. I have many engineer friends, but they're really prone to just building stuff because they can. We're both designers and I love human-centered design and human-dri

Lasse Rindom Lasse Rindom both consults with enterprises on AI projects and talks with business and technology experts about their thoughts and discoveries. In both his consulting practice and his podcast conversations, Lasse has discovered both tremendous opportunities and potentially pitfalls when adopting enterprise-scale AI solutions. We talked about: his work as an AI leader at Basico, the origins of his AI-focused podcast, The Only Constant the unexpected opportunities that arise from the new ability to work with unstructured content that AI affords his quest for use cases that will help identify new governance structures and operational frameworks some examples of AI workflows that enable new business capabilities, like the ability for non-coders to query an agent that can write SQL queries for them his candor in his consulting practive about the possible pitfalls of AI tech, in particular the consequences of LLM hallucinations how current LLMs fall short of natural language, acting more like "chaotic code" the unfortunately common belief that generative AI can be applied one way that he is addressing the "lying robot" problem: using multiple AI agents to correct each other (instead of fine-tuning the models) the current strategic AI deficit in the market, resulting in consultants pushing untested engineering solutions the differences between how enterprises and SMBs consume tech solutions the importance of holistic thinking and staying focused on core problems as you explore AI solutions Lasse's bio Lasse Rindom is AI Lead at Basico and a leading expert on AI and automation. He has previously been global technology manager at facility management giant ISS and CDO of Baker Tilly Denmark. Lasse is a frequent debater on LinkedIn, a Gartner Peer Community ambassador and is host of the podcast “The Only Constant” in which he has deep discussions with global thought leaders on what AI and technology means for us as humans and as businesses. Connect with Lasse online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/_fdAweq3Wuw Podcast intro transcript This is the Content and AI podcast, episode number 24. I generally focus these interviews on content practices, but I'll zoom out now and then to explore the broader strategy and technology landscape. Today I'm talking with Lasse Rindom, a thoughtful and knowledgeable consultant who works with enterprises on big AI projects. He's also a podcaster who talks with business leaders around the world about AI and tech. In his conversations and consulting work, he has discovered a world of lying robots, chaotic code, and strategic deficits. Interview transcript Larry: Hi, everyone. Welcome to episode number 24 of the content and AI podcast. I'm really delighted today to welcome to the show, Lasse Rindom. I'll have him pronounce his name correctly in just a minute. I don't speak Danish, apologies. But Lasse is the AI lead at Basico, a Danish consultancy that works with big enterprises in Denmark and other places, I'm assuming as well. But welcome to the show, Lasse, to tell the folks a little bit more about what you're doing there at Basico. Lasse: Hi, Larry, and thank you for having me on the show today. I'm really thrilled to be here. So my name is Lasse, Lasse Rindom. That's how you say it in Danish so people could know that. I always say it's okay to say Lasse. Everyone knows that, that's dog. Lasse: I am the a AI leader at Basico, which means I'm defining our go-to-market strategy and our products in the AI space, and we focus very much on the back office function. So that's your legal, facility management, finance, HR payroll and finance IT systems. So I'm defining how we want to approach the AI market in that space and primarily in Denmark. Prior to that, I've had stints at an analyst firm, very short stint, and I've been a chief digital officer and head of digital at an SMB and an SMB consultancy. Plus, I have also previously been very heavy in the automation space, especially around RPA, where I built the framework and the technical setup for ISS globally some years back. So I come from an automation background, but actually my major is in history. So I'm not necessarily the tech guy born, but I think I cover a lot of ground. I have a lot of long lines and I try to make sense of everything I know all the time. Larry: And you just mentioned that you're a history major and you're always trying to make sense of things, which leads to how I first discovered you is through your podcast called The Only Constant. And I just love the evocative name that like we're in an age where the only constant is constant change. Can you tell me a little bit about where the podcast came from and how it fits in your practice now? Lasse: So where it came from was basically two things or three things maybe. I wanted to do a p

