Blog/2026-07-10/Dashboards vs. Questions
Now that we have agents that can analyse our data for us, the question becomes whether to retain our dashboards or not. I think it's pretty clear that the standard answer is right: we need both these systems.
Dashboards are useful for awareness of current state and how it's evolved. An LLM-based query is useful for interrogating the data.
So, to see the general health of my system I use a dashboard, and to ask specific questions about something that's odd I would use an agent.
For instance, I run an ETL system for a client and every now and then I pop in to check the health of the system. I want to see how fast it's running, how many syncs have failed, and questions like that which are the same every time I look. I've found that the easiest way I have of getting a good idea of what's up is to make sure that my dashboard always has the same information in the same place and I specifically make sure that the page loads identically without any movement.
On the other hand, it's just as important to be able to ask ad-hoc whether some specific pipeline or subpopulation is performing differently or has a reason for change - and here an agent equipped with a read-only key and access to my Kubernetes cluster is quite powerful. One recent way I asked it was if a spike in failure rate that showed up on my dashboard was due to a new API change from Meta's marketing API. It was able to identify that it was a transient error from their servers rather than a persistent problem and provide me the evidence I needed to confirm.
