TODO for AI
vs 
ChatGPT
By Marcell Havlik, founder of TODO for AI · Updated
The default AI assistant, with agent mode, deep research and connectors bolted onto the chat product. Here is where each one wins, with numbers, and who should pick which.
| Fact | ChatGPT | TODO for AI |
|---|---|---|
| Interface | Web, desktop, mobile | Web, desktop, mobile, CLI, IDE (Zed, JetBrains, VS Code), voice |
| Models | OpenAI only | Any provider: Claude, GPT, Gemini, Grok, Ollama |
| Source | Closed | Edge + CLI public |
| Starts at | Free | Free |
Key takeaways
- Models. ChatGPT model choice: OpenAI only. 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 89.9% on Terminal-Bench 2.1 with Opus 5.5 (high) (own harness, 80/89 tasks, 2026-10-08; not an official leaderboard submission).
- Price. ChatGPT pricing: Free tier, Go $8, Plus $20, Pro $100 or $200, Business $25 per seat. Every capability has its own cap. 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. ChatGPT gets one task done in a chat window. 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 ChatGPT if you mainly want an excellent assistant for chat, writing and research. Pick TODO for AI if you want the work executed on your PC and a cloud VM, not just described to you.
ChatGPT
OpenAI only
TODO for AI
Any providerWe are not competing for the same job
ChatGPT gets the task done.
TODO for AI organises the whole company’s work.
ChatGPT answers one question: how do I get this task done, in a chat window? 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 ChatGPT is, and where it stops
ChatGPT is the product everyone measures assistants against, and for chat, research and writing it deserves that. Agent mode and deep research turned it from a text box into something that goes away and comes back with work done, connectors reach into Drive and mail, and at $8 for Go the entry price is the lowest here. As a general assistant it is the safest default on the list.
It is still a chat product with agents attached. Everything runs on OpenAI models inside OpenAI's sandbox, and each capability carries its own quota, so you run out of deep research while your message allowance sits untouched. Agent mode can keep cookies between runs and schedule recurring tasks, but it does so inside OpenAI's environment: it never opens a terminal on your machine, never picks up a CLI tool you installed, and never uses the Chrome profile your real sessions live in.
Anyone who wants one excellent assistant for research, writing and everyday questions.
Three reasons ChatGPT users look elsewhere
Messages, deep research, agent runs and images each have a separate cap. You hit one and the rest of the plan cannot cover for it.
Agent mode browses in OpenAI's environment and keeps its own sessions there. It is still not a shell on your PC, not your Chrome profile, and not your repo.
Every answer comes from OpenAI models. There is no way to have Claude or Gemini review the output before it ships.
Six dimensions that decide it
ChatGPT 12/30TODO for AI 29/30How does ChatGPT compare to TODO for AI, feature by feature?
| Feature | ChatGPT | TODO for AI |
|---|---|---|
Persistent cloud VM An always-on machine. Files, logins and sessions survive between runs. | Sandbox per run | Yes |
Model choice | OpenAI only | Any provider |
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. | Their sandbox | Yes |
Business tasks, not only code SEO, email, ads, social, CRM via CLI tools. | Research and docs | Yes |
Any CLI as an integration | Connectors | Any binary |
Voice control | Yes | 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. | No | Yes |
Many agents, each configured Each agent gets its own model, prompt, tools and permissions. Pick which one takes an item. | Custom GPTs | Unlimited, per task |
Projects for the whole company Engineering, marketing, ops, finance: separate projects and agents, one team and one bill. | Shared chat projects | Unlimited, shared |
Team roles, pooled usage | Per seat | Roles + pooled |
Tool permissions | Connector scopes | Allow, approve, block |
Open runtime | No | Edge + CLI public |
Same ladder, different meter
A separate cap per feature: messages, deep research runs, agent runs, image generation. Nothing is pooled between them and nothing carries over.
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.