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Collaboration is critical to teaming, but how do we do it so that we feel effective and unburdened? My name is Matt Abrahams and I teach strategic communication at Stanford Graduate School of Business. Welcome to Think Fast Talk Smart, the podcast. Today I look forward to chatting with Molly Sands. Molly is a behavioral scientist and the head of the Teamwork lab at Atlassian. She and her team conduct research into best practices for high performing teams. Her work focuses on understanding how teams can collaborate more effectively in a distributed and hybrid work environment, especially in the world of AI. Welcome Molly. I have long admired the work of your team and I'm really excited to have a conversation about the work you do.
B
Thank you so much. I'm excited to be here.
A
Okay, shall we get started?
B
Let's do it.
A
Awesome. So the teamwork lab studies many aspects of teaming and productivity. How do you determine what to study? And do you have some guiding principles for the work that you do?
B
I am really Focused on a few things in our work, we have a couple key beliefs about teamwork. And one is that people can accomplish a lot more together when they work well together. And the other is that in most companies today, it is way too hard to work together. And the more that we can get on the same page about what we're trying to achieve together and how we're going to get there, the more effective we are. Those are sort of my guiding philosophies around how do teams work effectively together? And we anchor our research in a couple areas. So one, my team, the teamwork lab at Atlassian, we study teams across the world. So we will survey thousands of teams, we'll talk to leaders, we'll do lots of different types of research, and then we also study teams within the company. And within Atlassian, we're really able to get in the mix with teams and change how they work and measure lots of different types outcomes. And so from those two approaches, we get a really good sense of what are the challenges that most people are facing today and that all of our customers really care about and need us to come up with better solutions for. And then we also have this amazing experimental pool and so we can start to really change ways of working and then see how that impacts outcomes.
A
In that research that you do, at least trying to identify what the big challenges are there, two or three that stand out in terms of what really teams struggle with.
B
Yeah. So goals, what actually matters is huge for teams and how people invest their time in companies today. And so we spend a lot of time studying and thinking about how do we get clear on what we're trying to do and how do we invest our times in ways that are actually meaningful and help us do real work and not just talk about work.
A
Do you have suggestions for how people can help identify their goals? And then I know something you spend a lot of time on is alignment, getting people aligned to those goals. Because I've been in several organizations where I thought we were working in one direction. It turns out others thought we were working in another. So how do we determine what those goals are and how do we get alignment towards them?
B
So I think a lot of the best work happens when you start by asking why. Right. And you are really focused on what are we, what do we want the true outcome to look like? And in a lot of companies and a lot of of teams today, people get activities confused with outcomes. Right. It's less about what is the business problem we're solving, what is the customer problem we're Solving and more about what activities are we doing to get there. And so getting really clear about the problems is really the first step to having a great strategy. And then being more explicit about how are we going to get there and getting that input, getting people to really understand why is this a problem, why do we want to solve it, and how are we uniquely position to do that. All of that product thinking is really how I think about it tends to help teams get much better aligned. And then being explicit. Right. There's so many moments you just referenced times of thinking. Well, I thought we were all on the same page, but I never said it out loud. And your colleagues and your teammates are not mind readers. So the more that we can really map this out together, the more effective our teams tend to be.
A
I think taking the time to really reflect on what is important here, what's the problem we're solving, why are we doing this? And then making it explicit by documenting it and communicating it are really important. And I have found in the practice that I do and when I go into organizations, having people just share what is the goal and have everybody give their version of it, people are often very surprised that they weren't aligned so explicitly. Not just providing it, but making sure people share their take on it can be really helpful to you.
B
Yeah. I always tell managers or anyone that's leading a project, one of the first things you should do is ask everyone to tell you what they think you're trying to accomplish.
A
And a powerful question I found I'd be curious to get your input on it is asking people, what does success look like? What does success of this team look like?
B
Yeah, we actually start every project we do in our platform. We have a way that people can document this. But what are we doing, why are we doing it? And what does success look like? And just by asking those three questions and writing something up that everyone working on that project reads and thinks about and gives feedback on, that is such a fast way to actually accelerate everything that happens from that point on.
