Configure your dev environment and a coding agent
Go from a fresh Windows PC to a fully configured development environment and coding agent.
Microsoft’s Windows Developer Config turns a fresh Windows 11 machine into a ready-to-use development machine. See the project README for a complete list of configurations and downloads.
This configuration installs PowerShell 7, Git, GitHub CLI, VS Code, Python, uv, Node.js, .NET, WSL with Ubuntu, and common developer settings. Review what this configuration changes.
Open Windows Terminal, select PowerShell, and choose Run as administrator. Download and apply Microsoft’s Standard Windows Developer Config using the command from the project’s Quick start:
irm https://aka.ms/devconfig/standard/setup.ps1 | iex
Plan about 30 minutes for this configuration on a clean machine with a good internet connection. Accept the User Account Control prompts. If setup restarts Windows to enable WSL, sign back in and accept the second prompt; setup resumes automatically. The configuration is complete when it prints its final summary.
Coding agents help developers move faster by exploring codebases, implementing features, fixing bugs, writing tests, and automating repetitive tasks. You can run them locally for fast and unlimited private experimentation without cloud usage limits.
Choose the approach that best fits your needs:
To get started with open-source coding-first agents, follow these instructions:
Note: We will add instructions for GitHub Copilot shortly.
Note: Pi is a lightweight terminal coding agent. It runs inside a project folder and can inspect, edit, and execute code using a local model. The steps below will bring you through installation, setup, and a sample workflow example.
Open a new PowerShell window and install Pi and its llama.cpp integration:
npm install -g --ignore-scripts @earendil-works/pi-coding-agent
pi install git:github.com/huggingface/pi-llama
Install and start llama.cpp using the Running Models Locally playbook. Keep the PowerShell window running llama-server.exe open. Open a second PowerShell window and verify that the server is ready:
Invoke-RestMethod http://127.0.0.1:9931/health
Continue when the response reports a status of ok.
In the second PowerShell window, change to your project folder and start Pi:
cd C:\path\to\your\project
pi
In Pi, select the model served by llama.cpp:
/model
After selecting your model, you’re ready to get coding with your local agent! Take a look at the official documentation for Pi usage to get started with the commands and capabilities offered to you, or ask your agent itself for a walk through!
Take me through a tutorial of all the capabilities this harness offers.
cuopt-numerical-optimization-api with the name of the skill you want to install:npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --yes
--agent. You can use any of the agents described above. Use --agent more than once to install the same skill into multiple agents./reload-skills. In other agents, start a new session.Start building GPU-accelerated applications locally or in the cloud with NVIDIA CUDA and other GPU development tools.