Comparison · GitHub · verified 2026-09-22

TODO for AI
vs GitHub Copilot

GitHub's coding agent: completions in the editor, a cloud agent that takes an issue and opens a pull request. Here is where each one wins, with numbers, and who should pick which.

Start free PricingGitHub Copilot site
InterfaceIDE, GitHub.com, CLIWeb, desktop, CLI, voice
ModelsOpenAI, Anthropic, Google, xAI, moreEvery provider
SourceClosedEdge + CLI public
Starts atFreeFree
Facts verified 2026-09-22. Pricing is public list price.
Every vendor
models, vs openai, anthropic, google, xai, more
Your machines
PC, cloud VM, real Chrome
Any CLI
is an integration, not just MCP
Free
from, vs Free
Architecture at a glance
GitHub Copilot
Models
OpenAIOpenAI, Anthropic, Google, xAI, more
Runs in
IDE, GitHub.com, CLI
Where it lives
GitHub runners per task
Produces
Code
PRs
Code and pull requests
SEO
Email
Ads
TODO for AI
Models
AnthropicOpenAIGooglexAIDeepSeekEvery provider
CROSS-VENDOR REVIEW
Runs in
Your PC
Cloud VM
Real Chrome
Voice
Where it lives
Always-on cloud VM · vault · your logins
Produces
Code
SEO
Email
Ads
Social
CRM
Struck-through outputs are outside GitHub Copilot's scope. TODO for AI runs the same models plus the rest, from a machine that stays on.
The short version

Who should pick which

Choose GitHub Copilot if
  • Your work is GitHub issues and pull requests
  • You want the cheapest entry into a serious coding agent
  • You want completions and an agent from one vendor
Choose TODO for AI if
  • A lot of your backlog never becomes a pull request
  • You need the agent on your own machines and in your own browser
  • You want one flat budget instead of metered premium requests
  • You want engineers and non-engineers on the same board
Positioning

We are not competing for the same job

Different problem

GitHub Copilot gets the task done.
TODO for AI organises the whole company’s work.

GitHub Copilot answers one question: how do I get this task done, from issue to pull request? 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.

Context

What GitHub Copilot is, and where it stops

Copilot is the default coding agent by distribution. It completes in the editor, reviews pull requests, and the cloud agent picks up an issue, works on GitHub's runners and opens a PR. The model picker is the most open of any coding agent here: OpenAI, Anthropic, Google, xAI, Moonshot and Microsoft models, with Claude Code and Codex available as third-party agents on the same surface.

The shape is the constraint. Copilot works where GitHub works: repositories, issues, pull requests, Actions. Anything that is not a diff has no home. Copilot CLI does run in your terminal with per-command approval, but the agent that works unattended runs on GitHub's runners, and premium requests meter per model so an active team's bill follows its habits.

Teams whose work lives on GitHub and who want agents attached to issues and pull requests.
Why people switch

Three reasons GitHub Copilot users look elsewhere

01
Everything must become a pull request

The unit of work is a diff, tracked as an issue on a repository. An invoice to chase, a campaign to launch or an inbox to triage has no shape in Copilot.

02
Autonomous work leaves your machine

Copilot CLI runs locally, but the agent that works unattended does so on GitHub's runners, on a clone of the repo. It reaches neither your servers nor your logged-in browser.

03
Metered premium requests

Completions are unlimited, agent work is not. Premium requests carry a per-model multiplier and overage bills per request.

Scores

Six dimensions that decide it

Six dimensions, 0 to 5
GitHub Copilot 16/30TODO for AI 29/30
Model freedom4 · 5 /5
Which vendors and models you can run
Long-running work3 · 5 /5
Persistent machine, scheduling, parallel tasks
Beyond code1 · 5 /5
Marketing, ops, browser, email, not only repos
Openness1 · 4 /5
Source available, self-host, extend
Team & permissions4 · 5 /5
Roles, pooled usage, tool approvals
Cost predictability3 · 5 /5
Flat plan vs metered tokens
Feature by feature

What each one ships

FeatureGitHub CopilotTODO for AI
Persistent cloud VM
An always-on machine. Files, logins and sessions survive between runs.
GitHub runners per task
Model choice
OpenAI, Anthropic, Google, xAI
Any provider
Cross-vendor review
Review GPT output with Claude, or the other way around.
Drives your real browser
Chrome extension plus cloud browsers.
Business tasks, not only code
SEO, email, ads, social, CRM via CLI tools.
Code and pull requests
Any CLI as an integration
CLI locally, MCP
Any binary
Voice control
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, issues and pull requests
Many agents, each configured
Each agent gets its own model, prompt, tools and permissions. Pick which one takes an item.
Coding agent + custom agents
Unlimited, per task
Projects for the whole company
Engineering, marketing, ops, finance: separate projects and agents, one team and one bill.
Repos and issues
Unlimited, shared
Team roles, pooled usage
Per seat
Roles + pooled
Tool permissions
Repo scopes + command approval
Allow, approve, block
Open runtime
Edge + CLI public
Pricing

Same ladder, different meter

TierGitHub CopilotTODO for AI
EntryFree, or Pro $10Free (Sonnet only), or Starter $20
MidPro+ $39Pro $100
TopMax $100Ultra $200
TeamBusiness and Enterprise per seat$30 standard / $120 premium per seat, min 2 seats incl. 1 premium, +$50 bonus pool
GitHub Copilot · what it meters

Completions are unlimited on paid plans. Agent work spends premium requests, multiplied per model, and overage bills per request.

TODO for AI · what it meters

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.

USD per month, monthly billing, public list prices as of 2026-09-22.
Verdict

Bottom line

Our take
If your engineering work lives on GitHub, Copilot is the cheapest and most convenient way to put agents on it, and the model picker is genuinely open. TODO for AI is for the rest of the backlog: the tasks that never become issues, worked by an agent with a shell on your own machines and a session in your real Chrome, on a board your non-engineers can also use.
FAQ

Common questions

Is TODO for AI a GitHub Copilot alternative?
For code, they overlap; Copilot is better integrated with GitHub and cheaper to start. The difference is scope: TODO for AI also runs the non-code half of the backlog, on your machines, with every model on one plan.
Does Copilot let me choose the model?
Yes, and its picker is unusually wide: OpenAI, Anthropic, Google, xAI and more, though premium requests carry per-model multipliers. TODO for AI includes every vendor in one dollar pool.
Does the Copilot agent run on my computer?
Partly. The IDE agent and Copilot CLI run locally, and the CLI executes shell commands with your approval. The autonomous cloud agent runs on GitHub's runners. Neither reaches your other servers or a session in your real Chrome, which is what TODO for AI's bridge and extension provide.
Can I use both?
Yes, and many do. Copilot for in-editor completion and PR work, TODO for AI for the tasks that never make it to an issue.