To use AI for fact checking, AI tools might do better with a complete, self-contained set of documentation to check against a reference. Single-sourcing, with its conditional and fragmented content, complicates this model.
In this experiment, I try to implement a loop of recursive self improvement on an essay, but it fails.
I'm starting a new series describing the various AI experiements I do. I've been looking for my next area of focus, and I realized that more than anything else, I like experimenting with new tools, techniqes, ideas, etc. So I'm writing a series of posts called AI experiments.
In my prompt engineering series, I added an article exploring how API quick reference guides (QRGs) can improve developer usability and also augment AI chat sessions with much-needed context. These QRGs are structured as hierarchical tree diagrams providing a visual map to complex APIs. The diagrams make it easier for developers to navigate and understand relationships between elements compared to traditional flat reference documentation. The article also includes a step-by-step process for creating these QRGs using AI.
This post describes the key arguments and themes in The Coming Wave: AI, Power, and Our Future, by Mustafa Suleyman, for the AI Book Club: A Human in the Loop. This post not only breaks down the logic but also jumps off into some themes (beyond the book) that might be more tech-writer relevant, such as potential future job titles, areas of focus for tech writers to thrive now, questions for discussion, and more. It also contains the book club recording.
This post captures some of my reflections on attending the 2025 Write the Docs conference in Portland. Some themes I discuss include the paradox of AI fatigue, the delight and difficulty of unconference sessions, why lightning talk formats are so challenging, and more.
In this Q&A with Fabrice Lacroix, founder of Fluid Topics, I ask him questions about his recent tcworld article in which he argues for an innovative, advanced model for Enterprise Knowledge Platforms (EKPs) acting as a central AI-powered brain for all company content, delivered via APIs. Fabrice also outlines a future where tech writers become information architects, governing vast knowledge ecosystems and coaching diverse content contributors.
In this post, I share my enthusiasm for API quick reference diagrams, which have significantly improved user comprehension and findability in our API documentation. I also explore how these diagrams serve as informative, low-token context for AI tools, enhancing their understanding of API structures (especially when accompanied with reference documentation) and how they counter hallucination in AI outputs. Finally, I end with a short tutorial on how to create these diagrams using AI.
In this post, I argue that technical writers should actively challenge ideas they find problematic, drawing inspiration from Jonathan Rauch's The Constitution of Knowledge. Rauch argues that truth arises from social debate and critique. Taking it a step further, we should listen to internal red flags or intuition when something feels amiss, even if the reasons aren't immediately clear. When direct confrontation is challenging, use open-ended, clarifying questions to investigate concerns and collaboratively explore issues.
Today was one of those days where I felt like I've seen the future. In about a day and a half, I used AI to create 8 different tree diagrams for APIs in an SDK I support. Each tree diagram has varying numbers of elements (from 50 to 350+). The tree diagrams visually depict the API structure and hierarchy, showing the data type, required/optional status, and sometimes other details. Each element links to its specific section in the reference documentation.
I recently added Document360 for API docs to my Chapter 4: OpenAPI spec and generated reference docs in my API doc site. Document360 lets you publish API reference documentation from OpenAPI specification files. Importantly, it lets you integrate this API reference content smoothly with your broader knowledge base and regular documentation, all within a single portal. The platform supports various import methods for OpenAPI files (versions 3.1, 3.0, 2.0) and Postman Collections, focusing on the publishing aspect rather than OpenAPI authoring (which I feel is a smart move to avoid unnecessary UI complexity).
This post has notes and questions for discussion for More Than Words: How to Think About Writing in the Age of AI, published in February 2025 by Jonathan Warner. Warner's book, which explores what we lose when we outsource writing to AI, is the first book in the AI Book Club: A Human in the Loop.
Jonathan Warner's book More Than Words: How to Think about Writing in the Age of AI is a spirited defense about the value and humanity of writing without AI at a time when AI promises to replace many writing activities. Warner argues that writing involves thinking and feeling, and as we grapple with ways to identify, express, and articulate our ideas in writing, it's an experience that changes who we are.
Crossings: How Road Ecology is Shaping the Future of Our Planet, by Ben Goldfarb, is a richly descriptive work of investigative journalism exploring the topic of road ecology, which looks at how roads impact their surrounding environment. More specifically, road ecology is "'the study of how 'life change[s] for plants and animals with a road and traffic nearby'" (6).
I'm starting an book club called AI Book Club: A Human in the Loop. As you might expect, the book club involves reading and discussing books about AI on a regular basis. The book club will meet online, currently planned for the third Sunday of each month at 10 am Pacific Time (Seattle's time zone). There are some async chat options through Slack as well, and we'll record the meetings. Check it out at AI Book Club: A Human in the Loop. If you've been looking to read more (or get back into reading) while also increasing your understanding of AI, this club could be a good fit.
