FlowlinesGlossary
Plain definitions grounded in the real product: issues, users, production sessions, MCP journeys, and the evidence chain behind them.
Where execution observability inspects one LLM call, behavioral observability looks across sessions: which issues recur, who is affected, what users intended, and which original sessions show the pattern. It turns trace data into operating answers.
How do I know if my agent is working in production? ›Flowlines separates behavior issues from reliability errors. Each issue includes what happened, why it matters, the next step, technical detection details, where it fires, and the affected production sessions.
What signals does Flowlines detect out of the box? ›Drift often does not crash. It appears as a behavior issue that recurs across sessions, users, intents, or tool journeys. The useful unit of investigation is the pattern plus the original sessions, not an isolated response.
How do I detect agent drift over time? ›Silent failures do not throw an exception. Flowlines surfaces behavior issues separately from reliability errors, then links the finding to affected sessions so a team can inspect the actual conversation and tool path.
How do I catch silent failures in production? ›The Flowlines Home view includes user cohorts alongside active users, intents, issues, and sessions that need attention. Cohort context helps teams see whether a recurring issue is broad or concentrated among a particular group of users.
How do I segment my users by behavior? ›It appears on the Flowlines Home view next to analyzed chats, active users, and negative feedback. It gives operators a fast health read while the Issues and Search views provide the evidence behind the aggregate.
How do I know if my agent is working in production? ›Issue details in Flowlines connect the summary and next step to the exact sessions where the pattern occurred. This keeps a conclusion inspectable and gives engineering a concrete starting point for diagnosis.
How do I catch silent failures in production? ›Flowlines shows calls per session, repeated-call loops, failed sessions, and typical tool paths for each intent cluster. It distinguishes a technically successful call from a journey that actually helped the user.
See MCP observability ›The standard live path accepts OTLP/JSON or protobuf at the Flowlines traces endpoint and routes data using a namespace API key. Provider connectors can poll existing traces without replacing the source trace store.
How do I connect Flowlines to my agent? ›A successful tool status does not prove that the agent completed the task. Outcome coverage makes that gap visible and helps teams find where additional context is needed to judge success.
See MCP journey evidence ›Use Flowlines with your assistant