Gerry McGovern As we navigate our paperless offices and admire our sleek compact computing devices, it can be hard to imagine the impact that our digital experiences are having on our communities and the planet. Gerry McGovern studies the environmental impact of the digital industry. He has uncovered an alarming story of unsustainable growth, toxic side effects, and human misery, which he shares in his book, World Wide Waste. We talked about: how he became an environmental activist focused on the impacts of digital the phenomenal pace of growth of digital infrastructure the impact on local communities of the big data centers that house cloud infrastructure how the compute-intensive nature of AI exacerbates his observation of the long-standing lack of transparency in the AI industry the "snake oil sales" aspects of AI the troubling use of "forever chemicals" by the semiconductor industry the material impact of computer chip manufacturing how human over-consumption and the environmental impacts of AI overlap his advice for actions you can take to mitigate your personal impact: slow down and use your brain more think local - local foods, local computer storage, etc. prefer text over images and other high-bandwidth communications Gerry's bio Gerry’s latest book, World Wide Waste, examines the impact data waste and e-waste are having on the environment and what to do about it. Gerry also developed Top Tasks, a research method used by hundreds of organizations to help identify what truly matters. Connect with Gerry online Mastodon LinkedIn GerryMcGovern.com Video Here’s the video version of our conversation: https://youtu.be/W5-BMTTEUik Podcast intro transcript This is the Content and AI podcast, episode number 23. It's easy to think of digital media and experiences - including our new AI explorations - as ethereal things that magically traverse the computing cloud to enlighten and entertain us. Gerry McGovern is here to remind you that that's far from the case, that "digital is physical." The data centers that power cloud computing are lapping up water and consuming electricity at an alarming pace, and the arrival of AI is accelerating these troubling patterns of overconsumption. Interview transcript Larry: Hi, everyone. Welcome to episode number 23 of the Content + AI podcast. I am really delighted today to welcome to the show Gerry McGovern. Gerry is the author of the book The World Wide Waste: How Digital is Killing the Planet and What to Do About It. He's also probably better known ... and I originally met him almost 15, 20 years ago when he was talking about customer care words, and subsequently out of that arose, I think, his work on top task methodology. So anyhow, Gerry's a well-established figure in the discipline, has a lot of important stuff to tell us about the environmental costs of AI. But welcome, Gerry. Tell the folks a little bit more about what you're up to these days. Gerry: Thank you, Larry. It's lovely to be speaking to you again. I suppose what I'm up to mainly is ... In a sense, I never thought it would happen, but I've become a type of environmental activist focused on the impacts of digital and how to use digital in a better way, in a less damaging way. I don't think digital can be green in any sense, but I think it can be used to help more our environment and at least to reduce the damage it causes to our environment. So, that's the main stuff I'm focused on. Larry: Yeah. Well, I got to say, I love the idea that you're an environmental activist now, because we need plenty of that. But one of the things about your work that I think has really driven home the point to me that we think of digital as this ephemeral thing happening out there in the ether. It's like no consequence. You can just throw stuff in a hard drive or share something. But this is still connected to the physical world, right? Gerry: Absolutely. And the first sentence in The World Wide Waste says, "Digital is physical," and basically, the cloud ... It's on the ground in these mega data centers that are ... They say between now and '27, data centers will add the equivalent electricity demand of a Germany, or perhaps a Japan, of electricity demand to the global electricity network. So it's growing at a phenomenal pace, the quantity of architecture that's out there. It's very, very much physical. Larry: That's just amazing. And one of the things that the people building those giant server farms and things they're good at is, you don't really hear that much about it. They're almost doing reverse PR or something. Gerry: Oh, yeah. It's one of the most secretive, least transparent industries on Earth, and deliberately so. It's all part of the plan. They will never reply to a press call, or very, very rarely. They've become a little bit more in the last, but it&

