Observability

Byscientist
Close-up view of binoculars on a surface with sunset reflection in lenses.

Observability is important for AI and AI tools. It is the ability to monitor them for token usage, response quality and model drift. Typically, an AI system is monitored through logs, traces and metrics but an AI system on AI agent may need other metrics. Troubleshooting a complex AI system that produces its output probabilistically is much more difficult since subtle changes in the input layer may change the output and hence a very different observability metric is needed. The requirement may be simple – decrease the hallucinations, and latency while removing any observable bottlenecks.

Check out this AI observability video : https://www.youtube.com/watch?v=v_SPcIGOJvs

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