Guides
A guide to monitoring your software when AI agents write, test, ship and debug it, with a directory of 90 monitoring and developer tools checked for what an agent can get out of each one.
If your team uses AI coding agents such as Claude Code or Cursor, five things need watching in new ways: the code they write, the pipelines that ship it, the systems that run it, the agents themselves, and the bill. This guide has one page for each. We call them stages because they follow the order of the work.
The five stages
Each stage page has four parts: what changes when an agent does the work, the numbers worth tracking (the guide calls them signals), three levels from doing it by hand to letting the system do it, and the tools that cover the stage. Use the levels to see where your team is and what the next step is.
Agents writing code, generating tests and reviewing pull requests as one loop.
Pipelines running far more often, and releases compressing from weeks to hours.
Infrastructure, APM, logs, traces, profiling and incident response, with an agent as the reader.
Watching the agents themselves: hallucination, drift, eval scores and what a session actually did.
Token cost, model routing and spend governance.
The vendor directory
An MCP server is the connector that lets an AI coding agent query a tool such as Datadog or Grafana in plain English. Each directory page checks one vendor's server for what an agent can ask it and where the answers come back cut short with no warning. 63 of the 90 vendors have a working server of their own.