Operations | Monitoring | ITSM | DevOps | Cloud

Most teams judge their AI coding agent on two things: the monthly bill and a feeling. The bill tells you what you spent and the feeling tells you whether it seems to be helping, but neither one tells you what the agent actually did. As these tools move into the critical path of how software ships, that gap is starting to matter. I wanted to replace the feeling with something I could measure and understand what shapes of work affects this bill, so I decided to run an experiment on myself.

Builder in the loop is a Mezmo interview series focused on the engineers, product leaders, and operators shaping AURA, an open-source, MCP-native agent harness for production operations. This installment features Tony Rogers, whose work on AURA is less about building new features and more about trying to break them before users can.

There was a time when “Opus” meant a classical composition and “Sonnet” was fourteen lines of Shakespeare you definitely did not read before the test. Now they’re model tiers, and every new release rewrites the economics of your engineering org whether you’re ready or not. Currently, your monthly total hides the crucial information you need to control and justify AI spend.