Mike Atherton Mike Atherton is well-known in the content world for his work at institutions like the BBC and Facebook and for his co-authorship of the influential book Designing Connected Content. His latest content project appears at first to be less serious. Newsbang is a daily AI-produced satirical news show. Its content is based on real historical news but delivered by AI-created stereotypical newscasters. The result is fun, but the process of creating the show has added real-world technical skills to Mike's professional toolkit. We talked about: his work as a UX writer and content designer his experiments with AI tools, including the suite of generative tools he's using to create Newsbang, a completely artificial daily news program how he accomplished his goal of creating an ensemble sketch comedy vibe his workflow for the daily production of the "news" show some of the surprising traits of his news characters that emerged as AI generated them lessons learned about the cost of producing AI programming, like the costs of prompting the variety of models he uses to build the show, including open-source models that have more lenient guard rails to permit more edgy comedic content how he creates his own guardrails to achieve the effect he's looking for in the show while still creating a family-friendly show how he developed the technical skills it takes to create Newsbang how his work with Newsbang helps in his day job his hope that more content professionals will follow him into the AI playground Mike's bio Mike Atherton brings years of experience to the UX, IA, and Content Design field, having tackled content challenges at big names like Meta and the BBC. Now, he's focused on developing UX writing systems, exploring the use of AI to do big things with tiny teams. As well as the day job, Mike is the creative mind behind Newsbang, a daily satirical news podcast that's both written and produced using AI technology. With Carrie Hane, he also wrote the book ‘Designing Connected Content’, sharing strategies for seamless digital experiences. Mike lives in the British countryside and loves working from home. Connect with Mike online LinkedIn Newsbang Video Here’s the video version of our conversation: https://youtu.be/lpDa8szujWo Podcast intro transcript This is the Content and AI podcast, episode number 22. Most of the news coverage and social-media conversations around AI and content feel urgent and important. This is serious business, but you can have fun with this technology, too. Mike Atherton has done content work at places like the BBC and Facebook, and he still does proper content design in his day job. Newsbang, his daily, AI-produced satirical news show, has given him both an outlet for his inner comedian and a venue in which to hone important new work skills. Interview transcript Larry: Hi, everyone. Welcome to episode number 22 of the Content and AI podcast. I am really delighted today to welcome to the show Mike Atherton. You might know Mike, he's probably best known as the... Well, he's best known for a lot of things, but he's worked at the BBC and a lot of other interesting stuff he's done. He co-wrote the book Designing Connected Content with Carrie Hane, which a lot of people in my world appreciate. But he's now a content designer and creative technologist based in the UK. Welcome, Mike. Tell the folks a little bit more about what you're up to these days. Mike: Well, hey, Larry, thanks for having me on. It's great to be back. Yeah, I'm a UX writer and content designer by day. I work with various product teams in different kind of companies to write everything from the microcopy, the words on the buttons, through to taxonomy and control vocabulary and all the good stuff that we UX writers like to do. And as part of that, for the last few years, I've been dabbling with these wicked AI tools that have come our way and seeing what I could do with them to try and make them generate content in a particular voice and tone or in a particular way to fit in with a brand voice or a product voice. And that's really got me interested in the styles of writing and the styles of content that models can generate if you give them the right push. Larry: Yeah, well that's why, I mean, I'm always looking for an excuse to talk to you. But most recently in December, you launched this news site called Newsbang, which is entirely AI generated. And I mean, there's a number of taglines I've heard in it, but one of them is "a taste of truth served with a side of satire,"" and it seems like there's a lot of... But anyhow, there's always to what you were just saying, well, there's so much about this project I want to ask you about. But one of the first things is there's a distinctive tone to it throughout. There's a bunch of different personalities in there, a bunch of different

