GlassFlow is specifically built for all your agent workflows. When your agent runs for 20 minutes and crashes at step 190, no worries — GlassFlow handles this.
The waterfall view every tool uses breaks down around 100 events. A 20-minute run with 500 tool calls produces an unreadable waterfall. GlassFlow uses a timeline model with anomaly detection, so you can scan hundreds of steps at a glance and jump straight to the one that matters.
GlassFlow expects to hear from running agents on a regular interval. A frozen agent — one that stopped making progress without crashing — is flagged immediately. In every other tool it looks identical to a slow healthy one.
Cost, latency, and token consumption update continuously as the agent runs. In existing tools these are only calculated on closed traces — if 90% of your agents are running, your dashboards reflect the minority that finished.
For always-on agents there is no trace end. GlassFlow’s session model handles open-ended runs, updating metrics continuously and keeping runs queryable at any point — not just after they finish.