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Claude Code's new web-based scheduled tasks let developers run automation scripts reliably around the clock, eliminating the need to keep machines active or constantly monitor sessions for task execution.
If you're a developer who relies on automation to streamline your workflow, Claude Code's new web-based scheduled tasks might be just what you need. This feature allows you to run prompts at regular intervals using Anthropic-managed cloud infrastructure, ensuring that your tasks continue to execute even when your computer is offline.
Previously, scheduling tasks with Claude Code required keeping your machine running or using the /loop command within a session. Now, with web-based scheduled tasks, you can automate recurring work without worrying about your local environment. This is particularly useful for:
These tasks are available to all Claude Code on the web users, including Pro, Max, Team, and Enterprise plans.
To help you decide which scheduling method fits your needs, here’s a breakdown of the three options:
| | Cloud (Web) | Desktop | /loop |
| --- | --- | --- | --- |
| Runs on | Anthropic cloud | Your machine | Your machine |
| Requires machine on | No | Yes | Yes |
| Requires open session | No | No | Yes |
| Persistent across restarts | Yes | Yes | No (session-scoped) |
| Access to local files | No (fresh clone) | Yes | Yes |
| MCP servers | Connectors configured per task | [Conf] |
To set up a scheduled task, follow these steps:
You can set tasks to run at various frequencies:

When creating a scheduled task, you need to specify the repository and branch. The task will have access to the code in that branch, but it won't be able to write changes back to the repository unless explicitly configured.
Connectors are pre-configured integrations that allow your scheduled tasks to interact with other services. For example:
Each connector can be configured per task, ensuring that you have the right level of access and functionality.
You can run scheduled tasks in different environments to match your development, staging, and production workflows. This helps ensure that changes are tested and validated before they reach production.
Once you've created a scheduled task, you can manage it from the web interface:
For more detailed information, check out the following resources:
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Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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