Why Local-First?

agrepl is built on a local-first philosophy. We believe that developer tools for AI agents should be fast, private, and deterministic.

1. Privacy & Security

AI agents often handle sensitive data: system prompts, proprietary business logic, and PII (Personally Identifiable Information). Cloud-based observability platforms require you to send this data to their servers.

With agrepl, nothing leaves your machine.

• Traces are stored in local JSON files.
• Root CAs are generated locally.
• You have total control over your data.

2. Speed and Developer Loop

Recording and replaying agents should be instantaneous. By running everything locally, agrepl eliminates:

• Network latency to external APIs during replay.
• Slow cloud dashboards.
• Dependency on a stable internet connection for debugging.

3. Determinism

Cloud environments are noisy. By replaying agent sessions locally from a static trace, you ensure that:

• Every tool call returns the exact same result.
• LLM non-determinism is eliminated by caching responses.
• You can debug edge cases in a “frozen” environment.

4. Portability

Because runs are just JSON files, you can:

• Commit them to your git repository for regression testing.
• Send a single file to a teammate to reproduce a bug.
• Build your own tools on top of the open JSON format.