LangSmith Engine is how we’re spinning the always-on, self-improvement loop for every agent
- Tracing is on for every single agent
- Purpose built infra with SmithDB to handle data at agent scale (more data than humans have ever produced will be produced by agents)
- Ambient agentic intelligence applied to every Trace to find errors, product insights, or anything you want to look for (you can customize Engine to your needs)
- PRs and Evals generated from this massive data with human gating/acceptance
the data our agents produce is a gold mine of information to make agents and systems better over time
the goal is that this flow shows users the first sparks of truly always on Continual Learning for their agents across their entire company
