Chapters 1–4
Working with sources
Understand the approach, the workspace, history, and readable source files.
The living tutorial & engineering lab
Document-as-Code
From static documents to information we can work with.
Document-as-Code applies software engineering practices to the management of information. Sources are maintained in readable formats, changes are versioned and reviewed, and automated processes can validate, transform, and publish the information.
From sources to results
Maintain once. Use in different ways.
By separating information from how it is presented, the same maintained sources can support documents, websites, dashboards, visualizations, AI workflows, and other applications.
Maintain
Readable sources and clear ownership
Review
Proposed changes and recorded decisions
Process
Explicit checks and selection rules
Reuse & transform
Shape information for its audience
Possible outputs
DocumentsWebsitesDashboardsDiagramsAI contextPresentations
Review and processing can repeat as sources change. Choose the rules and outputs each task needs; no single tool or strictly linear workflow is required.
Why it matters
More confidence in the information
Inspect changes, identify responsible owners, and connect results to the sources that produced them. Checks support review; they do not replace it.
Less repeated work
Reuse shared information and automate repeatable checks and publication, instead of maintaining independent copies.
Richer uses for the same sources
Connect records, create useful views, and provide AI tools with selected context that people can inspect and review.
11 chapters · Read in sequence or explore a topic
Choose a learning path
Chapters 5–7
Making information processable
Add metadata, meaningful relationships, validation, and repeatable processing.
Chapters 8–9
Using information in new ways
Prepare project knowledge for agents and explore connected information.
Chapters 10–11
Making it a working environment
Automate checks and publication, inspect the lab architecture, and compare environments.
Explore the working lab
The tutorial uses this repository as a working example. Try a focused exercise or inspect the project's recorded activity.
- Choose content for a handbook
Browser-only simulation · Compare inclusion rules against fictional source review states.
- Edit Markdown and see the result
Browser-only practice · Edit headings, lists, and a table. Changes are not saved.
- Validate procedure metadata
Browser-only practice · Check YAML fields against a visible schema. Passing is not approval.
- Explore customer projects and agreements
Fictional records · Explore relationships, delivery commitments, and change-impact review candidates.
- Trace an output to its sources
Repository architecture · Compare the sources, processing, results, and update triggers for five outputs.
- Explore a spreadsheet-style view
Fictional fixed dataset · Sort and filter a department budget using CSSV.
- Open the Project Control Center
Growth measured at build time · Operational snapshots refreshed on deployment and hourly, with retrieval times. Optional live retrieval is separate.
Each chapter also includes a short practice quiz. Fictional example statuses do not constitute operational approval.
Present and share
Explore how the approach works, when its benefits justify the change, and how this lab puts it into practice.
Behind the Lab: From Sources to Experience
A guided tour of the Document-as-Code Lab: Markdown, Astro, GitHub, GitHub Pages, interactive components, presentations, and an alternative Microsoft 365 approach.
9 slides · Speaker notes
Document-as-Code: Rethinking How We Work with Information
For engineers and practitioners: maintained sources, metadata, relationships, review, processing, and AI context.
10 slides · Speaker notes
Why Document-as-Code? From Document Production to Information Value
For leaders and teams: where reuse, review, traceability, and AI can help, and what adoption requires.
10 slides · Speaker notes