Use Thumper's local AI agent to write, refactor, and debug code without sending your source to the cloud.

What is Vibe Coding?

Vibe coding means describing what you want in natural language and letting an AI agent write the code for you. Instead of typing syntax, you describe the *vibe*—the intent, the behavior, the feel—and the agent translates that into working code.

Cloud coding assistants like Copilot and Cursor send your source code to remote servers. With Thumper-Run's local agent, your code never leaves your machine.

Setting Up the Agent

Install Thumper-Run and open the Agent panel
Select a code-capable model: Qwen 3 14B or DeepSeek Coder V2 recommended
The agent has access to local tools for file reading, writing, and terminal commands

What the Agent Can Do

Generate new files from a description: "Create a REST API in Python with FastAPI that manages a todo list"
Refactor existing code: "Split this 500-line function into smaller helpers"
Debug errors: Paste a stack trace and ask "why is this failing?"
Write tests: "Add unit tests for the authentication module"
Explain code: "Walk me through what this Rust macro does"

Example Session

You: *"Create a Rust CLI tool that watches a directory for new images and generates thumbnails."*

The agent will:

Create a new Cargo project
Add dependencies (notify, image)
Write the watcher logic with error handling
Generate a README with usage instructions
Run cargo check to verify it compiles

Each step is visible in the agent's execution log. You can intervene, ask for changes, or roll back any step.

Privacy Advantage

Cloud coding assistants train on your code, indexing proprietary logic, API keys accidentally left in source files, and internal architecture patterns. A local agent processes everything in-memory and writes only to your filesystem.

Local agent sessions can keep code and history on the machine when cloud models, remote tools, telemetry, and sync are disabled. Current relay-assisted sync is server-assisted and must not be treated as private E2EE for source code or session history.

Model Recommendations

Qwen 3 14B (Q4_K_M): Best all-around for code generation, fits in 10 GB VRAM
DeepSeek Coder V2 16B: Specialized for code, strong at multi-file refactoring
Llama 3.1 70B (Q4_K_M): Best quality if you have 24 GB+ VRAM
CPU users: Qwen 3 4B is viable at ~10 tokens/second for simpler tasks

Check the VRAM guide to match your hardware to the right model.

Tips for Better Results

Be specific about language, framework, and patterns you want
Provide context: paste relevant code snippets the agent should work with
Iterate: the agent improves with feedback in the same conversation
Use the file tool: point the agent at your project directory so it understands the full codebase

Ready to try it? Download Thumper-Run free →