Elizabeth Beasley As AI is storming into content design and operations, Elizabeth Beasley is taking a patient and deliberate approach to adopting it in her practice. Elizabeth works on security and identity products at Intuit, so the experiences she designs have to be reliable and trustworthy, hence her identification as a "risk nerd." She has also navigated big business changes before, like the shift from cable broadcasting to video streaming, and saw in those transitions the benefits of being a cautious and curious adopter of new technology. We talked about: her role as a content designer working on security, identity, and fraud at Intuit how her background in media and technology have made her a slower adopter of new technology like AI how being a "risk nerd" informs her concern around reliability and trustworthiness in AI how her cautious approach to AI adoption may actually put her in a better position to develop trustworthy AI experiences the new collaborators she is working with as AI arrives on the scene her work on an industry standards body around new security technology the utility of having troops back at the fort to keep the old operations running as your org explores new tech like gen AI how her interest in history informs her approach to change the inherent risks in being first to adopt new technologies her "peaceful Wednesday" practice for preventing and coping with stress and burnout how times of rapid change like this can prompt useful career reflections the recent evolution of her thinking on the "seat at the table" issue Elizabeth's bio Elizabeth Beasley a Senior Content Designer with Intuit’s Identity team. She approaches life with a healthy balance of optimism and skepticism. Because everything is going to be okay, maybe. She used to have hobbies like performing improv comedy and ballroom dancing. Now she enjoys watching other people doing their hobbies on YouTube. Connect with Elizabeth online LinkedIn Video Here’s the video version of our conversation: https://youtu.be/Ny2l_mZgLXQ Podcast intro transcript This is the Content and AI podcast, episode number 21. It's easy to get caught up in the frenetic pace of generative AI technology adoption - unless you have already created rituals to help slow your life down. Elizabeth Beasley created her "peaceful Wednesday" ritual ten years ago to bring some calm to her increasingly fast-paced work life. That practice is serving her well now as she and her colleagues at Intuit develop their approach to incorporating AI tools while continuing to deliver trustworthy experiences. Interview transcript Larry: Hi, everyone. Welcome to episode number 21 of the Content and AI podcast. I am really happy today to welcome to the show Elizabeth Beasley. Elizabeth is a Senior Content Designer at Intuit, the big financial software company. Welcome, Elizabeth. Tell the folks a little bit more about what you're up to these days. Elizabeth: Hey, it's so fun to be here. Yes, I'm at Intuit. Financial services is my life lately, and I've worked in a fun space. I think it's fun, security, identity. I always describe it to my mom or my friends like, I do the part where you create your account, you sign back into your account, you manage your account and I make that easy for you with content design, they still don't quite understand that, but that's the space I work in and I really, surprisingly enjoyed. I worked in banking previously and got into security and now I'm sort of obsessed with security and identity and fraud and it's a fun, exciting space to work, and also I love it because everyone uses it, so it's very relatable and it affects many, many people. So it has a lot of impact. Larry: You can't do anything until you get past that experience that you're designing. Elizabeth: Yeah. Larry: Then you're in and then you can start doing stuff. But you sort of established your cred. You're not like some kind of a Luddite about technology. You clearly, you're deep in it every day doing that, and yet the reason we connected and the reason I wanted to have you on the show is that we connected, I think on LinkedIn, I can't remember exactly how it started, but you're sort of like a slower adopter of AI technologies. And I was like, perfect, I want to get her on the show because every one of the 20 episodes before this were all, and I'm as into it as them, just deep into the technophilia and all the new work things around AI and you're more like, yeah, it's great and you're studying it, you're staying on top of it, but you're not just diving in with both feet, fangirl about it. Tell me a little bit about how that perspective arose. Elizabeth: Yeah, it is, sometimes I feel like I'm behind, but then I'm like, I'm just a late adopter. It's okay. I'm a late bloomer. And I think it

