runloq vs Linear — Why runloq for AI Coding Agents
Linear is one of the best project management tools ever built for humans. Fast, opinionated, beautiful. If your team of engineers wants a structured sprint workflow with cycle management, roadmaps, and Slack notifications, Linear is excellent.
But Linear was built for human product teams, not AI coding agents. The gap is fundamental, not cosmetic.
The fundamental difference
Linear answers: “What is the team working on, in what sprint, assigned to which person?”
runloq answers: “What is the agent backlog, routed to which AI specialist, running on which model, with full audit trail?”
The second question is meaningless to Linear. There’s no model field, no agent field, no concept of “which LLM tier should execute this ticket.”
Feature comparison
| Feature | runloq | Linear |
|---|---|---|
agent field — which AI specialist | ✅ | ❌ |
model field — opus/sonnet/haiku | ✅ | ❌ |
| MCP server (structured agent access) | ✅ | ❌ |
| Local-first SQLite, works offline | ✅ | ❌ (cloud-only) |
| Free forever (local) | ✅ | ❌ (seat pricing) |
| Scheduled + recurring tickets | ✅ | Partial (cycles) |
| Append-only agent audit log | ✅ | Partial (issue history) |
| Auto-spawn next iteration on close | ✅ | ❌ |
| React dashboard | ✅ (included) | ✅ (better for humans) |
| Roadmaps + cycles | ❌ | ✅ |
| Team @mentions + notifications | ❌ | ✅ |
| Slack/GitHub PR integration (human) | Partial | ✅ (native) |
| Enterprise SSO + audit | ❌ | ✅ |
When to use Linear instead of runloq
Linear wins for:
- Human product teams (PMs, designers, engineers) doing sprint planning
- Companies with compliance needs (SOC 2, audit logs for humans)
- Teams that need roadmaps, OKRs, and cycle management
- Orgs already paying for Linear and not doing agent-driven work
When to use runloq instead of Linear
runloq wins when:
- You’re a solo developer or small team where AI agents do most of the coding
- You want cost-aware model routing — mechanical tasks on sonnet, strategic work on opus
- You need an offline-first, zero-cloud-dependency backlog
- Linear’s per-seat pricing doesn’t fit a single-developer workflow
- You want your agent to pick up and close tickets without any UI
The cost argument
Linear charges per seat. For a solo developer using Claude Code as the “second engineer,” you’re paying for a seat that the AI agent will never use.
runloq is free forever for local use. The agent reads the backlog via MCP or CLI. No seat. No monthly billing. No API rate limits.
The model-routing argument
When Linear assigns a task to a human engineer, it doesn’t need to know whether that engineer is “junior” or “senior” — the human figures it out.
When runloq assigns a task to an AI agent, the model matters enormously:
haiku— trivial mechanical work: rename, format, boilerplate. ~$0.05/turn.sonnet— debugging, refactoring, implementing a clear plan. ~$0.43/turn.opus— architecture, design reviews, hard reasoning. ~$1.73/turn.
A debugging session incorrectly assigned to opus costs 4× more than on sonnet, with no quality improvement. runloq lets you encode this decision at ticket-creation time. Linear has no equivalent concept.
The local-first argument
Linear is cloud-only. Your backlog lives on Linear’s servers. If Linear is down, you can’t see your tasks. If you’re on a plane, you can’t check what’s blocked.
runloq is one SQLite file. Open it with any SQLite viewer. Back it up with cp. Run it on a plane. The agent can read the backlog with zero network connectivity.
Can I use both?
Yes — run runloq as your agent’s local backlog and keep Linear for the human team. If your agent needs Linear access, run the official Linear MCP server alongside runloq; runloq stays focused on being the agent-driven backlog.
Frequently asked questions
Is runloq a Linear alternative? For solo developers using AI agents, yes. For human product teams, no — Linear is still better for that use case.
Does runloq have roadmaps? No. runloq is a task tracker, not a roadmap tool. If you need quarterly planning and OKRs, use Linear for that layer and runloq for agent-driven execution.
Does Linear have an MCP server? Not yet (as of 2026). Linear has a GraphQL API, but no MCP server designed for AI agent consumption. runloq’s MCP server is specifically built for the agent protocol.
What’s the migration path from Linear to runloq?
Run prism import-linear (coming in v0.2) to pull your open issues from Linear via the GraphQL API and import them as runloq tickets. Or start fresh — runloq tickets are simpler to create than Linear issues.