I Used Three AI Agents on a Real Project. Here's What Each One Is Actually Good At.

The Setup I've been building k3d-manager — a shell CLI that stands up a full local Kubernetes stack: Vault, ESO, OpenLDAP, Istio, Jenkins, ArgoCD, Keycloak. The kind of thing that takes a week to wire up manually. I wanted it done in one command. At some point the project got complex enough that I stopped being able to hold it all in my head at once. So I brought in three agents: Claude handles planning and code review. Codex writes and modifies code. Gemini runs commands on the live cluster and verifies things actually work. That's been the theory for about three months. Here's what I've actually observed. Each Agent Has a Real Strength Profile This is the part most AI workflow articles skip. They talk about what agents can do. I want to talk about what each one is reliably good at versus where they consistently break down. Codex is a strong implementer. Give it a well-specified task — "add this function," "change these three lines," "apply this YAML fix" — and it does it cleanly. It