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Summary
What happens when you cross an eager librarian, a happy puppy, and 800 UX experts? You get the Rosenbot—Rosenfeld's new GPT-4 level chatbot, trained on our books and hundreds of hours of conference and community call recordings. What went into creating the Rosenbot? Lou is joined by SimplyPut's Peter van Dijck, an old friend from the IA community and the chief architect of the Rosenbot. If you're beginning your journey into developing generative AI products, you'll want to join Lou and Peter to learn from their lessons, ask questions, and share your own thoughts on AI's role in making curated content more useful and impactful.
Key Insights
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The Rosen bot uses curated, high-quality content from Rosenfeld Media to avoid common pitfalls of enterprise chatbots operating on messy internal data.
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Significant project resources, around 30-50%, must be devoted to evaluation combining user tests, expert reviews, and repeatable automated metrics.
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The chatbot intentionally avoids summarizing entire books to prevent cannibalizing book sales, instead acting as an entry point to authors’ original work.
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Users and researchers often don’t know how they will use AI tools initially; the use cases evolve through interaction with the technology.
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Building AI conversational agents requires embedding follow-up questions and memory simulation into the interaction design beyond a basic large language model.
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Semantic search and topic analytics behind the scenes enable insights about conversation content trends and authors' influence in real time.
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Balancing fresh, current content with older foundational material is challenging since methodologies and societal norms continually evolve.
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There is a tension between jumping in to build and learn quickly versus cautious, deliberate product development; both parties in the talk appreciate different approaches.
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Interactive UI elements like expandable answers and filters for broadening or narrowing responses are planned to enhance the conversational interface.
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The Rosen bot acts as a creative companion and research assistant, helping accelerate idea exploration and uncover relevant historic knowledge efficiently.
Notable Quotes
"If you don’t jump in and learn, you’ll spend your time reading stuff on it and not really understand the tech."
"People forget the expertise every seven years and have to learn everything again—this bot helps make that expertise accessible."
"The content behind this bot is curated and high quality, unlike the typical confusing, outdated information in corporate repositories."
"We devote 30 to 50 percent of the project time just on evaluation with real users and experts to ensure quality and safety."
"The bot doesn’t summarize books because we’re a publisher and don’t want to cannibalize book sales—it points users to the original sources."
"We’re building in the attribution of ideas to authors and speakers, emphasizing the humans behind the expertise."
"Chatbots aren’t just the language model—they have structure around intent classification, safety checks, and session memory simulation."
"Sometimes you have to build stuff and learn from it rather than wait for the perfect moment or tools."
"AI in design can act as a creative companion, helping explore ideas and analyze past research more efficiently."
"The product is imperfect, probably about 60 percent there, but if we get to 80 percent it will be a compelling tool for UX content."
Dig deeper—ask the Rosenbot:
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