Your AI team, each one their own job
Different agents handle different work — research, writing, code, ops — all running in parallel, never stepping on each other.
Different agents handle different work — research, writing, code, ops — all running in parallel, never stepping on each other.
Researcher does the digging, Coder writes the code, Writer drafts the copy, Operator watches the system. Each one is a separate agent with its own settings, its own conversation history, its own files. You pick whoever you need for the task.
An agent isn't just a chat window — it has its own sandbox to run code, its own file area, its own scheduled tasks, its own permission boundary. Coder editing the codebase doesn't touch Researcher's sources. No bleed.
An agent can delegate sub-tasks to another agent — Writer pulls the report from Researcher to draft a blog, Operator asks Coder to run a data script. Complex jobs flow naturally.
Let me grab the draft from Researcher, then rewrite it as a blog:
Done — 1,500 words with a cover image, archived to Drive.
Spin up four agents in minutes — research, writing, code and ops, all covered.