Shane Newman is a strategic innovator in technology and analytics with extensive experience at Splunk and Red Hat, where he led initiatives to redefine infrastructure, application, and business service management through monitoring and analytics. One of his most recent projects has been using ChatGPT to significantly augment and enhance the knowledge base within the platform domain of Lantern. Through this work, he has partnered with the Splunk Lantern team to identify areas where documentation is lacking or could be improved, ensuring the knowledge base remains dynamic, comprehensive, and up-to-date. He believes this approach is making significant strides in enhancing the overall user experience, demonstrating the potential of AI-human collaboration in content creation and knowledge management.
The Beauty and the Beast: A Relationship with ChatGPT
Co-presented with: Jennifer Swallow
For many content creators, ChatGPT is a Beast, a looming monster threatening to take away the livelihoods of the Beauties, the highly-skilled knowledge workers. Yet we can’t avoid it. We are being forced to confront it head-on. Rather than allow it to imprison us, what if we lean into what it has to offer? What prince might we find hidden beneath the scary surface? This talk is a case study on how a crowdsourced knowledge base, Splunk Lantern, is using articles generated through a custom AI model to provide more self-service content to customers. Using ChatGPT for first drafts allows both the contributors and the content management team to build out content faster to support more Splunk programs and answer more customer questions. But the process hasn’t been without its challenges. Just as Belle and the Beast had a few false starts while they tried to understand each other, so too has working with ChatGPT been an iterative process. But the result is a benefit to Splunk Lantern users and Splunk customers as a whole.
In this session, attendees will learn:
1. How to create an AI model that uses the company’s public-facing docs to generate new content based on a specific outline
2. What human editors caught while editing
- Grammar and style issues
- Wordiness and nonsense phrases
- Content organization challenges
3. How the process to retrain the model based on editorial feedback worked (and didn’t work)
4. What benefit this AI/human partnership is bringing to the company
- Enhanced content quality and efficiency
- Improved knowledge management strategy
- Better support and user experience through targeted self-help articles
