aDNA vs. PARA
Two systems for organizing knowledge — one designed for personal productivity, the other for AI-native project collaboration.
Overview
aDNA
A knowledge architecture standard for AI-native projects (§1). Organizes all project knowledge into three directories — what/, how/, who/ — determined by the question test. Designed for both human and AI-agent navigation. Includes governance files, session tracking, federation, and FAIR metadata. Open standard with spec, template, and extension system.
PARA
Tiago Forte’s organizational system from Building a Second Brain. Organizes personal knowledge into four categories: Projects (active), Areas (ongoing responsibilities), Resources (reference material), Archives (inactive). Designed for individual knowledge management across tools like Notion, Obsidian, and Evernote.
Comparison
| Dimension | aDNA | PARA |
|---|---|---|
| Organizing principle | 3 categories by question type (what/how/who) | 4 categories by actionability (projects/areas/resources/archives) |
| Primary audience | Teams + AI agents | Individual humans |
| Agent support | Native: CLAUDE.md, AGENTS.md, session tracking, convergence model | None: no agent orientation, no routing, no governance files |
| Knowledge types | 14+ entity types with typed frontmatter | Untyped: any note can go anywhere within the 4 buckets |
| Scalability | Multi-agent, multi-project, federated | Single-person, cross-tool |
| Learning curve | Moderate: spec, templates, governance files | Low: 4 simple categories, minimal rules |
| Extensibility | Base/extension architecture with domain types | Flexible but informal: no extension framework |
| Collaboration | Built-in: sessions, coordination notes, handoff protocols | Bolted-on: depends on the tool’s sharing features |
| Standards | Open spec (§1-§13), FAIR metadata, typed I/O | No spec: a method, not a standard |
Where aDNA Excels
- Agent collaboration: PARA has no concept of AI agents navigating knowledge. aDNA’s governance files, AGENTS.md routing, and session tracking were built for agent-first operation.
- Team scale: PARA is personal. aDNA handles multi-agent coordination, conflict detection, and handoff continuity.
- Typed knowledge: aDNA’s 14 base entity types and frontmatter conventions make knowledge machine-queryable. PARA notes are freeform.
- Federation: aDNA lattices can be shared across instances. PARA has no cross-system sharing protocol.
Where PARA Excels
- Simplicity: Four buckets. No frontmatter. No governance files. You can explain PARA in 5 minutes. aDNA takes longer to learn.
- Personal fit: PARA was designed for how individuals think about their own projects and responsibilities. aDNA was designed for projects, not people.
- Tool agnosticism: PARA works in any notes app. aDNA works best with AI agents (Claude Code, etc.) and Obsidian — its governance files are meaningless without agent tooling.
- Low overhead: No session files, no AGENTS.md, no templates. PARA is lightweight by design.
When to Choose Which
| If you need… | Choose |
|---|---|
| Personal knowledge management across apps | PARA |
| AI-agent-navigable project knowledge | aDNA |
| A quick organizational system for your notes | PARA |
| Multi-agent collaboration with audit trails | aDNA |
| Minimal overhead, maximum simplicity | PARA |
| Typed, federable, FAIR-annotated knowledge objects | aDNA |
| To organize existing personal notes better | PARA |
| To build a knowledge architecture for a team or project | aDNA |
They’re not mutually exclusive. A developer might use PARA for personal notes and aDNA for shared project knowledge.
Sources
- Tiago Forte, Building a Second Brain (2022) — PARA method definition
- Forte Labs: fortelabs.com/blog/para — PARA overview
- aDNA Standard v2.1, §1 (Introduction), §3 (Triad Architecture) — aDNA specification
Related
- The Triad — aDNA’s three-category organizing principle (compare to PARA’s four)
- Governance Files — the agent-orientation layer PARA lacks
- Agentic Literacy — the skill set aDNA develops that PARA doesn’t address