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+# 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.