đź“Ł Join us for an AI Teammates Show & Tell with the Security Architecture Team - April 28, 2026

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Hi Community :waving_hand:

AI Teammates are becoming an essential part of how we work inside Asana. When our own teams turn to AI Teammates to solve real challenges, you know the technology delivers. The Security Architecture Team’s story is a powerful example, and we’re excited to have them share it at our upcoming AI Teammates Show & Tell!

:sparkles: This webinar is open to the entire Asana Community, and we’d love for you to join us! :sparkles:

In this session, the Security Architecture Team will share how they built an AI Teammate that changed the way they work. But the real takeaway goes beyond security. You’ll see firsthand how flexible AI Teammates can be and walk away with practical ideas for creating one that fits your own team’s needs, no matter what kind of work you do.

:microphone: You’ll have two ways to participate:

  1. :sparkles: Submit your questions in advance through our pre-event form. These will be prioritized during the Q&A portion
  2. :speech_balloon: Ask follow-ups live in the Q&A box during the session

:backhand_index_pointing_right: Register here to save your spot!

:date: April 28, 2026

:eight_thirty: 8:30 am PT / 11:30 am ET / 4:30 pm BST


Want to get a head start? Check out this article to learn more about how the team is putting AI Teammates to work: Asana catches security risks before anyone writes a line of code with AI Teammates

This is a great chance to hear directly from a team putting AI Teammates to work and to connect with others in the community who are doing the same.

Looking forward to seeing you all there! :heart:

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These sessions were recorded and made available to those who couldn’t attend live? Thank you

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Hi @Enric_Moreno, yes! We’ll be posting the recap and link to the recording here in this thread later today. But the recording is already available to Ambassadors like you in Asanaverse. To access it, log into Asanaverse and click this link: Virtual Community Event Recordings, and from there, go to the section “Special Events :raising_hands:”. Hope this helps!

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Hi Community,

Thanks to everyone who joined our AI Teammates Show and Tell With the Asana Security Architecture Team on May 28th! We hope the session helped you get a better sense of how AI Teammates can support real work and make everyday workflows a little easier.

:videocassette: Missed the live session?

No worries if you couldn’t make it. Here’s the full recording so you can watch it whenever you have some free time:


:speech_balloon: Q&A Summary

Here are the questions we answered during the session:

Q: What if my team worries that AI will create extra review work instead of saving time?

A: That concern is very valid, and it’s one reason narrow use cases matter. If the AI Teammate is focused on the right kind of work, it should reduce effort on repetitive first-pass tasks rather than create more cleanup. Starting small helps teams find the right balance between speed and oversight. Teammates can be very verbose, so you may need to adjust the prompt a bit to help it focus on what matters. It’s an evolving process, and setting up custom fields can also help reduce review work. We also did testing internally before rolling it out.

Q: How do you know if the AI Teammate is actually helping the workflow?

A: Teams often look for signs like reduced back-and-forth, faster first drafts, more consistency in output, or time saved on repetitive tasks. It doesn’t always have to be a huge transformation right away, even making a common workflow smoother or more scalable can be a meaningful win. You can look at how quickly the AI Teammate reviews documentation or comments and responds. Before, there may have been a human doing all of that work. One common misconception is that AI improves the quality of work automatically. It actually improves coverage; the quality still depends on the quality of your instructions.

Q: What happens if someone gives it a messy or incomplete request?

A: A good rule of thumb is that rules are great for predictable, repeatable actions, while an AI Teammate is more helpful when the work involves judgment, interpretation, or generating content. For example, a rule can route a task when a field changes, but an AI Teammate can help summarize a request, draft a response, or turn a vague ask into a clearer next step. In our process, the AI checks for completeness, asks for additional information when needed, and helps restructure messy requests. That first step - having AI assess and reformat - can be a really helpful starting point.

Q: Let’s say I run an intake process and people submit requests in different formats every time. Could an AI Teammate help standardize that?

A: Yes, that’s exactly the kind of scenario where an AI Teammate can be especially helpful. It can review inconsistent requests, pull out the key details, and turn them into a more standardized format so the team can act faster.

Q: What kinds of requests are actually a good fit for an AI Teammate day to day?

A: The best use cases tend to be lightweight but recurring work — things like drafting updates, summarizing information, answering common process questions, organizing content, or helping teams move work forward faster. It’s especially useful when people are doing the same kind of thinking over and over, even if the exact request changes each time. They’re also as good as the amount of context they have, and they can span everything they have access to. That helps them find relevant information and support more informed decisions.

Q: Do people need to learn special prompts, or can they just ask in normal language?

A: In many cases, people can just ask in normal language. Usually the most effective requests are clear about the goal, audience, and format, but they don’t need to be overly technical. A lot of adoption comes from making the interaction feel natural instead of requiring people to learn a whole new system. We encourage people to interact with AI Teammates as if they were talking to a person. Prompting is still helpful for the people maintaining the teammate, since you may need to adjust it a bit to get the results you want. It’s a learning experience, and it evolves as you keep instructing it.

Q: Did you need to redesign your process first, or could you add an AI Teammate into an existing workflow?

A: No, we started by plugging it into the existing process.

Q: Why are AI Teammates unable to read custom fields in subtasks?

A: In Asana, subtasks are treated as separate task objects, and the AI surface doesn’t yet expose those subtask field values the same way it does for the parent task. If you need the AI to use that information, the usual workaround is to move the key field to the parent task, duplicate it onto the subtask body or title if needed, or have the AI work directly on the subtask instead of the parent.


Hope you have a great rest of your week!

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