Maaike Groenewege: From Technical Writing to Prompt Design Leadership – Episode 20

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 ChatGPT, but they are part of a larger workflow. For instance, a workflow where you receive an email, you want to have a first suggestion for an answer, you generate that text, you put it in an email again, or perhaps in a phone call. So it's not really visible, but it's definitely there in the background. Larry: Oh, interesting. Yeah. Well, you've done so much. I guess, first, let me ... Can you do a quick job description for what a prompt engineer does? Maaike: Absolutely. Larry: You just outlined the main duties, like... Maaike: Yeah, yeah. Larry: But what does that look like day-to-day? What's your new job? Maaike: My new job ... And it's so funny because it's actually my old job. I feel I'm back to technical writing and technical communication again, because in order to write a good prompt for a machine, I actually apply the same principles that I use for prompting humans, instruction design. So basically ... Maaike: Let's take a situation, like a real-life situation. This is not from my actual client, but it was an assignment I once got. It came from a developer. He's quite well-known in the space. He's like, "Maaike, listen. I need to prompt a newsletter or a one-pager for three different audiences, and it should be based on two or three articles from the news, from actual news, about LLMs and machine learning." He's like, "Well, I prompted it and I must say that the output is meh." I looked at this prompt, it was literally like, "Hey, generate a newsletter." Maaike: I'm like, well, when I would tell a junior editor to create a newsletter, I would give him more instructions. I would tell him something about my target audience. Who is it for? What are the information needs? What is their level of expertise? Because technical writing 101, don't write for your own level of understanding, but make sure you understand your target audience. Maaike: So it was so funny because prompt engineering is positioned as a rather technical job sometimes or a very marketing job. But my job is right in the middle. So what I do is I do a lot of domain analysis. I need to know who I'm working for, and in order to determine the information need of my target audience, I, of course, need to know a little bit of what they're doing. Maaike: I do target audience analysis, user task analysis, all kinds of stuff. Then when I write my prompt, I do find I write it in the form of a traditional instruction, and that, of course, is one. I've been doing that for 25 years. So it's almost like being full circle back into the place I never left in the first place, because even as a conversation designer, I still feel very much ... At heart, I'm always a technical writer because I always support users in completing their tasks successfully or answering questions, solving problems, and these are just new incarnations, I guess, of that job. Larry: As you talk about your background and where you are now, I'm reminded that everybody in content design, conversation design, technical writing, I mean technical writing seems to be like that's the most straightforward one. People often study that in college and then go actually do it. But everybody else, the conversation designers and content designers and UX writers I know, they all come from some crazy amalgam of careers and backgrounds. In your case, it just seems like the perfect storm of that technical writing plus conversation design. Larry: I guess tell me, because, well, you first came to my attention a few years ago as a really prominent and well-known and well-regarded and super-helpful content and conversation designer, and these new agents we're working with, the chatbots and GPTs all that stuff, they're all conversationally based things. Does my idea that you're perfectly positioned for that, does that resonate? Did you feel like this has just come really naturally, or- Maaike: Yes, and it's interesting because when I started as a technical writer, I wasn't even aware that that was a formal job. It was in the early 2000s. So little trip down memory lane, it was the time of a news group called Tech Role where people like me gathered. I was what we call the lone technical writer at the company. So I basically invented my own job. Maaike: I found that I just got really fascinated, especially by how people ask their questions. I also spent some time at the help desk at the same company where I started as a tech writer. The way people ask questions, it can be so completely different from what you think they want to do, and that's what started to fascinate me throughout my career. Maaike: With conversation design, 20 years later, I felt like I had won the lottery because, for the first time, we got our user questions handed to us on a silver plate, because especially if you create a chatbot with natural language understanding, you get the literal questions from your users. This, of course, as a technical writer. Maaike: Well,