A
Yeah. What are we doing? Why is it important? And what does success look like? Really important questions. I think another important question, and I'm sure this won't surprise you, is I'd love to talk about AI and AI's role. It's certainly affecting work, period, but also in teams. Your research shows a shift towards using AI as a collaborator. Can you help us understand what that looks like? What recommendations do you have to leverage AI to help teams be more successful?
B
One of the things we saw earliest as AI was Really taking hold of how we do work was that people's mindset around it mattered in a huge way. And so if you really think of AI as a collaborator rather than just a doer, but you're actually thinking about AI more like a teammate and someone that can push your thinking forward and that you can go back and forth with, those are the people that are seeing much better outcomes, and that's across a lot of things. So they're seeing more efficiency in the work they're doing, they're able to do tasks faster, but those folks are also seeing better quality work and their teams are viewing them as more innovative. And some of the promise of AI that we're all excited about is really coming true for the people that start to think about AI in that collaborative mindset, rather than simply as, oh, well, I can delegate and automate a few things.
A
Can you give us a few examples of what true collaboration with AI might look like? Does it have a seat at the table? Is it in the zoom meeting with me? Am I asking it questions like a colleague? What does that look like?
B
So I think it is great to think of AI as a quick way to get some information that you need, but it's also about that back and forth interaction. So actually creating things and not just taking the first output that you get, but actually going back and forth, debating, asking questions, having AI push your thinking and pushing back too, saying, I don't think this is right. I know about this other thing. How do we incorporate this? And much in the way you would go about collaborating with other people, where it is a back and forth.
A
We had a really insightful episode we did with Jeremy Uttley where we talked about how treating AI as a conversation partner, not as a search engine, really can change the dynamic. And it sounds like that's what you're advocating for, is really engage in dialogue, talk to it and challenge it and it will help you benefit. Can you give us an example of using AI as a tool to help you? I read about or listened to an episode of something where Atlassian has built an onboarding tool out of AI to help people get started and be more productive.
B
Yeah, We've had great success with onboarding with an AI buddy. So we built what we call her name is Nora and new Lassian, an onboarding Rovo agent. And Nora has access to all of the data that we have about policies and people programs and how we run our company, how people get set up in our systems. And when our new hires join, they have a variety of touch points with other humans. But we also give them access to Nora and say, hey, if you have any of those basic HR questions, ask her if you have any questions about how things operate in this company. If you're wondering who to ask about this, if you don't know how to file a ticket, just all of those logistical things that come up as you're joining and you don't really want to go to your brand new manager and be like, oh, I have this like really annoying list of 25 questions about logistical things. You want to be showing up as strategic in those conversations. And Nora is your buddy for everything that you need. And people feel a lot more comfortable asking questions. They don't worry about how AI is going to perceive those questions. So they really ask everything they want. And we've also found that this has vastly increased how much people use AI as a collaborator as they onboard into their new role.
A
So it's an on ramp to helping them feel comfortable using AI as a tool to help them with their work. I like that.
B
Yeah. And so we've seen a really strong relationship there that just this initial touch point sets that expectation that this is a way that we work in this company and this is how you're going to get information.
A
I know when I would onboard on companies I would always feel so embarrassed because I couldn't remember something I was taught and I'd have to go back and ask and I feel like I'm trying to set a good impression and now everybody thinks I can't remember anything. To have a tool like that would be helpful. So finding niche needs and building AI tools to help, not only help with whatever that need was, but it also helps people feel more comfortable using AI as a collaborator.
B
Yeah. And I think it's important for companies to think about where they have really robust knowledge. So AI works the best when it has access to the right information. And so in HR policies tend to be really carefully documented. You actually do need to have good resources for any new employee about what your benefits look like, about how people manage different systems, about how they integrate into teams. We're able to pretty easily create customized onboarding plans using AI as well. And so when all that information is available, you can easily build on top of it. And so, so I usually encourage leaders to think about where are pockets within your company that you have that great data already there and to think about those as use cases where you can get some clear wins.
