Running multiple coding agent harnesses? Omnigent + MLflow adds layered observability
Teams building AI agents often use separate 'harnesses' (the tools or environments that run an agent) for different jobs: one for , another for , another for evaluation. That raises three problems: how to coordinate the workflow across harnesses, how to confirm the agent is actually doing the right thing, and how to evaluate the outcome of each task. Omnigent, an project, is built to handle the side of that problem.
Tracing and evaluation are handled separately by pairing it with MLflow. The post itself is a brief pointer rather than a walkthrough — it notes the actual link and setup details are in the comments, so no concrete is given here.
Key points
- Multi-harness setups are common: separate tools for , , and evaluation
- Omnigent is an project focused on work across those different harnesses
- Tracing and evaluation are handled by pairing it with MLflow
- The actual link and setup details are only in the post's comments, not in the post itself