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Tom Johnson
Senior Technical Writer at Google
Tom Johnson is a senior technical writer currently working at Google in the Seattle area.12 He has an extensive background in technical writing and documentation, particularly focusing on API documentation and developer-related content.
Career Highlights
Tom joined Google in November 2020, where he works on developer documentation for Google Maps APIs, specifically for automotive partners integrating map data into their vehicles.2 Prior to Google, he held several notable positions:
- Senior Technical Writer at Amazon (June 2018 - November 2020)
- Technical Writer at Amazon (February 2016 - June 2018)
- Senior Technical Writer at Experian / 41st Parameter (June 2014 - February 2016)
- Technical Writer at Badgeville (March 2013 - June 2014)
Expertise and Contributions
Tom is well-known in the technical writing community for his blog "I'd Rather Be Writing" (idratherbewriting.com), where he regularly writes about topics related to technical writing and communication.1 Some of his focus areas include:
- API documentation
- Technical communication trends
- Information usability
- Tech comm careers
- Processes for managing documentation
He has also created a popular API documentation course, which is one of the most visited sections of his website.1
Educational Background
Tom earned his undergraduate degree in English from Brigham Young University. He also holds an MFA in Literary Nonfiction Writing, which he completed between 1999 and 2002.3
Personal Life
Tom is married with four children. He met his wife Shannon at BYU in the Writing Fellows program, as they were both English majors.1
Tom Johnson's extensive experience, popular blog, and contributions to the field of technical writing have made him a respected figure in the technical communication community.
Highlights
I created a handful of short videos on prompt engineering for docs techniques here:
- Podcast: Creating high-fidelity, thematically organized notes from engineering meetings using AI: https://lnkd.in/gFfEaZYe
- Podcast: Gathering source material for context input: https://lnkd.in/gdMqSXhy
- Podcast: Populating documentation templates using AI: https://lnkd.in/gGx-r3Db
- Podcast: Using file diffs for better release notes in reference docs: https://lnkd.in/gz4AzbFK
- Podcast: Using long-token contexts to quality check an entire API doc set: https://lnkd.in/g5h2d7Jq
- Podcast: Task decomposition and complex tree diagrams: https://lnkd.in/g6GUqZkM
#promptengineering #ai #techcomm #technicalwriting
New post: Using long-token contexts to quality check an entire API doc set
One of the advantages of recent Gen AI updates is the massive token input context. When you can pass in an entire set of documentation as an input, you have a much stronger possibility for powerful prompts. In these prompts, the reference docs can serve as a key source of truth. User guide content and drift out of date, but a freshly generated reference doc should be accurate to the code base, for the most part. From this source of truth, you can do all sorts of things, such as identify outdated content in the user guide, see what's new between outputs, get links in your release notes, and more. In this article, I share 8 quality control prompts you can use when passing in your entire reference docs. Read more: https://lnkd.in/gBgUqKmc #ai #technicalwriting #documentation
