LangChain

Schedules for Managed Deep Agents: Cron jobs, prompts, and Slack delivery

Published 2026-09-23 · Duration 3:26

Summary

This video demonstrates how to implement automated, recurring tasks using Schedules for Managed Deep Agents. By configuring cron jobs, agents can run autonomously to generate and deliver structured reports (e.g., a weekly Salesforce pipeline summary) to external channels like Slack, without manual intervention. The process involves defining the schedule syntax, deploying the agent to LangSmith, and ensuring the agent has access to necessary tools and context.

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Key takeaways

  1. Automated Reporting via Cron Jobs

    Schedules allow agents to send recurring messages that invoke tools or leverage context, such as generating a weekly pipeline summary for the sales team.

  2. Schedule Configuration 0:01

    Schedules are defined by creating a file in the schedules directory, specifying a cron job, a time zone, a prompt, and optional input context.

  3. Deployment and Monitoring 0:01

    The scheduled agent must be deployed to LangSmith using a deploy command, allowing users to inspect the configured cron jobs and prompts within the LangSmith UI.

Technical details

  • Agent Architecture 0s

    Managed Deep Agents can be configured with instructions and tools (e.g., access to Salesforce) to perform complex tasks.

  • Scheduling Syntax 1s

    Schedule definition requires a cron expression, a specific prompt, and the ability to configure input context (e.g., a user message).

  • Integration and Tools 0s

    Real-world tool connections, such as Salesforce, should utilize an MCP server. The agent can also be configured to deliver results directly to specific channels, such as Slack.

  • Deployment Workflow 1s

    To activate the schedule, the agent must be deployed to LangSmith, which publishes the agent and configures the cron job.

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