# Non-Linear: Product Vision

## One-liner

A graph-native issue tracker for small IT teams where both humans and AI agents navigate a shared decomposition tree of project structure.

## Core Thesis

Software projects are easier to conceptualize top-down using graphs. Traditional issue trackers (Jira, Linear, GitHub Issues) are flat or loosely hierarchical — they force teams to reverse-engineer structure from ticket lists and labels. Non-Linear makes the graph the first-class data model, so both humans and AI agents can reason about project topology directly.

## Why Now

1. **AI agents need topology.** Current tools bolt on AI after the fact. An agent that wants to understand "what should I work on next?" or "what's blocked?" has to reverse-engineer structure from flat ticket lists. A graph-native model gives agents *rails to traverse*. This is a structural advantage, not a feature.

2. **Small teams are underserved.** There's a gap between "too simple" (Trello, GitHub Issues) and "too heavy" (Jira, Azure DevOps). Small teams need more structure than a Kanban board but can't justify Jira administration overhead.

3. **Agent ecosystems are emerging.** Building for AI-agent workflows is a bet on timing. Teams are beginning to use agents for code review, task decomposition, triage, and status reporting. An agent-native tracker is positioned for this shift.

## Target Users

- **Startup dev teams** (3-10 people) building software products
- **Freelancers managing multiple client projects** with cross-project dependencies
- **One-person teams with AI agents** where the agent acts as a focused collaborator

## Competitive Landscape

| Tool | Strength | Gap |
|------|----------|-----|
| Linear | Fast, opinionated, clean | Flat structure, AI retrofitted |
| Jira | Powerful, extensible | Heavy, complex, AI bolted on |
| GitHub Issues/Projects | Integrated with code | Minimal structure |
| Plane.so | Open-source Linear alternative | Same flat model |
| Trello | Simple, visual | No hierarchy, no agent support |
| Kumu / Obsidian Canvas | Graph modeling | Not issue trackers |

**The gap:** No tool combines graph-native project modeling with AI-agent-first API design.

## Design Principles

1. **Graph is the spine.** The decomposition tree defines project structure. Everything else — views, permissions, agent navigation — derives from graph position.
2. **Depth is type.** Issues are untyped. A node's position in the tree implies its abstraction level. Root = project, children = components, leaves = tasks. Labels handle orthogonal concerns.
3. **Two graphs, separated.** The decomposition tree (strict parent→child hierarchy) and the association graph (lateral links like "blocks", "relates-to") are distinct relationship types. The tree is structural; links are annotation.
4. **Agents are first-class actors.** Not assistants bolted on — agents have accounts, roles, permissions, and can traverse the graph independently.
5. **Granular trust.** The permission system is policy-based from day one. Roles are convenience bundles over a granular engine, not hardcoded ceilings.