Maaike Groenewege Maaike Groenewege began her content career in technical communication. She is now a leading voice in conversation design for AI. Maaike draws on her technical writing background in her conversational AI practice, having observed that whether you're writing for humans or designing prompts for LLMs, you have to truly understand your audience and consistently provide clear and specific instructions. We talked about: her work over the past couple of years as a prompt designer how the instruction design principles from her days in technical writing and technical communication prepared her for her current role how her early exposure to help desk duties prepared her for the many question-answering responsibilities in her current role how her writing skills, her critical approach to generative AI, and her love of technology combine to give her a unique perspective on conversational gen AI content how retrieval-augmented generation drawing on high-quality content datasets can help set a base level of knowledge for LLMs her opinion that conversational chatbots are a transitory stage on the way to transactional chatbots that can provide self-service problem-solving the workflow for incorporating retrieval-augmented generation into LLMs the similar meaning of the concept of "chunking" in technical communication and LLMs the differences between how LLMs process language and how humans read - and the implications of this for prompt design and engineering the emerging structure for prompts: assigning a role, describing the task, providing a context the differences between conversational prompting, prompt design, and prompt engineering how she works with her engineering partners the difference between the logical inference that knowledge graphs do and the statistical inference that LLMs use how she keeps up with the rapidly changing developments in her field her invention: ALIs, application language interfaces how she uses ChatGPT in voice mode to capture and summarize her thoughts when she's out for a walk her prediction that "the future is bright for those who know how to write" Maaike's bio Maaike Groenewege is a conversation design lead, linguist and prompt designer with her boutique consultancy firm Convocat BV. She coaches both starting and more experienced conversational teams in optimising their conversation design practise, NLU analyses and team communication. Her main focus right now is on how LLMs can benefit enterprise conversational AI. Maaike is the founder of www.convo.club, an online community for more than 700 conversation designers. Connect with Maaike online Convoclub LinkedIn Connect with Maaike at these events European Chatbot and Conversational AI Summit, Edinburgh, March 12-14, 2024 UX Copenhagen, March 20-21, 2024 Unparsed Conference London, June 17-19, 2024 Video Here’s the video version of our conversation: https://youtu.be/3qxxb18BqFM Podcast intro transcript This is the Content and AI podcast, episode number 20. A false dichotomy has arisen in the AI world between conversational prompting in chatbot interfaces and prompt engineering under the hood. Maaike Groenewege works in the middle ground, in a role she calls "prompt design." She also draws on practices from her background in technical communication, after observing that whether you're writing for humans or designing prompts for LLMs, you have to truly understand your audience and always provide clear and specific instructions. Interview transcript Larry: Hey, everyone. Welcome to episode number 20 of the Content + AI podcast. I am super delighted today to welcome to the show Maaike Groenewege. Maaike is ... Well, she's a principal at Convocat, her company, and she's an actual genuine, prompt engineer. So, Maaike, welcome. Tell the folks more about what it's like being a prompt engineer at Convocat. Maaike: Thank you so much for having me, Larry, and it's such a pleasure to be here with you. Yes, I guess that I can say that for the last two years, I've been working as a prompt engineer, or perhaps rather a prompt designer. When I tell people that, they're all going like, "Oh, that must be really sexy," and, "It's the job of the future," whereas, in reality, I basically write instructions for large language models. Maaike: I guess I wouldn't really associate it with being sexy because most of this is very much getting your feet in the dirt kind of work, Excel sheets, lots of analysis, lots of document analysis and content analysis. I guess it's basically a job for ... Well, can I call them language nerds like you and me? Maaike: So, yeah, right now I'm working for a large Dutch publisher. I help them finding out what kind of work we can automate by prompting. It's really interesting. But I've also worked in situations like hyper-automation, where the prompts are not the prompts that you write in C

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, I think it was maybe a few months before the book came out. And since then, I mean conversation had been a thing. I had talked to Phillip Hunter and several other content designers before I had you and Diana on the show, but it seems like I'm going to guess that more has happened in the last four years than in the four years before you wrote the book. Is that accurate? Rebecca: I think that's definitely accurate. Yeah, our book came out in April of 2021, and I think that ChatGPT became publicly available in November of 2022. So our book has been amazingly well received, tons of enthusiasm. It really seems to be sticking around and people are finding it useful. But if you control F and search our book, there is not one mention of the term large language model. And I think there's only one mention of natural language generation. Rebecca: It's been interesting to look at our book through the lens of the fact that te

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 work involved and you're really excited about, and have experimented as much with, the new AI tools. Let's start with the customer and the audience analysis stuff that you do. That was really interesting to me when I read about that. Can you talk a little bit about that? Andy: Sure. If you write a prompt that says draft a blog post of 2,000 words that talks about supply chain ... You're going to get something pretty boring. It's going to be inherently undifferentiated. I joke that AI stands for average information. AI ate the internet. Literally the Common Crawl is 85% of the internet. We know that ChatGPT was trained on the Common Crawl. And it comes back and just gives you vanilla. It tastes like water. Of course it's boring. It's not for anybody. It's generic. All you did was say, write me a blog post. So all of my most successful adventures in AI, and these are daily, begin by teaching it or training it on your target audience. Now, if you've got battle tested, ideal client profi