A
Yeah, clear easy pilot wins and really get that momentum going. I appreciate that a lot. As you And I talked about before we came on the air, meetings can be really useful for teaming. But many of us struggle with the meetings we have. We feel like they're too many. We feel like we're victimized by poor meetings. They zap our time. I know you have done research into meetings and actually at Atlassian, you guys have some really interesting approaches. I know you use loom videos for asynchronous updates. You have what are called page led meetings. Can you define these two approaches? Because I think they're really unique and could be helpful for many. And then what other advice do you have generally in terms of how we meet better, when we meet better, who we meet with. So I'd love to get specific on what you all have done because I think it transfers to many people and I just love generally what your research has found.
B
Meetings are one of the biggest challenges in people's jobs. Right? Anytime that we run research about what's holding people back from achieving what they want to at work, meetings are the number one thing. It's the biggest barrier to productivity. But it's essential that we talk to each other. That's how we come up with great ideas. That's how we create together. There are so many things that are so important about that. And in the last few years, as companies have embraced much more distributed global work, people have brought a lot of the meeting habits that we did not love in the office, online with them. And so now we're all stuck in these back to back meetings all day long. And what we really think about is taking control of our time and solving the problems that meetings are supposed to solve in different, more efficient and more effective ways. And so I think people should think about having kind of three types of time in their day. One is time for deep work. You really do need time to think, to write, to create. Depending on what your job is, that time will look different. But the time where you're using your brain in the most powerful ways and now you've got AI as a partner during that time as well. And then we should have meetings. And at Atlassian, we do page led meetings and we've done a lot of research on this idea. And the basic idea is that you put together a really clear synopsis of what everyone needs to know as context to have a conversation. This works really well when you're trying to make a decision, when you're trying to align people, when you want feedback on a perspective or path forward. So any of those kinds of meetings where you really are bringing a group together to say let's chart the path forward or make sure everyone's at least aware of it. Those moments work really great for this page led meeting concept. And the pages should be short. Pages should be no more than a five minute read. You don't want people reading for hours together.
A
And do people read those when they all convene together or is the expectation that you read them in advance? Cause I know Amazon does in the room. We all read.
B
Yes, we do in the room as well. The prereads are tough. People don't do them. You're not sure if people did them. You maybe did it, but it was four days ago and now that's not top of mind for you. So it's a great way at the beginning to just set the context for everyone and we ask people to comment.
A
So you said there were three ways of using time. I'd love to revisit those. And then I hate update meetings. And I know you all have an interesting way of getting that information that I think everybody should consider.
B
Yes. Okay, so three ways of using time. One is traditional meetings, another is deep work. And the third is. And this sounds so silly, but collaboration, more fluid collaboration. And what we've seen in people trying to fix meetings is that some teams have shown shifted to way too much structure. And so every time that you're bringing people together to talk, it is like very agenda led and someone is giving a presentation and that's not the moment where you can really create together. And so especially if you're working on distributed teams where people are in lots of different locations having these more fluid moments where you can come together and really just work, that could be pair programming, that could be writing a page together, that could be doing a creative brief or coming up with concepts, brainstorming all these different ways that we really do work together. And I think people need to start to think about that as a category that is different from a formal structured meeting, but make a lot more time for that kind of collaborative work.
A
So it's this notion of deep time where you're by yourself, maybe with an AI collaborator working on something. It's the typical traditional structured meeting led with pages where you all sync up on what it is we're talking about. And then the more collaborative ideative time where people come together and can really have the freedom to do the work that needs to be done.
B
Exactly. And in order to have time to do all of those things, you cannot be in back to back standing meetings where you are giving status updates and people don't have meetings for no reason, even if they're not effective, which most of the time they tell us they are not. They're trying to solve a problem. And usually that problem is getting or sharing information. And so we do a lot of asynchronous video. We have a tool called loom that we use, which lets you record yourself talking. You can screen record, you can just record a video of you. And that captures a lot more signal than simply a written update. We find that people feel more connected to other people when they communicate through video and that there's a lot of benefits to giving more of that personal touch to information. And so we ask people to usually do their updates, our status updates, either through writing or through limb videos, depending on how much context they need to share. And we align all of our work to goals. So there's a whole system and infrastructure around goals. What are teams working on? Where do you have shared goals? And this creates a lot of that clarity that we were talking about in the beginning, right, of what are we trying to achieve together? And just repeatedly having people look at and remind themselves of that information through our ways of sharing updates is huge for staying on the same page about what we're really trying to achieve.
