Matthew Baldwin - Read the Rules: What technical writers can learn from board game design
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Treat rulebooks as unpatchable instruction sets: design for correctness and clarity before shipping.
Briefing
Board game rules are a high-stakes form of technical writing because they’re effectively “unpatchable” once printed: if a rule is unclear or missing, players can’t experiment their way to the answer and the game won’t work until the rulebook is fixed. That makes rulebooks a useful model for documentation work, since the rules function like an algorithm executed by people—where the “platform” is the reader and the “program” is the step-by-step instructions. Matthew Baldwin, a content developer at Microsoft and a longtime board game enthusiast, argues that technical writers can borrow board game rule design principles—especially information architecture and usability best practices—to make complex systems easier to learn, navigate, and trust.
His first focus is information architecture, using Wingspan as the centerpiece example. The rulebook splits content into a main “how to play” guide plus an appendix reference, so readers get a guided learning path without being forced to wade through every edge case up front. Wingspan also teaches from general to specific: it starts with a short, theme-flavored introduction that still communicates concrete learning goals (what players do, what resources exist, and how points are earned), then provides an overview of turn structure and round flow, and only then drills into the details of each action (play a bird, gain food, lay eggs, draw cards) and bird powers. Baldwin highlights how this structure creates “bounds” in the reader’s mind—like assembling puzzle edges first—so later details have a clear place to land.
Navigation and scanability get treated as design requirements, not afterthoughts. Wingspan’s sections use clear headers, images, and whitespace, with nonessential notes visually separated so readers can ignore them when they’re focused on playing. The appendix acts as a just-in-time reference when a card interaction isn’t obvious, mirroring how good technical documentation separates conceptual explanations from dense reference material.
In the second half, Baldwin offers a “laundry list” of rulebook best practices that translate to documentation. People learn by doing, so step-by-step setup pages and “quick start” style instructions work better than passive reading. Clear language beats branded jargon: calling hexagons “squares” (or renaming familiar concepts like a draw deck) may feel clever but causes forgetting and confusion later. Consistency matters: define terms once and use them exclusively, which also reduces localization burden. Images and examples improve comprehension—especially for setup—while overusing screenshots can create maintenance problems. He also recommends flagging frequently missed steps, using consistent layouts via templates, and tailoring the writing style to the audience (war gamers may tolerate numbered, versioned structures; role-playing fans may prefer more narrative prose). Accessibility shows up in practical choices like icons for color-blind readers and second-person writing that avoids gendered pronouns.
Finally, Baldwin stresses validation: designers should run blind play tests where people learn from the rulebook alone, revealing omissions that experts overlook. After release, feedback loops matter too. He points to Tapestry’s self-reported gameplay data, which led to balancing patches, and argues technical teams should similarly monitor support signals and verbatims to patch documentation experiences before customers struggle. In short: rulebooks succeed when they teach effectively, navigate cleanly, use consistent terminology, and continuously improve based on real user friction.
Cornell Notes
Board game rules work like a form of technical documentation where the “program” is executed by people, and the stakes are immediate: unclear or missing rules can’t be patched after printing. Baldwin uses Wingspan to show how strong information architecture—general-to-specific teaching, a separate reference appendix, and scan-friendly layout—helps readers learn without getting lost. He then lists documentation tactics drawn from rulebooks: teach by doing, use familiar language, define terms once and reuse them consistently, add images and examples, and call out steps people commonly miss. He also emphasizes blind play testing before release and using feedback data afterward to improve the experience.
Why does Baldwin treat board game rulebooks as “quintessential” technical writing?
How does Wingspan’s rulebook structure reduce reader confusion?
What does “customer intent” mean in this context, and how does it shape the writing?
Why does Baldwin warn against renaming familiar concepts (like “draw deck”)?
What practices improve consistency and localization outcomes?
How should documentation teams validate and then improve after release?
Review Questions
- Which parts of Wingspan’s rulebook are designed for learning versus quick reference, and what problem does that separation solve?
- Give two examples of how terminology choices (e.g., branded names vs clear terms) can affect reader comprehension months later.
- What would a “blind play test” look like for a technical documentation draft, and what kinds of issues would it likely reveal?
Key Points
- 1
Treat rulebooks as unpatchable instruction sets: design for correctness and clarity before shipping.
- 2
Use information architecture that teaches general concepts first, then provides structured details that fit the reader’s mental model.
- 3
Separate conceptual documentation from dense reference material so readers can learn quickly without losing time.
- 4
Write in clear, customer-recognized language; avoid jargon or thematic renaming that increases recall costs.
- 5
Define terms once and reuse them consistently to prevent ambiguity and reduce localization complexity.
- 6
Improve scanability with consistent layouts, headers, whitespace, and visual separation of optional notes.
- 7
Validate with blind play tests and improve post-release using support signals and user feedback data.