TODO for AI
vs 
monday.com
By Marcell Havlik, founder of TODO for AI · Updated
Work OS whose AI agents sit in board columns and automations, metered in AI credits. Here is where each one wins, with numbers, and who should pick which.
| Fact | monday.com | TODO for AI |
|---|---|---|
| Interface | Web, desktop, mobile | Web, desktop, mobile, CLI, IDE (Zed, JetBrains, VS Code), voice |
| Models | Vendor managed | Any provider: Claude, GPT, Gemini, Grok, Ollama |
| Source | Closed | Edge + CLI public |
| Starts at | Free | Free |
Key takeaways
- Models. monday.com model choice: Vendor managed. TODO for AI runs any provider, Claude, GPT, Gemini, Grok or a local Ollama model, on one plan, and one model can review another's work.
- Benchmark. TODO for AI scored 95.1% on Terminal-Bench 2.1 with Opus 5.5 (own harness, 77/81 tasks, refused tasks excluded, 2026-09-30; not an official leaderboard submission).
- Price. monday.com pricing: Free, Basic €9, Standard €12, Pro €19 per seat per month billed annually, Enterprise custom. AI credits are included per plan: 1,000 on Basic, 2,000 on Standard, 3,000 on Pro. TODO for AI has a free plan (Claude Sonnet only), then Starter $20, Pro $100 or Ultra $200 a month with any provider included.
- Where the work happens. monday.com gets one task done inside the board. TODO for AI is one board your team and agents work through together, on your own PC, a cloud VM and your logged-in Chrome.
- Who should pick which. Pick monday.com if monday is already where your team tracks work. Pick TODO for AI if the task needs a shell, a repo, a deploy or a logged-in browser.
monday.com
TODO for AI
Any providerWe are not competing for the same job
monday.com gets the task done.
TODO for AI organises the whole company’s work.
monday.com answers one question: how do I get this task done, inside the board? So do the others — Cursor inside the editor, Claude Code in one person's session, Lindy by asking its assistant.
We answer a different one: where does the work live? One board per project, and a project for each part of the company — engineering, marketing, ops, finance, one per client. Your colleagues work on it. So do your agents, as many as you want to run, each with its own model, tools and permissions. Items carry the people who worked them and the agent that ran them, and the board filters by person, so what the company has in flight is one screen instead of a Slack thread.
That is not a team plan bolted onto an AI tool. It is the product. The agents are how items get closed; the board is what the company runs on.
What monday.com is, and where it stops
monday.com is the work OS a lot of non-technical teams already live in, and its AI arrived where that team already looks: an AI column that classifies or summarises rows, agents you drop into automations, a Sidekick that drafts in place. Nothing to install and nothing to learn, because it is the board you opened anyway.
The ceiling is the board. An agent reads and writes items, docs and connected apps, and that is its whole world. It never gets a command line, a machine of its own or a session in your Chrome, so a task like "log into the ad account and pause the losers" has nowhere to land. And the AI is metered separately from the seat: 1,000 to 3,000 credits a month depending on plan, after which the agents stop until you buy more.
Teams already running monday boards who want agents acting on those boards.
Three reasons monday.com users look elsewhere
Agents act on items, columns and connected apps. Work that needs a script written and run, a repo touched or a real browser session driven has nowhere to go.
A seat at €9 to €19, then an AI credit pool that a normal three-person team burns most of every month. The month the agents are useful is the month the bill moves.
The free plan has no AI features, so evaluating the agents at all means paying per seat first.
Six dimensions that decide it
monday.com 14/30TODO for AI 29/30How does monday.com compare to TODO for AI, feature by feature?
| Feature | monday.com | TODO for AI |
|---|---|---|
Persistent cloud VM An always-on machine. Files, logins and sessions survive between runs. | No | Yes |
Model choice | Vendor managed | Any provider |
Cross-vendor review Review GPT output with Claude, or the other way around. | No | Yes |
Drives your real browser Chrome extension plus cloud browsers. | No | Yes |
Business tasks, not only code SEO, email, ads, social, CRM via CLI tools. | Board objects + connected apps | Yes |
Any CLI as an integration | Connectors + MCP | 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, agents in board automations | Yes |
Many agents, each configured Each agent gets its own model, prompt, tools and permissions. Pick which one takes an item. | Agents + Sidekick, per board | Unlimited, per task |
Projects for the whole company Engineering, marketing, ops, finance: separate projects and agents, one team and one bill. | Boards and workspaces | Unlimited, shared |
Team roles, pooled usage | Seat + AI credits | Roles + pooled |
Tool permissions | Board-level | Allow, approve, block |
Open runtime | No | Edge + CLI public |
Same ladder, different meter
Seats plus a monthly AI credit pool: 1,000 on Basic, 2,000 on Standard, 3,000 on Pro. Credit cost varies with task complexity, and monday puts a typical 3-person team at 800 to 1,200 credits a month. Run out and you buy more.
One pool priced in dollars of model cost, spendable on any vendor. Session and weekly windows pace it, and a 1.3-1.5x plan multiplier applies, so a $20 plan is about $15 of list-price API. Team seat prices go into one shared pool.