Your first day building agents

This journey is for the person who turns "the team keeps asking the same questions" into an agent that answers them. In fifteen minutes you create an agent, shape how it behaves, and watch it answer in chat — the loop every later agent refines.

You need the Editor role or higher (the Agents section is hidden from members) on a workspace where chat already answers — that is the quickstart.

1. 1

   Create the agent

   To start an agent teammates can pick in chat, open Agents in the sidebar and click Create agent. Name it for the job, not the technology — "Support Triage" beats "GPT Helper" — because the name is what teammates pick from the chat composer later.

2. 2

   Shape its identity

   The editor opens on the General tab: the display name teammates see, a one-line description, and the agent type. The switch that matters on day one is Visible in chat — without it the agent exists but nobody can pick it from the composer.

   

3. 3

   Write the instructions

   Open Instructions & models — the knob that matters most. Write one paragraph as if briefing a new colleague: the voice to answer in, the domain it owns, and the cases it should refuse. Concrete beats complete — you will refine after seeing real replies.

   

4. 4

   Bind the model

   The same tab binds the model: pick one from the workspace's configured providers, or leave routing on automatic so Tale resolves the best available model per request. Click Save — an Agent saved toast confirms the write.

5. 5

   Watch it answer

   Open New chat, pick your agent from the agent picker, and ask something squarely inside the instructions you wrote. Then ask something the instructions say to refuse.

   

Where you are now

You have shipped the smallest real agent: instructions, a model, a place in the picker. The full model behind what you touched is Agent concepts — instructions, knowledge, tools, and model as four knobs. The natural next build is your first agent end to end, which adds knowledge bindings and a real domain; after that, agents with knowledge and delegation between agents take the same loop further.