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LidRun

Keep Claude Code, Cursor, Docker, Ollama and long-running Mac tasks alive with closed-lid workflows, timers, charging-only mode, low-battery auto-stop and thermal guardrails.

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LidRun

LidRun Reviews and Details

This page is designed to help you find out whether LidRun is good and if it is the right choice for you.

Screenshots and images

  • LidRun
    Image date //
    2026-06-29

Features & Specs

  1. AI Workflow Continuity

    Keep Claude Code, Cursor, Codex, Docker builds, Ollama and local LLM jobs running on your Mac even when the lid is closed.

  2. Battery & Thermal Guardrails

    Monitor battery level and thermal state during long runs, with low-battery auto-stop and thermal-aware protection instead of a blind wake lock.

  3. Auto Mode (Smart Routing)

    Keep your Mac awake only while a watched process is actively running. Idle apps won't hold your Mac awake unnecessarily.

  4. Closed-Lid Runtime

    Continue AI and developer workflows with the MacBook lid closed without requiring an external display setup.

  5. Smart Auto Release

    Automatically release the wake lock and let your Mac return to normal sleep when the task is finished.

  6. Developer CLI Support

    Built for terminal-first workflows with CLI support for developers running scripts, builds, agents and automation.

  7. Live System Monitoring

    View battery status, temperature information and runtime state directly from the menu bar.

  8. Safety-First Runtime Engine

    Designed as a safe runtime layer for AI work on Mac โ€” helping reduce risks during long unattended sessions.

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Questions & Answers

As answered by people managing LidRun.
  1. What's the story behind LidRun?

    LidRun started from a simple frustration: starting a long AI coding session or overnight build, closing a MacBook to move around, and discovering the workflow stopped because macOS went to sleep.

    Existing tools could keep a Mac awake, but they were mainly designed for simple scenarios like keeping a screen active. Long AI and developer workloads created a different challenge: keeping work running while being more aware of battery and thermal limits. LidRun was built to solve that gap โ€” giving Mac users a safer way to keep AI and development workflows running even with the lid closed.

  2. What makes LidRun unique?

    LidRun is built for a new category: the safe runtime layer for AI work on Mac. Unlike traditional keep-awake tools that simply prevent sleep, LidRun is designed for long AI and developer workflows โ€” keeping Claude Code, Cursor, Codex, Docker, and local LLM jobs running even when the lid is closed.

    Its key difference is safety-aware automation: battery monitoring, thermal awareness, low-battery auto-stop, Auto Mode, and automatic release when work is finished. LidRun helps developers keep AI workloads running without relying on a blind wake lock.

  3. Why should a person choose LidRun over its competitors?

    Traditional tools like caffeinate and Amphetamine are excellent for simple keep-awake use cases. LidRun focuses on a different problem: keeping long-running AI and developer workflows alive when you leave your Mac.

    LidRun combines closed-lid runtime support with intelligent controls โ€” keeping your Mac awake only when work is actually running, monitoring battery and thermal conditions, and automatically returning the Mac to normal sleep when the task is complete.

    It is built for developers, AI users, and anyone running unattended workloads on a Mac.

  4. Which are the primary technologies used for building LidRun?

    LidRun uses native macOS technologies to provide reliable runtime control:

    • IOKit power assertions for managing keep-awake behavior
    • macOS power management controls (pmset) for lid-closed workflows
    • Battery monitoring through macOS system APIs
    • Thermal state monitoring for safety-aware controls
    • Process monitoring for Auto Mode
    • Offline license verification using Ed25519 signatures

    LidRun is built without kernel extensions or display simulation hacks, focusing on documented macOS capabilities.

  5. How would you describe the primary audience of LidRun?

    LidRun is designed for Mac users running long AI and developer workflows, especially:

    • Developers using Claude Code, Cursor, Codex, Docker, or local LLMs
    • AI engineers running agents and automation tasks
    • Indie hackers building and testing projects overnight
    • Developers running long builds, scripts, and terminal workflows
    • Power users who need their Mac to keep working while they step away
  6. Who are some of the biggest customers of LidRun?

    LidRun is currently designed for individual developers, AI builders, and Mac power users.

    Typical users include:

    • Developers running Claude Code, Cursor, Codex, and Docker workflows
    • AI engineers experimenting with local LLMs
    • Indie hackers building products on Mac
    • Professionals running long automation or build processes

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Is LidRun good? This is an informative page that will help you find out. Moreover, you can review and discuss LidRun here. The primary details have been verified within the last quarter. So they could be considered up to date. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.