Summary
Keeping large content repositories organized is an ongoing challenge. There's always new stuff coming in, and taxonomies evolve over time. Resource-strapped teams seldom have opportunities to re-categorize older content. It's a task well-suited for generative AI. Large language models have powerful capabilities that can help teams keep content organized at scale. Using LLMs in this capacity can lead to better user experiences and free team members to focus on more valuable efforts. This presentation explores two approaches for using LLMs to organize content at scale: 1) re-categorizing content using existing categories and 2) developing new categories from existing content. Both will be shown as proofs of concept alongside feasible next steps.
Key Insights
-
•
Maintaining organized large content repositories is often deprioritized despite evolving product portfolios, leading to reduced findability.
-
•
Search alone is insufficient for large repositories because users often lack context about what content exists.
-
•
Evolving taxonomies require periodic retagging of older content to keep it relevant and findable.
-
•
AI, specifically large language models like GPT-4, can automate taxonomy maintenance tasks significantly faster than humans.
-
•
Human oversight is critical to review AI-suggested tags to prevent hallucinations and ensure quality.
-
•
Developing new taxonomies requires analyzing content holistically, which exceeds typical LLM context windows.
-
•
Embedding databases help chunk and relate content statistically for clustering similar topics at scale.
-
•
Graph Retrieval Augmented Generation (Graph RAG) integrates knowledge graphs with LLMs to increase precision by leveraging semantic relationships.
-
•
RAG enables querying domain-specific content unseen by generic LLM training data, supporting bespoke AI assistants.
-
•
AI tools enable higher speed and new methods for content work but require new workflows and ongoing experimentation.
Notable Quotes
"Keeping large content repositories organized is an ongoing challenge that often gets deprioritized."
"Search alone doesn’t cut it, particularly when people don’t know what they’re looking for or lack context."
"If organizations don’t keep content organized, it becomes less usable and less useful over time."
"Large language models can help organize content faster and at much larger scale than people can."
"I used GPT-4 to retag 1,200 blog posts, reducing an estimated 10–12 hours of tedious manual work to about a third of that time."
"I made sure the LLM would only use terms from my predefined taxonomy, but it still introduced some of its own tags."
"Working with these tools requires new workflows and checkpoints to validate and tweak the AI's output."
"Graph RAG uses knowledge graphs instead of just plain text snippets, which really improves precision."
"I see these AI tools as augmenting human work, letting us focus on what matters most, not replacing humans."
"The best way to understand these technologies is to learn them hands-on, especially if your work involves language or taxonomies."
Or choose a question:
More Videos
"We went very, very big instead of an annoying side project; it became the core of our research systems."
Elizabeth Sklar Jessica ShengCo-creating research enablement with your tech org: a case study
March 10, 2026
"Metrics are always a conversation, they shouldn’t be a covenant."
Saara Kamppari-Miller Nicole Bergstrom Shashi JainKey Metrics: Comparing Three Letter Acronym Metrics That Include the Word “Key”
November 13, 2024
"Human-centered design is not just about your end users, it’s about the humans in your team."
Gretchen AndersonScaling the Human Center
June 8, 2017
"We had to charge not just project work but all the costs including vacation, rent, insurance, and bookkeeping."
Chelsea MauldinLet's Talk About Money
November 17, 2022
"Growth in your career doesn’t always have to be vertical; sometimes sideways or diagonal moves help you stay true to yourself."
Lada GorlenkoTheme 3: Introduction
June 10, 2021
"If you design for everyone, no one is satisfied — start with specific solutions then generalize."
Craig VillamorResilient Enterprise Design
June 8, 2017
"We had passed through this awkward moment. I felt I had rudely probed into this open wound."
Susan Simon-DanielsWar Stories LIVE! Susan Simon-Daniels
March 30, 2020
"Building coalitions and embedding research insights within the culture is essential for long-term impact."
Robin BeersBeyond Insights: Researchers as Organizational Change Catalysts
March 25, 2024
"Design requires teams because you can't be expert in everything—from pixels to hardware to databases."
Paul Pangaro, PhDSystems Disciplines: Table Stakes for 21st Century Organizations
June 6, 2023
