TODO for AI
vs 
Linear
By Marcell Havlik, founder of TODO for AI · Updated
The issue tracker engineering teams like, with its own Linear Agent and coding sessions in a Linear sandbox. Here is where each one wins, with numbers, and who should pick which.
| Fact | Linear | TODO for AI |
|---|---|---|
| Interface | Web, desktop, mobile | Web, desktop, mobile, CLI, IDE (Zed, JetBrains, VS Code), voice |
| Models | Linear Agent: Claude, GPT or GLM, picked per workspace; delegated agents bring their own | Claude, GPT, Gemini, Grok and other supported models |
| Source | Closed | Edge + CLI public |
| Starts at | Free | Free |
Key takeaways
- Models. Linear model choice: Linear Agent: Claude, GPT or GLM, picked per workspace; delegated agents bring their own. TODO for AI includes Claude, GPT, Gemini and Grok on paid plans. Pick the model for each job; let another review the result.
- Benchmark. TODO for AI scored 91.0% on Terminal-Bench 2.1 with Opus 5.5 (high) (own harness, 81/89 tasks, 2026-10-26; not an official leaderboard submission).
- Price. Linear pricing: Free, Basic $10, Business $16 per user per month billed yearly, Enterprise custom. Coding sessions draw AI credits: model tokens at provider rates plus $0.25 per 20 minutes of sandbox. TODO for AI has a free plan (Claude Sonnet only), then Starter $20, Pro $100 or Ultra $200 a month with the supported multi-vendor catalog.
- Shared business work. TODO for AI: Your whole team and its AI agents, on one board. Shared company context, brand voice and memory. AI working in your connected tools, signed-in browser and machines.
- Included usage. One shared pool of credits, with the cloud VM and browser included. Personal session and weekly limits apply. Credit usage depends on the model; see the pricing page for plan details.
- Who should pick which. Pick Linear if your work is engineering issues and cycles, and you want the best tracker for them. Pick TODO for AI if the work on your board is not only code.
Linear
Linear Agent: Claude, GPT or GLM, picked per workspace; delegated agents bring their own
TODO for AI
Supported vendorsWhere our product fits
One board for the company’s work.
People decide. Agents do the work.
Your whole team and its AI agents, on one board. Shared company context, brand voice and memory. AI working in your connected tools, signed-in browser and machines.
Chase the invoice. Ship the website update. Prepare the report. Fix the code. Every task keeps its request, contributors and result together, ready for the next colleague or agent to pick up.
Keep Linear where it fits. Bring the rest of the company’s backlog here.
Plans and usage limitsWhat Linear is, and where it stops
Linear is the closest thing to what we are building, from the opposite direction. It already has the thing the agent vendors do not: a real shared board, where a teammate and an agent can hold the same item, where state is queued, started, blocked and done, and where everyone can see it. It now has its own worker too. Linear Agent answers in chat, in comments and in Slack, creates and updates issues, runs Skills and scheduled Loops, reaches other tools over MCP, and starts coding sessions in a Linear-hosted sandbox that installs the toolchain, tests the app in a browser and opens the PR. Admins pick Claude, GPT or GLM for the workspace.
The shape is still product and engineering. The sandbox works on a GitHub repo, the browser inside it is for testing your app, and anything else goes through whatever MCP connections exist. There is no shell on your own machines, no session in your logged-in Chrome, and the model is one workspace setting rather than a choice per agent.
Engineering teams who want issues, cycles and coding agents on one board.
Three reasons Linear users look elsewhere
Linear Agent can reach other tools over MCP, but the sandbox, the browser and the workflow are shaped around a repo. Invoices, outreach and ad accounts have no natural home there.
Coding sessions run in Linear's managed sandbox. Linear never gets a shell on your box or a session in your Chrome, so a tool behind your logins without a connector goes back to a human.
Admins choose the model for coding sessions across the workspace. TODO for AI sets the model per agent, so triage can run on a cheap model and the hard part on a strong one.
Six dimensions that decide it
Linear 17/30TODO for AI 28/30How does Linear compare to TODO for AI, feature by feature?
| Feature | Linear | TODO for AI |
|---|---|---|
Persistent cloud VM A hosted workspace with persistent files, separate from the machines you connect. | Linear sandbox for coding sessions | Yes |
Model choice | Claude, GPT, GLM per workspace | Supported models across vendors |
Cross-vendor review Review GPT output with Claude, or the other way around. | No | Yes |
Drives your real browser Browser extension (Chrome, Firefox) plus cloud browsers. | Sandbox browser for testing, not your session | Yes |
Business tasks, not only code SEO, email, ads, social, CRM via CLI tools. | Engineering first, MCP beyond | Yes |
Any CLI as an integration | MCP + Agent API | Any binary |
Voice control | No | Yes |
People and agents on one board Colleagues and agents work the same list. Items show who contributed and which agent ran them; filter the board by person. | Yes, for engineering issues | Yes |
Many agents, each configured Each agent gets its own model, prompt, tools and permissions. Runs remain subject to usage limits. | Linear Agent + 30+ delegated | Configured per task |
Projects for the whole company Engineering, marketing, ops, finance: separate projects and agents, one team and one bill. | Teams and projects | Unlimited, shared |
Team roles and usage Pooling is not exclusive to TODO for AI. A shared budget does not remove personal session or weekly limits. | Per seat + AI credits | Shared credits, per-seat limits |
Tool permissions | OAuth scopes | Allow, approve, block |
Open runtime | No | Edge + CLI public |
Same ladder, different meter
Seats, plus AI credits for coding sessions and Loops (tokens at provider rates, sandbox $0.25 per 20 minutes). Delegated agents such as Devin or Cursor bill on their own plan on top.
One shared pool of credits, with the cloud VM and browser included. Personal session and weekly limits apply. Credit usage depends on the model; see the pricing page for plan details.