Which free open-source AI agents work in VS Code or Zed?

What you are probably seeing

You spend hours re-explaining basic code structure to remote AI assistants that do not retain context between sessions.

You notice a gap between the speed of your manual logic building and the time it takes to verify outputs from general LLMs that lack local file access.

Why it happens

Most free AI models are hosted on remote servers that require API keys and upload your proprietary code to third-party infrastructure for processing.

Local open-source agents run inference on your machine, which allows them to access your file system directly but requires you to validate their output more rigorously.

What changed recently

Step by step

1. Install a local LLM runner like Ollama and download a small, efficient model that fits your hardware constraints.

2. Configure a VS Code extension that connects to your local runner to enable in-IDE chat and code completion.

3. Zed users should use the built-in provider settings to point the agent to your local endpoint instead of a cloud service.

4. Define one specific recurring task, such as generating unit tests for a single module, to serve as your benchmark for the agent.

5. Run that task in both the editor and your manual workflow to identify exactly where the AI agent fails to understand your business logic.

Ways to go further

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