Fawn has over 25 years of experience working in technical documentation. Over the past decade, she has led large documentation teams for a variety of companies, from Fortune 100s and to Start Ups. Over the years, Fawn has led teams that have specialized in content strategy, content creation, information architecture, contextual help, in-code documentation, data science, visual design, interactive design, and content design. Right now, Fawn is a senior leader at Meta. Her teams lead content strategy and creation for Meta’s AI, ML, and Data Infrastructure groups. Fawn lives in Santa Cruz, California, with her children, two (pet) rats, and two dogs. When she’s not working, she enjoys spending time with her family, meditating, doing jiu jitsu, and telling dad jokes.
Case Study: Experiments in Using AI for Content Personalization and Writer Efficiency
There is no doubt Large Language Models (LLMs) such as Meta’s LLaMa or Open AI’s ChatGPT, will forever change how we work. It’s close to impossible to know exactly how our field will change, but change is coming. It’s time to turn toward these new, amazing technologies. In this session I will show a couple of the ways that Meta’s Doc Engineers have leveraged LLMs and AI. See how you, too, can embrace these new, amazing technologies and in doing so increase your overall efficiency and help shape the evolution of our craft.
In this session attendees will learn:
- At a high level, about Large Language Models (LLMs), such as Meta’s LLaMA or Open AI’s ChatGPT
- How to leverage LLMs to write more efficiently
- How to use LLMs to create personalized content for end users
- How to deeply engage with, and help influence, AI’s role in the future of technical communications