Chat

Direct an agent by hand — and promote what works into a workflow.

What chat is for

Chat is the interactive way to use the harness. You give an agent a task, watch it work, and redirect it as it goes.

It’s the right mode when you don’t yet know what you’re looking for. The agent doesn’t answer from an index — it investigates: reads files, runs commands, traces call paths, and follows the code until it can answer.

In a session an agent can:

• Explore your codebase — read, search, and trace how data flows through the application
• Run commands in its sandbox to test its own hypotheses
• Load skills for specialized procedures
• Delegate to sub-agents, so a broad question can fan out without losing the thread
• Track its plan as a running todo list you can watch
• Record findings and write patches for what it confirms

Ask open-ended questions — “are there any exposed endpoints in this service that shouldn’t be?” — or point it at something specific and ask it to dig in.

Watching it work

A session shows you what the agent is doing rather than just its conclusion:

• Tool calls appear as they run, with a status dot and the command or arguments, so you can see the reasoning path.
• The todo list shows the plan and what’s done, and disappears once everything completes.
• The sub-agent tree appears when the agent delegates, showing which children are running.
• The Tools panel on the right lists every tool call in the session; click one to jump to it in the transcript.

This visibility is the point. When an agent reaches a wrong conclusion, the tool trail usually shows exactly where it went sideways.

Sessions

Chats persist to your organization, so work doesn’t evaporate when you close the tab.

Action	Notes
New chat	Starts a fresh session
Rename	Sessions title themselves from your first message
Archive	Keeps the session read-only; unarchive to continue
Delete	Permanent, with a confirmation

A session survives a page reload mid-turn — reconnecting picks the running turn back up rather than losing it.

Choosing a model

The model picker in the header sets the model for the session, and you can switch mid-conversation.

Switching carries your context forward: Console summarizes the conversation so far and hands that summary to the new model, marking the switch point in the transcript. If a turn is in flight, you’ll be asked to confirm, since switching cancels it.

Use a faster model to explore, then switch to a more capable one for the hard part.

Cancelling a turn

Press Escape while a turn is running. The agent stops and the transcript notes the interruption, so you can redirect without starting over. Anything already recorded — findings, patches — stays.

Starting from a finding

The fastest way into a productive session is from a finding. Start a chat on any finding opens a session with the affected code, the agent’s reasoning, and any generated patch already loaded, and you type your question in the same step.

Promote it to a workflow

Chat is exploratory by design. Once you’ve asked the same question a third time, it belongs in a workflow:

In chat	As a workflow
You pick the repository each time	The trigger names the repositories
You type the task	The workflow’s description and agent chain encode it
You read the answer	Outputs deliver it to the pull request
Runs when you remember	Runs on every pull request

The translation is usually direct: the prompt you refined becomes the workflow description, and the agents you found useful become the chain.

Next steps

The CLI

Same agents, against your local working directory.

Build a workflow

Automate what worked in chat.