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 Podcast intro transcript This is the Content and AI podcast, episode number 17. As AI tools arrive in our workplaces, we're discovering that this isn't just another technology adoption cycle. The generative nature of tools like ChatGPT permits rapid iteration on ideas and quicker learning about their impact. For a prototyping strategist like Markus Edgar Hormess adding these AI agents to his service-design teams has been a boon, letting him and his colleagues collaborate and experiment in ways they couldn't have imagined just a few years ago. Interview transcript Larry: Hi, everyone. Welcome to episode number 17 of the Content + AI podcast. I am really happy today to welcome to the show Markus Edgar Hormess. I first met Markus a year ago at a service design workshop in Amsterdam, and we've been talking ever since about getting him on the show. So it's great to finally have you here, Markus. Larry: Markus, he's one of the co-authors of the book This is Service Design Doing. He's real active in the serv

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, copywriting as creative direction. Dan: And then eventually back to the Google data, so SEO copywriting and SEO strategy. And I focused for a while on optimization, research, data analysis for SEO, some technical SEO. And then, yeah, my recent journey has been more in the design world. Content design, content strategy, user experience design. And I'd always been interested in AI and the question was always, how do you do that as a job? Particularly from the position I was coming from as a former student and teacher of poetry and writing. Of course, when ChatGPT came out, like for many people, the connection became clear to me and I started incorporating it immediately into all my work. Dan: I realized that I also needed to brush up on my coding skills, and particularly get more invested in Python. And I took some courses specifically on generative AI and machine learning for that purpose, just to make sure I was prepared. But now I think I'm leaning more into the world of knowledge, thinking about the data that we need for A

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, if we're working in product content, we're used to working with product managers, we're used to working with UX designers, engineers. And that has shifted in that the team that I am partnering with now is made up of engineers and product managers, but we're also working really, really closely with data scientists and we do not have a UX designer or UX researcher on the team right now. So UX content design is really the entire voice of UX in this group, which is really cool. Larry: That's really interesting because often we're the last one in. How does that feel going in there as a sole UX person? Rebecca: It's exciting. It's been a little bit intimidating, but I haven't found myself feeling completely lost or anything. I think it's been great. As we were chatting earlier and you said we're really... We're creating a content product when we're working with these language models. The output is text and language, and so who better could be suited to drive and des

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. Welcome to episode number 14 of the Content and AI podcast. I am really delighted today to welcome to the show Me Habib. May is the CEO and co-founder at Writer, an app many of you're familiar with. They're just having a great year and I was excited to get her on the show towards the end of 2023 to talk about topping the MMLU leaderboard with the Palmyra, their LLM, closed the nice funding round. Sounds like things are going well at Writer, May. May: Oh, thanks Larry. It's so nice to come back and chat with you. Yeah, we've had a great year, thank goodness. I've got our last all-hands of the year after this conversation, and so it was definitely nice to look back. We do these weekly updates to the whole company. I write them, and I went back and looked at week one and compared it to week 52, and then one's like, "Oh, let's go back a little further." I went 2022, week 52, and then 2021, week 52, and yeah, it's awesome to see things build and all the progress. Larry: Yeah. Wel

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 you were doing a year ago? Laura: Yeah, that's a great question. I came up to content design through content strategy and to an extent marketing as well. And so I think for me, it really helped to have that content strategy background, meaning really being familiar with content at scale, content governance. And I think that's been the biggest difference for me, that in my current role, I had to go back to my past and brush up on some of those skills that I think I learned more in the past, versus in my most recent roles as a content designer. I think my day-to-day was still a little bit more writing strings and felt a little bit more like bespoke and... I don't want to say in the moment because of course, ideally it wouldn't be in the moment, but unfortunately sometimes it is in the moment when someone asks you to write a string or edit a string, versus right now I do think my role, it's a lot more focused on the strategy at scale, and I do think it's a function

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, it's more like the tools and the workflows that we use to get our jobs done. So my role is to work on those tools and work on those workflows and make sure it's easy for our writers to get their jobs done in an efficient and easy way so they can create high quality content. And more recently, one of the areas I've been interested in looking into is GenAI and how we might use that to improve our workflows. Larry: Yeah, that's why I wanted to have you on the show. You told me about this product you developed, the Trip Planner, that's based on AI. Can you tell us a little bit about how that project arose and how you got involved with it? Chris: Yeah, definitely. So my involvement with AI and GenAI in general started when ChatGPT came out. I think a lot of people took notice back then. That was late last year, 2022. And I started playing around with it. I'm always a bit of a nerd and early adopter of technology, so I started using it for different things. I have a toddler at home, so I was act

