> Markdown twin of https://adna.network/use-cases/educator/
> Index: https://adna.network/llms.txt · Full corpus: https://adna.network/llms-full.txt
> State is a build-time snapshot generated 2026-08-30 (UTC); nothing here is live.

# Educator — aDNA Use Cases

## Meet Prof. Sarah Kim

Sarah teaches a graduate course on AI-augmented knowledge work at a research university. Her students come from diverse backgrounds — computer science, biology, business, humanities. She needs a framework that's rigorous enough for the CS students and accessible enough for the humanities students.

## The Challenge

Teaching "how to work with AI agents" is hard because there's no standard curriculum. Every tool has its own approach. Students learn prompting techniques but not knowledge architecture — they can ask an AI a good question but can't organize their project so the AI gives consistently good answers. Sarah wants to teach the structural layer, not just the interaction layer.

## How aDNA Helps

Sarah uses aDNA itself as the teaching tool. Students don't just read about knowledge architecture — they build one. The course vault is both the syllabus and the subject.

**Week 1-3**: Students navigate this vault (aDNA.aDNA/), reading concept files and following the beginner tutorials. They learn the triad, governance files, and the question test by seeing them in action.

**Week 4-6**: Students fork the base template and create their own project vault. They extend the ontology for their thesis domain, write context files, and experience how structure improves agent output.

**Week 7-9**: Students run a mini-campaign — 3 missions, each with deliverables. They practice mission decomposition, session tracking, and AARs.

**Week 10**: Students present their vaults. The dual-audience principle is the grading rubric — a non-expert should be able to navigate the vault and understand the domain.

## What Their Vault Looks Like

```
# Course vault (shared reference):
ai_literacy_course.aDNA/
├── what/
│   ├── context/         # Readings, research summaries
│   ├── concepts/        # Student-authored concept files
│   └── assignments/     # [EXT] Assignment specifications
├── how/
│   ├── campaigns/       # Course syllabus as a campaign
│   ├── missions/        # Weekly assignments as missions
│   ├── sessions/        # Student work logs
│   └── templates/       # Assignment templates
└── who/
    ├── governance/      # Course policies, grading rubric
    └── team/            # Student roster, office hours

# Each student also has:
student_thesis.aDNA/     # Individual project vault
```

## Outcome

Students leave the course able to structure knowledge for AI agents — not just prompt them. The dual-audience principle improves their writing across all contexts. Several students adopt aDNA for their thesis work. The course vault itself becomes a growing knowledge resource maintained across cohorts.

## Typical Ontology Extensions

| Entity | Triad | Purpose |
|--------|-------|---------|
| `assignment` | how/ | Assignment specifications with rubrics and deadlines |
| `student_project` | what/ | Registry of student vault forks with progress tracking |
| `reading` | what/ | Course readings with discussion prompts |

## The teaching kit

A 3-week curriculum: nine tutorials in pedagogical order, each self-contained and classroom-sized.

**Week 1 — orientation**

1. [Navigate an aDNA Vault](/learn/tutorials/navigate-a-vault) — 15 min · Beginner — guided tour of a live vault. Students learn the triad and governance files by walking them.
2. [Apply the Question Test](/learn/tutorials/question-test) — 15 min · Beginner — sort 10 sample items into what/how/who. First structural-thinking exercise.
3. [Create Your First CLAUDE.md](/learn/tutorials/first-claude-md) — 20 min · Beginner — students write the agent-orientation file for their forked project vault.

**Week 2 — authoring**

4. [Write a Context File](/learn/tutorials/write-a-context-file) — 30 min · Intermediate — a quality-rubric-scored context file ready for their vault library.
5. [Extend the Ontology](/learn/tutorials/extend-the-ontology) — 25 min · Intermediate — a domain-specific entity type with directory, AGENTS.md, and template.
6. [Design a Mission](/learn/tutorials/design-a-mission) — 25 min · Intermediate — decompose multi-session work into claimable objectives.

**Week 3 — composition**

7. [Build a Lattice](/learn/tutorials/build-a-lattice) — 30 min · Advanced — a validated `.lattice.yaml` as a directed graph of modules.
8. [Run a Campaign](/learn/tutorials/run-a-campaign) — 30 min · Advanced — a phased multi-mission initiative with quality gates.
9. [Federate a Vault](/learn/tutorials/federate-a-vault) — 30 min · Advanced — export, import, and compose lattices across aDNA instances.

## Related

- [Agentic Literacy](/learn/concepts/agentic-literacy) — the competency framework the course develops
- [Dual-Audience Writing](/patterns/dual-audience-writing) — the assessment rubric turned into a writing discipline: can a non-expert navigate this vault?
- [What is aDNA?](/learn/what-is-adna) — recommended first reading for students
- [Navigate a Vault](/learn/tutorials/navigate-a-vault) — the first tutorial students complete
- [The Question Test](/glossary/glossary-question-test) — the what/how/who sorting rule students practice first
- [The Triad](/glossary/glossary-triad) — the three-legged structure the whole course is built on