A
I really like that idea of recording the update. Not only do you get more information, as you said, more signal, but people can take in that information when they need it. And so I will often coach people in the organizations I go into where people are just so frustrated with these long update meetings where maybe 10% is useful to you. Have everybody record their sessions in a structured way so you know you're getting the same type of information. And the requirement is that you just watch it in advance of the meeting so when you come together, you can actually have a discussion about what you learned rather than wasting the time of hearing everybody's update. And I really like that. And I also like what you said about tying these into the broader goal and always reminding people how these things connect. So I think those are very useful tools to help people be more efficient and effective in their meetings. So the idea is not get rid of all the meetings. The idea is maximize the utility of the meetings for what they're meant for. So thank you for that. We'll be right back to finish our conversation. But first we're going to take a quick break for a message from our sponsors. These sponsorships support the cost of making our show, allowing us to bring it to you free of charge.
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So, Molly, before we end, I'd like to ask everybody three questions. One, I make up just for you and two, I've been asking everybody for as long as this podcast has gone on. Are you up for that?
B
I am up for that.
A
I am curious what is something that your team is currently studying or working on that has you really excited?
B
We are working on a lot of research about how you really make AI part of the team. So we see people are using AI more and more at work and in their personal lives, but how do we solve team level challenges and problems, the things that are really hard about working together? And so we are doing some really interesting interventions right now with teams where we embed AI not just as an individual collaborator for everyone on the team, but also into some of these team processes and ways of working. And I'm very excited to see more of what we learn from that.
A
I would love for you, when you start getting results, to have you share some of that and we will try to get that information out because I see that as a big unlock, but I also see it as something that could be a real challenge. So it'll be really interesting to find what you learn. Question number two, who is a communicator that you admire and why?
B
I really admire Molly Graham. She, I think is a fantastic communicator in really synthesizing some of the core things that are hard about work and putting analogies behind them that make them very memorable. And I've been really impressed with her work. She's most well known for the give away your Legos piece that she's written about how to scale in companies and how to grow. But I think all of her content is so actionable and memorable.
A
So I like that it's actionable. That's what we're all about is practical and tactical actions. But it sounds like the ability to synthesize and to make things accessible through things like analogies, which are wonderful skills for anybody hoping to be a good communicator. Final question. What are the first three ingredients that go into a successful communication recipe?
B
Making it resonant. You want people to immediately feel what you're talking about. Clarity and I think, passion. When you care about the topic, when you care about what your message is, that really comes through in the way you communicate.
A
Making it resonant, relevant, salient, really important, being clear. You've talked about clarity a lot today. Clarity of goal, alignment to goal, clarity of messages and then passion. And you clearly are passionate about helping people collaborate and work better in teams. Thank you for the best practices. Thank you for helping us understand the details of what goes into collaboration and effective work. And thank you for your time in helping all of us be better in our teaming.
B
Yeah, thank you so much for having me and for this wonderful discussion.
A
Thank you for joining us for another episode of Think Fast Talk Smart, the podcast. To learn more about teams and teaming, please listen to episode 242 with Colin Fisher. This episode was produced by Kathryn Reed, Ryan Campos and me, Matt Abraham. Our music is from Floyd Wonder. With special thanks to the Podium podcast company. Please find us on YouTube and wherever you get your podcasts. Be sure to subscribe and rate us. Also follow us on LinkedIn, TikTok and Instagram and check out fastersmarterio for deep dive videos, English language learning content and our newsletter. Please consider our Premium offering for extended deep thinks episodes, AMAs, Ask Matt anythings, and much more at Fastersmarter IO Premium.
