Magnet 
Magnet is an AI business or productivity platform for creating and operating supported digital workflows.
Starting price Free + from $20/mo
Tool Information
Magnet is an AI business or productivity platform for creating and operating supported digital workflows.
Users define a narrow goal, provide only authorized inputs, generate a draft, compare it with reliable sources or originals, correct errors and rights issues, test the final output, and keep a human responsible for publication or action.
Free limited access is available and paid access starts from $20 per month; workspaces, usage, integrations, and billing period vary.
Connected AI can expose data, follow malicious instructions, or perform unintended actions. Least privilege, testing, logs, budgets, approvals, and rollback matter.
F.A.Q (3)
Pros and Cons
Pros
- Magnet gives teams a shared workspace for long-running coding agents
- Each session runs in an isolated cloud sandbox
- A connected repository is cloned automatically at the selected base branch
- Claude Code can inspect files; edit code; run commands; and execute tests
- Agents can make incremental Git commits while working
- Completed sessions can open pull requests automatically
- Issue tracking links the requested work to its implementation session
- Pages and documents keep specifications beside agent activity
- GitHub integration exposes pull-request diffs inside the workspace
- Real-time streaming lets teammates observe agent actions as they happen
- Follow-up messages can redirect an active session with more context
- Several sessions can run in parallel without occupying a developer laptop
- Environment setup can be customized for a codebase's dependencies and dev server
- Failed sessions retain conversation history for diagnosis
- An API allows sessions to be created programmatically
- The workflow is well suited to scoped fixes; refactors; tests; and overnight tasks
Cons
- Cloud sandboxes receive broad access to repository source code
- GitHub credentials and secrets require strict scoping and rotation
- An autonomous agent can introduce subtle bugs across thousands of changed lines
- Automatic pull-request creation does not replace human code review
- Parallel sessions can conflict when they modify overlapping modules
- Long-running work can consume substantial model and compute resources
- A weak prompt can produce a large but misdirected change
- Setup scripts from a repository can execute inside provisioned environments
- Tests can pass while product requirements; security; or performance regress
- Real-time streams may expose secrets printed by tools or logs
- Claude Code is the documented execution agent; limiting model choice
- Teams become dependent on Magnet's sandbox availability and GitHub integration
- Environment drift can make agent results differ from production
- Issue auto-completion on merge needs careful workflow configuration
- Large diffs increase reviewer fatigue and the chance of approving mistakes
- Consequential deployment; migration; and security actions need explicit approval boundaries
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Overview
Before you subscribe
- Check the currency, billing period, automatic renewal, usage limits and seats at checkout — prices and promotions change.
- App-store pricing can differ from website pricing by country, device and tax.
- Share only authorised data, and read the provider's encryption, retention and model-training terms first.
- AI output can be incomplete or wrong. Verify facts, citations, calculations and code before you publish or ship.
- Commercial usage rights vary by plan, provider terms and jurisdiction.
- None of these tools replaces a qualified professional for medical, legal or financial decisions.
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