Although I don’t work in road ecology or traffic engineering, the author somehow pulled me through 300 pages on this topic. He managed this not just through vivid language and diction, but by personally visiting places and telling stories about the specific challenges that animals, “carers,” forest service workers, and others faced as freeways and highways bisected and dissected their environments.
To use an analogy, suppose you’re a barista making espresso coffee. An AGI-capable robot trained as a barista is able to make all the coffee that a regular barista can make but twice as fast. Further, the Android barista can create exquisite espresso art in any shape that humans request, wowing them and making the experience novel. Soon the human barista is replaced. After all, the paying customer would rather pay $2.50 for a robot to make a latte instead of $5.00, especially when it tastes the same.
Most code samples in documentation are fairly basic, which is by design. Documentation tries to show the most common use of the API, not advanced scenarios for an enterprise-grade app whose complexity would easily overwhelm developers. (At that point, you end up with a sample app.)
With AI tools built directly into your authoring tool or IDE (such as VS Code), fixing simple doc bugs can become a mechanical, click-button task. Here’s the approach to fixing simple doc bugs:
(Note: The fact that I’m writing a book review on this topic might seem odd given that I usually focus on tech comm topics. However, I document APIs for getting map data into cars, so I sometimes read books related to the automotive and transportation domain. I also run a book club at work focused on these books.)
During the past few weeks, I’ve felt like my brain’s RPMs have been in the red zone. Granted, the constant stream of chaotic political news hasn’t helped—but regardless of current political events, I’m frequently checking the news, my email, and chat messages and operating in a mode that isn’t great. Reading long-form books has proven to be difficult. I run a book club at work focused on automotive and transportation books, and it took me two months to make it through a single book (granted, it was a 300-page historically dense book, but still).
“Biohacking” might be a pretentious cyber term for what is otherwise a straightforward experiment. For 10 days, I tracked my food and exercise levels while also wearing a continuous glucose monitor (CGM) to track my glucose levels. I then used AI to pair up the food + exercise with the glucose readings and perform an analysis about triggers for glucose spikes and recommendations to avoid them.
I want you to act as my AI stream journal (similar to a bullet journal), for the day. In this chat session, I’ll log 3 kinds of notes: tasks, thoughts, and events. Tasks are to-do list items. Thoughts are random ideas or notes I have. Events consist of food eaten, exercise, or descriptions of my internal states. The point is to have an easy way to dump all the scattered information in my head into a central log that you organize and analyze on my behalf.
Rather than approach the topic of publishing prescriptively, let’s begin with some concrete examples and move towards the formulation of general principles. The following are more than 100 openly accessible REST APIs that you can browse as a way to look at patterns and examples.
Browse a few of these documentation sites to get a sense of the variety, but also try to identify common patterns. In this list, I include not only impressively designed docs but also docs that look like they were created by a department intern just learning HTML. The variety in the list demonstrates the many options for publishing tools and approaches, as well as terminology. It seems that almost everyone does their API docs their own way, with their own site, branding, organization, and style.
Tip: If any of the links fail, just type {product} + api docs into Google’s search, you will likely find the company’s developer doc site. Most commonly, the API docs are at developer.{company}.com.
Activity: Look for common patterns in API doc sites
In this activity, identify common patterns in API documentation sites.
Select about three different APIs (choose any of those listed on the page).
Look for several patterns or commonalities among the API doc sites. For example, you might look for any of the following patterns:
Structure and templates
Seamless branding (between docs and the marketing site)
Abundant code samples and syntax highlighting
Lengthy pages
API Interactivity (such as an API Explorer)
Docs as code tooling
Note any non-patterns, such as the following:
PDF
Translation
Video tutorials
Commenting features
Multiple outputs by role
Make some notes in an API log or journal (or share them in the comments below).
In the next section, we’ll look at Design patterns with API doc sites. From your notes, look to see if the patterns I highlight match the ones you observed in the API doc sites you analyzed.
About Tom Johnson
I'm an API technical writer based in the Seattle area. On this blog, I write about topics related to technical writing and communication — such as software documentation, API documentation, AI, information architecture, content strategy, writing processes, plain language, tech comm careers, and more. Check out my API documentation course if you're looking for more info about documenting APIs. Or see my posts on AI and AI course section for more on the latest in AI and tech comm.
If you're a technical writer and want to keep on top of the latest trends in the tech comm, be sure to subscribe to email updates below. You can also learn more about me or contact me. Finally, note that the opinions I express on my blog are my own points of view, not that of my employer.