Thanks for spending time with us today. I hope you took as much value as I did from this episode. There were so many more important ideas that we have created a Quick Thinks episode that continues my conversation on this important topic. Hope you'll give it a listen. And thanks as always for being part of our thinkfast Talk Smart community.
Episode 248 – Better Together: How to Supercharge Your Team’s Productivity
Host: Matt Abrahams
Guest: Molly Sands, Behavioral Scientist & Head of the Teamwork Lab at Atlassian
Released: December 9, 2025
This episode delves into the science and practices behind effective team collaboration and productivity. Matt Abrahams welcomes Molly Sands from Atlassian’s Teamwork Lab to explore actionable strategies for setting goals, fostering alignment, integrating AI as a true collaborator, and making meetings matter more. Practical examples from Atlassian’s own experimentation illuminate paths to supercharging your team’s output in today’s distributed and hybrid work environments.
“The more that we can get on the same page about what we’re trying to achieve together and how we’re going to get there, the more effective we are.”
— Molly Sands (03:08)
“I always tell managers or anyone that's leading a project, one of the first things you should do is ask everyone to tell you what they think you're trying to accomplish.”
— Molly Sands (06:39)
“Just by asking those three questions and writing something up that everyone working on that project reads and thinks about and gives feedback on, that is such a fast way to actually accelerate everything that happens from that point on.”
— Molly Sands (06:55)
“If you really think of AI as a collaborator rather than just a doer… those are the people that are seeing much better outcomes.”
— Molly Sands (07:44)
"We've had great success with onboarding with an AI buddy… People feel a lot more comfortable asking questions. They don't worry about how AI is going to perceive those questions. So they really ask everything they want.”
— Molly Sands (09:55)
“Meetings are the number one thing… the biggest barrier to productivity. But it’s essential that we talk to each other. That’s how we come up with great ideas.”
— Molly Sands (13:36)
“People don’t have meetings for no reason, even if they’re not effective… usually that problem is getting or sharing information.”
— Molly Sands (17:39)
“Have everybody record their sessions in a structured way… The requirement is that you just watch it in advance of the meeting so when you come together, you can actually have a discussion about what you learned rather than wasting the time of hearing everybody’s update.”
— Matt Abrahams (19:08)
“We are doing some really interesting interventions right now with teams where we embed AI not just as an individual collaborator... but also into some of these team processes and ways of working.”
— Molly Sands (21:36)
“Making it resonant. You want people to immediately feel what you’re talking about. Clarity. And I think, passion.”
— Molly Sands (23:21)
| Timestamp | Speaker | Quote/Insight | |-----------|---------------|------------------------------------------------------------------------------------------------------| | 03:08 | Molly Sands | On getting teams on the same page: “The more that we can get on the same page... the more effective we are.” | | 06:39 | Molly Sands | On alignment: “I always tell managers… ask everyone to tell you what they think you’re trying to accomplish.” | | 07:44 | Molly Sands | On AI mindset: “If you really think of AI as a collaborator… you’re seeing much better outcomes.” | | 09:55 | Molly Sands | On “Nora” the AI onboarding buddy: “People feel a lot more comfortable asking questions… So they really ask everything they want.” | | 13:36 | Molly Sands | On meetings: “Meetings are the number one thing… the biggest barrier to productivity. But it’s essential that we talk to each other.” | | 17:39 | Molly Sands | On asynchronous updates: “People don’t have meetings for no reason, even if they’re not effective… usually that problem is getting or sharing information.” | | 19:08 | Matt Abrahams | On structured video updates: “Have everybody record their sessions… so when you come together, you can actually have a discussion about what you learned...” | | 21:36 | Molly Sands | On future research: “We are doing some really interesting interventions right now with teams where we embed AI… into some of these team processes.” | | 23:21 | Molly Sands | On communication: “Making it resonant…Clarity… Passion.” |
This episode equips listeners with grounded, evidence-based tactics to make teams “better together”—translating behavioral science into practical steps for clarity, alignment, and creative collaboration in the modern workplace.