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 and very specific audiences. And since COVID that has risen 50% every year, but when you get deep into the creator economy, they really think about content in terms of workflow and how do you create a process to develop content consistently, and how do you be creative? Lance: Because as a content creator, you have to consistently build content for your community. I stumbled upon AI and I thought, "Well, we're all going to be using this in two years," and here we are. And so I've been exploring then how AI works into the writing process, both in my own content development and also among creators. And then thinking about that in terms of technical writing, content and content management. One of the things that I think content specialists or tech writers have to offer us is a more structured conception of content and how that works into this idea of workflow. I was at a conference, I go to a conference every year in Krakow called SOAP, and last year the topic was content opera

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, I think it was the 30th of November last year, so it's still less than a year old. And when they launched it, I just threw myself in, absorbed as much as I could, created some frameworks, easy ways of being able to teach people, and then I just released these as courses. Dave: I've got now six courses on the platform. Just released another one last week. And I'm about to release some courses on my own website as well. Yes, that's my life these days, doing courses and then helping companies get onto their AI journey in the best possible way because I think a lot of them have got the wrong attitude. They're not looking at AI in the right way. Larry: Yeah, interesting. Tell me more about that, because I think we all have opinions about AI. What are you discovering? Dave: Well, of course, companies, as you know, they will tend to have, "Here's our quarterly target, here's our quarterly goal. Can we make more money and spend less money in this quarter?" That's what they do. It feels as if that's th

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. And then we connected again earlier this year in February. I put together a panel for Tracy Playle, that Utterly Content, about AI. And you were the first person I thought of for that panel, because you've been working with AI tech, and you had been doing stuff at Twitter, and I know you're doing it again at Microsoft. So anyhow, I just want to observe that our relationship over the last year and a half has been a microcosm of all the craziness we're all going through, watching this stuff evolve. Lisa: Yeah, we were just having a casual conversation and things changed. Larry: Tiny bit. Yeah. But the thing that's been a steady across that is your interest in, and use of, AI. I don't know, maybe talk a little bit about the stuff that you and Jordan had done at Twitter, because that was really interesting and promising. Lisa: When I first started at Twitter, one of the things... Because my career started as a tech writer. Then I moved into content strategy, enterprise content stra

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 reviews. We offer a review system management to the customers or shop owners. And for the consumers, we offer a buyer protection. And I'm part of a UX team at Trusted Shops. We are seven designers at the moment. And in the content localization team, we're five people. Claudia: Together, I do the math, we're around 13, 14, 15 people in the UX team. And I'm responsible for the content design craft at Trusted Shops. I jump into, let's say, projects that have a high impact on business, but I am also responsible to develop the craft. That means helping others in the team to write UX copy. One of the things that actually was part of this lately was developing a UX writing body called Piuma. That was one of the projects I worked on it this year. I can tell how we came actually to build Piuma the chatbot. Larry: That's why I wanted to have you on. And also, something you just said, we talked about this a little bit before we went on the air, but your official title is principal content designer at Trusted Shops. And

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 features that include integrations of chat agents and knowledge graph stuff as well as some other stuff. Can you give us a quick overview of that big product announcement that just dropped? Kurt: Yeah, it was huge. Quite honestly, if you're involved in the AI space and have already put something together into a product, the announcement of a couple days ago probably has completely upended any apple cart that you might actually have. There's a whole lot that goes in. Better performance, much bigger context, which is essentially how much information you can send over the wire and how much you can actually refer back to. There is, and I'm pulling this up so if it looks like I'm looking off into the space here, I am, but a whole new Assistants API, new integration with Retrieval, what are called RIGs, and code interpreting, so you can actually define function calls. It now incorporates GPT-4 Vision so

