# three.dev

> Find recurring AI agent failures in production conversations

three.dev helps teams understand where their AI agents go wrong in real conversations. It scores production traffic, attaches evidence to detected issues, and groups recurring problems into failure modes. Teams can see how often a problem occurs and prioritize fixes by its impact, rather than reviewing isolated transcripts without a broader picture.

The recorded context can be handed to a coding agent to help locate and repair the underlying behavior. Comparing traffic before and after a change shows whether a failure became less common and whether new problems appeared. The service offers a free starting option. Its experiment tools and specialized language model offering are separately labeled early access, so those capabilities should be distinguished from the core monitoring workflow.

## Listing details

- Canonical BetaNeon page: https://betaneon.com/products/three-dev
- Official website: https://three.dev/
- Category: Developer tools / ML engineering & evaluation
- Status: Launched
- Topics: AI agents, Debugging, Evaluation, Monitoring, Observability
- Listed: 2026-11-13T06:12:17.215Z
- Content updated: 2026-11-13T06:12:17.277Z
- Official source: https://three.dev/
This is a product introduction, not an endorsement. Confirm current availability, features, and prices on the official website. Community upvotes on BetaNeon are not star ratings.