lightning-studios

Provision and manage persistent cloud development environments on Lightning AI.

5|Updated Jul 3, 2026
One-click install
npx skills add https://github.com/Lightning-AI/skills --skill lightning-studios
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: lightning-studios
Source: https://github.com/Lightning-AI/skills/tree/main/lightning-studios
Command: npx skills add https://github.com/Lightning-AI/skills --skill lightning-studios

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires lightning-sdk.

What problem does it solve?

This skill removes the friction of setting up and managing cloud-based development environments, allowing users to provision, configure, and control GPU-accelerated machines directly through their AI agent.

Core Features & Use Cases

  • Lifecycle Management: Create, start, stop, and delete persistent cloud studios with specific hardware configurations.
  • Resource Optimization: Switch machine types (CPU to GPU) dynamically to balance performance and cost.
  • Use Case: A developer needs to run a heavy training job but wants to keep costs low; they can use this skill to spin up a CPU studio for code preparation, switch to an A100 GPU for the training run, and stop the studio immediately upon completion.

Quick Start

Use the lightning-studios skill to create a new studio named experiment-one and start it with a GPU machine type.

Frequently Asked Questions about lightning-studios

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I manage cloud GPU development environments on demand?

You can manage cloud GPU development environments by provisioning and controlling persistent studios directly through your AI agent. This allows you to create, start, stop, and delete machines with specific hardware configurations on demand.

Can I switch a cloud studio from CPU to GPU dynamically?

Yes, you can switch machine types dynamically from CPU to GPU to balance performance and cost. This allows you to use a CPU studio for code preparation and switch to an A100 GPU for heavy training runs.

Do I need the lightning-sdk to provision persistent cloud studios?

Yes, you need the lightning-sdk Python package and valid API credentials to interface with the Lightning AI infrastructure. These are required to provision and manage persistent cloud-based development environments.

What is the best way to automate cloud infrastructure lifecycle operations?

The best way to automate cloud infrastructure lifecycle operations is by using an AI agent to facilitate machine type switching, file synchronization, and remote command execution for compute-intensive tasks.

How do I keep cloud GPU costs low during heavy training jobs?

To keep cloud GPU costs low, you can spin up a CPU studio for code preparation, switch to a GPU machine type for the training run, and stop the studio immediately upon completion. This optimizes resource usage.

Does file synchronization work with remote command execution in cloud studios?

Yes, file synchronization works alongside remote command execution to facilitate compute-intensive tasks in cloud studios. These lifecycle operations are managed directly through your AI agent.