Hey everyone,
I’m Arnab, Chief Product Officer at Asana. I’ve been leading our work on AI Teammates, and now that the product is generally available, I wanted to share something with this community: a pair of hands-on walkthroughs I personally recorded to show how AI Teammates actually work — end to end, in realistic workflows.
These aren’t polished marketing reels. They’re detailed, step-by-step recordings that walk through real scenarios so you can see exactly how AI Teammates collaborate with people and tools to move work forward.
What you’ll see
Both walkthroughs follow a marketing team preparing to launch a major seasonal campaign. Together, they cover the full arc — from strategic planning to creative production to launch readiness — and show how AI Teammates handle the kind of cross-functional coordination that usually takes weeks:
1. From campaign kickoff to working prototypes
This one starts with a marketing leader kicking off a summer campaign. Rather than spending weeks getting a brief drafted and approved, here’s what happens:
- A Campaign Brief Writer AI Teammate gets assigned the work and starts immediately — reviewing past campaign performance, identifying objectives, and drafting a comprehensive campaign brief
- The brief lives in Google Docs, where multiple stakeholders (VP of Marketing, Creative Director, Finance) leave feedback directly in the document
- The AI Teammate incorporates feedback from multiple people across multiple tools. This is the multiplayer collaboration that makes AI Teammates fundamentally different from a personal copilot — they’re shared collaborators embedded in your team’s actual workflow, not a single-player productivity tool
- Once the marketing lead approves the brief, a Creative Coder AI Teammate automatically picks up the next task — translating the campaign strategy into a working HTML landing page prototype
- The full journey from campaign kickoff to working creative prototypes happens in days, not weeks
Watch the walkthrough:
2. Proactive launch readiness monitoring
This picks up later in the campaign lifecycle, when the team is nearing launch and cross-functional coordination gets critical:
- A Launch Planner AI Teammate runs a recurring monitoring task, continuously checking project timelines, engineering backlogs, standup transcripts, and capacity data
- It detects a risk: an API migration is slipping, and there’s a 40-hour engineering capacity gap that could delay the entire launch
- Instead of just surfacing the problem, the teammate proposes specific operational actions — reprioritize the migration task and reassign one backend engineer to close the gap
- The team reviews, agrees, and the work gets updated. Risk resolved, launch timeline back on track
This is what it looks like when AI reasons across your Work Graph — connecting signals across projects, meeting notes, and team capacity rather than just analyzing a single document.
Watch the walkthrough:
Why I wanted to share this
A lot of the conversation about AI agents focuses on individual productivity — helping one person write faster or summarize a meeting. That’s useful, but it’s not the hard problem.
The hard problem is coordination: the weeks lost chasing approvals, aligning stakeholders, and manually tracking dependencies across teams and tools. AI Teammates are built for exactly that. They’re not personal assistants — they’re co-workers that operate within your team’s shared workflows, with the same visibility and permissions as any human teammate.
What makes this possible is Asana’s Work Graph — the structured context layer that gives AI Teammates an understanding of your projects, team relationships, and how work actually flows across your organization. That context is what enables them to do meaningful, grounded work rather than produce generic output.
I hope these walkthroughs give you a concrete feel for what’s possible. I’d love to hear how you’re thinking about putting AI Teammates to work — and what you’d want to see next.