Give two people the same agent and the same task and you'll often get two different results. The usual assumption is that the better result came from a better prompt. Just as often, it came from a better-defined agent — one with a stable identity underneath the prompt: a voice it keeps, values it decides by, a role it stays inside. The other person is re-establishing who the agent is supposed to be at the start of every session, and it shows.

Identity is the pillar people skip. They pour effort into memory and tools and leave the agent's self to whatever the base model defaults to — which is how you end up with the same bland, hedge-everything, sounds-like-every-other-AI assistant no matter what you bolt onto it. This is a field guide to building the self on purpose: the constitution that anchors it, the voice that makes it recognizable, the values that steer it when the task is ambiguous, and the boundaries that give it a shape at all. We keep it in plain files (legible, versioned, portable), scale it across a fleet where every agent is a distinct citizen with shared values, and — the hard part — evolve a self over time without it drifting into someone else.

It's the third leg of a trilogy with Agent Memory and the skills pillar, all introduced in Building Your Agentic OS: identity is the who, memory is the what-happened, skills are the how. Get identity right and the agent stops feeling like a tool you operate and starts feeling like someone you work with.

This is a living document and will be updated as the tools and patterns evolve.