Asana AI Teammates: Assigning Work and Reviewing Results

Asana AI Teammates are AI agents you can add to a project and assign tasks to, alongside human team members. They accept assignments, complete drafts, and update task statuses. The practical question is how to write assignments they can follow, how to review their work, and what to do when the work continues outside Asana.

When your team uses a mix of tools and assistants, a shared record outside any one platform keeps the decisions, rules, and project context available to everyone. A tool like fenbs holds that shared record and connects to the assistants your team already uses.

What Asana AI Teammates can do

An AI Teammate in Asana can be assigned to tasks in a project. Depending on the task type and setup, the teammate can draft written content, summarize information, generate status updates, and complete structured work within Asana's interface. Check Asana's documentation↗ (opens in a new tab) for the current list of capabilities and supported plans, as these evolve.

AI Teammates work within Asana. They do not automatically access tools outside the Asana workspace. If a task requires reading from a document in Google Drive, looking up a customer record, or acting on information that lives somewhere else, a person needs to bring that information into the task or the teammate cannot use it.

How to write an assignment an AI Teammate can follow

An AI Teammate reads the task description and any attached context. Write the assignment as you would for a capable new employee who does not know your project history: describe the goal, the format you expect, and any constraints.

• State the goal clearly: "Write a two-paragraph summary of the Q3 results for the client update email."
• Specify the format: "Use bullet points. Each point should start with the metric name."
• Include necessary context in the task: paste in the data or figures the teammate will need.
• Set the acceptance condition: "The output is ready when it is under 150 words and covers revenue, churn, and NPS."

Reviewing AI Teammate output

Treat AI Teammate output as a draft, not a final deliverable. Read through it for accuracy, tone, and completeness before the task moves to the next stage. Check that any figures or facts it used came from the context you provided rather than from a guess.

If the output is consistently wrong in a particular way, update the task template for that type of work. A specific correction in the task description prevents the same error across every future assignment of that type.

When your team uses assistants outside Asana too

Asana AI Teammates work within Asana. If a developer is using Claude Code, a writer is using ChatGPT, and the project manager is using Asana's AI Teammate, each assistant sees a different slice of the project. Decisions made in one tool do not automatically reach the others.

A shared record that all those assistants can read solves this. In fenbs, you keep Decisions and rules, project context, and Where we left off in one place. Claude, ChatGPT, Cursor, and others connect over MCP and read the same record. The Asana Teammate works within Asana; fenbs keeps the shared context for the assistants outside it.

You do not need to move everything out of Asana for this to work. The two tools serve different purposes: Asana manages your team's tasks and workflows; fenbs holds the decisions, rules, and project context that all your connected assistants read. Keep task management in Asana for the work that benefits from its structure, and use the shared record for the information that needs to reach assistants that operate outside it.

What AI Teammates do not replace

AI Teammates draft, summarize, and complete structured tasks. They do not make decisions on the team's behalf, represent the team to a client, or carry judgment about which direction is right for the project. A human member should own the outcome of any work an AI Teammate contributes to.

One practical starting point is to keep a short context note in fenbs for each project your Asana AI Teammate works on. That note describes the client, the current goal, the relevant decisions, and what the last session produced. It takes a minute to maintain and saves the time of re-explaining that background every time a different assistant comes into the work.

How to do this with fenbs

1. Create a free account and add a team board for the project your Asana AI Teammate is working on.
2. Write the key decisions and rules in Decisions and rules: format preferences, off-limits actions, things that need human sign-off.
3. Add current tasks with enough context that any connected assistant can read the goal and the current state.
4. Connect the assistants your team uses from Integrations so they read the shared record before acting.
5. After each session, ask a connected assistant to update Where we left off so the record stays current for the next run.

For more on working with AI agents in a team setting, see what is an AI brain and AI employees.