Multi-agent observability is fragmented across every framework — built a tool to fix that
Summary
A new tool aims to solve the fragmented state of observability across multi-agent frameworks.
Similar Articles
Which platform is your company using for ai agent observability and reliability needs?
A developer building multi-agent financial workflows seeks community advice on observability and reliability tooling for AI agents in production, sharing frustration with fragmented landscape and cascading failures.
What are you using for observability?
A developer discusses the lack of suitable observability tools for AI agents, expressing disappointment with existing solutions like Opik and hoping for a service that supports OpenTelemetry for analyzing agent sessions and failure modes.
@bentannyhill: Agent observability is a means to an end: making your agent better. But observability and evals tools have traditionall…
Engine is a new tool that connects agent observability traces to automated fixes and evaluations, closing the agent improvement loop for engineering teams.
Most agent observability feels like crash footage
The author argues that current agent observability provides a trace of actions but lacks runtime justification for why actions were permitted, which is critical for production deployments involving money, data, or communications.
I open-sourced a full agent observability stack: Record -> Inspect -> Diff -> Act (all MIT)
The article introduces an open-sourced agent observability stack with four MIT-licensed repositories that focus on extracting and inspecting model beliefs to enhance AI agent debugging and performance.