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, you're mostly dealing with franchisees, so somebody who is working with us to build the IKEA brand in a new market. Larry: That's it. And having responsibility for the retail concept of one of the most iconic brands in the world, there's absolutely no pressure in this job, I'm going to guess. Tane: Oh, no pressure. No pressure at all. No. In some way, yes and no. I mean, yes, it's a big task. We are a very big, well-known brand around the world, but in insight when we're working on things, I think we're pretty normal. We talk about pretty normal things day-to-day. I mean, at the moment why I'm here with you today, we talk about things like content and AI and how we can use these to leverage them to improve not only the lives of our customers, they're many people, but also what we do day-to-day. Larry: Great. And that's the thing about AI is it's so sprawling and especially in a big enterprise like Ikea, it's going to be everywhere. Actually, I want to start because where we met, we

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 content, drowning in inefficient content processes. Please help us." That's our typical problem set. Larry: You're the cavalry riding in to save the day. That's great. But I think like anybody in the content world these days, there's this new kid in town, the AI, especially the large language models that are kind of... They seem to be finding their way into every corner of the content world, and the reason I wanted to talk to you is you're probably the first person I thought of when I thought of technical content. What's going on with AI in the technical world? So, a pretty broad question, but we talked a little bit before we went on the air, but I think just the context for how AI is affecting your work. Sarah: First, I'll say that, I mean, people are trying all sorts of things and experimenting and working through what does this look like and what are we doing with it and how are we going to make it work for us? Fundamentally, I think this is going to end up being a pretty straight

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. Noz is an omnichannel strategist at Urbina Consulting, but I know you do a lot of other stuff there too, Noz. Tell the folks what you're up to these days. Noz: Yeah, absolutely. Yeah, as you said, I'm an omnichannel strategist, which involves a lot. It's a lot of customer journey mapping, a lot of stakeholder ecosystems, content modeling, metadata modeling, working with people like ontologists and taxonomists and systems architects to really build full workflows that support omnichannel. Noz: My job is I'm founder and I lead a lot of the projects at Urbina Consulting. I also have founded an organization called OmnichannelX, which was a conference but has been pivoted to a year-round buffet of learning opportunities. We used to do an annual conference, the usual four-day thing. And we found that we weren't going to be able to do physical after COVID. It was just the conference market is too difficult. And we only had one physical conference before COVID, so we never really had a chance to establish ourselves

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 technologies. And for what it's worth, I got into doing graph work, which is how we met, I got into that because of natural language. I was working with a family of algorithms. There's some research that had come out of, basically, taking a raw text and being able to start to put structure into, and turn it into a graph by using natural language. Paco: So we ended up using, like I say, these kinds of technologies, mostly in open-source, for enterprise customers. Really, to help power, help them build applications of knowledge graph, and now large language has become very popular. And, been doing this for a while. Paco: One of the projects I'm involved with, there is an open-source project called Argilla, based in Spain. I'm in Spain right now, actually. We started six years ago in natural language, when some of the first open-source large language models were coming out, LLMLP templates, things like that. Argilla has been doing a lot of those open source integration paths with Spacy and other kinds of NLP proje

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 everybody's background, Dan has been explaining to executives for decades about how to get the most out of computers and computer stuff. And his latest thing - as an AI consultant - is helping people understand where to make smart investments in AI. And so he's been looking for ways to explain that he came up with this brilliant metaphor of the jellyfish and the flatworm. Tell us about that, Dan. Dan: Well, first of all, anybody who's in technology and has an intimate understanding of how bits move across networks and then goes into a room full of executives who maybe have a finance background or a healthcare background but can't visualize the difference between two databases, you can get very quickly frustrated trying to guide them. And one of the things that I've always learned is that if your audience can't visualize what you're trying to explain, they won't make the right decisions. AI today, say your executives are pondering a million

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 players in the AI space like OpenAI, Anthropic, and Google's Deepmind, and show you how to best use their products. Finally, we'll keep on the radar screen the concept of art general intelligence (AGI). But my main intent is to democratize AI technology to help content practitioners understand and use AI as expertly and efficiently as possible (edit: and to help content practitioners working on AI products). We've already seen many ways that AI can help content folks: content creation - relieving the terror of the blank page, tedious outline tasks, research, etc authoring, enterprise UX, auto- and assisted tagging, voice, tone, and style governance, creating content variants, repurposing existing content, etc. strategy formulation content design content engineering content operations AI's going to be able to help us across the span of content practice. No matter what kind of content work you do, you'll soon be using AI in any number of ways (edit: