March 29, 2026
cout, Strike, Repeat: Why Five Is the Magic Team Number
Atlassian just cut 1,600 people — including the teams building their own AI. What does that signal for the rest of us? Stephen and Lauren dig into the hidden coordination tax bleeding most teams dry, why the number five keeps showing up as the sweet spot for high-performing teams, and the emerging scout/strike model that's letting small groups outrun large ones. Plus: uncomfortable leadership truths, and what you can actually do about all of this today.
00:00 Intro
01:35 Coordination Tax
06:15 Team Math
09:40 Magic Five
14:45 Scout & Strike
21:10 Leadership
28:33 Wrap Up
WEBVTT
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Atlassian just laid off sixteen hundred people, including some of the teams that were building their own AI.
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They cut the people closest to this technology they said they couldn't survive without.
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What might that mean for the teams that you're in right now, and what can you do about it?
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I'm Steven, and this is the AI Transition, and with me as always, Lauren.
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Hey Stephen, this is a good one.
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Let's dig into today.
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Yes, yes.
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I'm quite quite close to the bone, and we we know people who've been involved with this as well.
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Um and we're we're seeing this happening in other organizations too.
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So this is a very relevant one.
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We're gonna dive into quite a few interesting things that I think um will be affecting and/or touching on pretty much everyone listening in a moment.
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So uh the hidden tax that's been kind of bleeding organizations' drive for decades, tax, the coordination tax.
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We'll dig into that.
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Um, why the number five keeps showing up as the magic number?
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We're going a bit woo-woo, Stephen.
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Magical.
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No, I'm kidding.
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Um some new archetypes that are appearing in organizations, some new, I guess, mindsets or squad structures that we're seeing emerge, um, some uncomfortable leadership conversations.
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And then as always, we try to give you some practical tips that you can take away.
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Something practical after after this, after we after we scare the bejesus out of most people, then we then we come back and say, hey, look, there is something you can do.
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Maybe just a small thing, but there's still something that we can do.
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So let's dive in.
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So we uh look, you know, don't we love the word tax?
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Um, especially these tired ages.
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So the coordination tax, this is where, you know, uh we've got all the overheads that we we deal with with our day-to-day work.
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So this is meeting preparation, you know, documenting decisions, cross-team ticketing, you know, where we've got all these meetings, we're trying to get all the knowledge.
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Um and some of the interesting ta stats around this one, again, it's not a new problem, but it's growing, is that we've got 60% of our time being spent on coordinating the work and then only about 40% available for execution.
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Can can can I just put some health healthy skepticism on those numbers, right?
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And there's been lots of um lots of different studies that have been showing this.
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I think it's a lot more than 60% of the city.
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I was gonna say, what do you reckon?
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I actually think it's more like 80.
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Yeah.
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But look, look, look seriously.
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But when when you talk to most people, what they end up doing most of the day, it's it's the meetings, it's the chatting to people, it's the sending messages, it's replying to emails, it's having right and all of that, nearly all of that, is all based on coordination about who's doing what, when and and what's going on.
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Um actually doing the stuff, that's really a small part of the for most people's jobs.
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It really is.
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And you know, particularly, dare I say, for people like you and I, where we're trying to help teams, you know, work more efficiently, that's that biggest challenge of breaking that habit of I just need a meeting, I need to talk about this, I need to bring people together.
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Um, and part of the challenge we've got with AI now is that you've got much more output without any of the structural change, right?
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So if we know that even since uh good old 2020, that this meeting load, and it's just a constant pattern for all of us, is increasingly, you know, growing significantly as these teams get bigger, you're losing that shared context.
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And now you've got output growing as well.
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And the rise of um this new phrase of the agentic tar pit.
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Quite like that one, to be honest.
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It's quite a visual, isn't it?
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Because I I I do feel myself um kind of stuck in that tar pit quite a lot these days.
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Beat getting pulled deeper into the tar.
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Yeah.
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You know, where you've got all this activity, not so much the outcomes, like as people starting to figure out how to use these tools.
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And, you know, I've run my meeting with my, you know, AI and tracking all my transcription.
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Now I've got to update all these notes.
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And so you've got this, you know, smart more output and it's reducing some of that manual, but still it's not helping you to coordinate the work.
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You've still got that coordination cost.
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What I'm seeing in a lot of teams these days is that, you know, and these aren't kind of frontier teams that are kind of you know agentic in AI first.
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You know, they're you know kind of like you're standard teams within within within large organizations.
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Any AI usage so far just now is mainly been around to simplify some of the manual tasks that they're already doing.
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So, for example, I'm using Copilot to make a summary of a meeting, right?
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Uh and so instead of taking notes yourself, people are using that and then cutting and pasting it that into a file somewhere, which means that while teams are getting bigger, we're just automating some of that documentation part of it, but not overly fixing a lot of the problems.
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Yeah, are we actually optimizing any anything at the end of the day?
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We're creating a lot more content, but are we actually thinking about how we need to interact with each other more efficiently?
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Yeah.
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Well, whereas teams that are kind of been using this a a bit more, it's not just about automating or AI fying or identifying or whatever words you you want to use there of the existing processes.
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It's actually looking at those and then saying, well, actually, do we need to do that?
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Can we not have, you know, the bots take that part of it, that part of the coordination?
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Do we really need to be doing this?
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One of the other things I I would throw in here is that I've just seen teams getting larger and larger, particularly since the pandemic and since the vast majority of corporate teams are meeting in Microsoft Teams online.
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There's no restriction now about how many people you can have a team in order to physically get in a room anymore.
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So you can have dozens and dozens of people now.
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And that's quite common.
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And we know that we're gonna start to talk about this this uh number of five shortly, but we know the more people we add into that mix, the more lines of communication that you've got.
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And you're creating more and more of that output.
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And how do you actually bring it together to optimize it?
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So hence this agentic tar pit, because it's kind of pulling you in.
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So we're not yet seeing those um uh I guess benefits of introducing these tools if we're not looking at the broader picture of how we actually coordinate.
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Well, why don't we kind of move on to that and that kind of that mathematics of the number five thing we see popping up quite a lot?
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But before we get to the number five, um, what I've been seeing, as I was saying in the previous section there, is just the number of people that are getting added into teams just now.
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So the so the overheads that go is when you've got eight people, twelve people, fifteen people, twenty-five people, right?
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The communication paths that trying to coordinate all of them, if you try and draw that out in a diagram of where the communication is going, it's completely crazy.
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Oh, it is.
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And like just for the simple maths, like if you've got five, it's 10 pathways, right?
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Once you hit 20, it's rapidly growing to around 190, 200.
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You're hitting 50, we're talking 1200.
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And you and I regularly work in, I'm working, well, maybe we will keep names out of it.
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But where people, how big is this team getting?
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Oh, yeah, it's gonna get up to about 50.
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And you're like, okay, well, maybe it's time to scale into some streams and teach, oh, I'm not sure about that.
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Like, we want to make sure.
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So once you think about how inefficient hundred lines of communications, which is crazy.
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So it's either overwhelmed by the number of passive communications or there's just no communication going on.
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And what I mean by that is so there's a there was a couple of meetings I that I attended um earlier this week and went on, and there was, I think there was 18 people in this one team who were uh uh having this discussion.
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But the reality was there was three people in that meeting having the discussion.
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Only three, right?
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The other, the other 14, 15 of them were cameras off, not really saying anything.
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I'm just not part of any conversation, probably not even listening.
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Um when we say multitasking, it means they're reading the paper or they're you know arranging their calendar to pick up their child later that day or whatever.
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That's true.
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And or look at bears trying to be less any cool, but let's be real.
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And look, we're all juggling a lot at the moment, but often where you've got these overloaded organizations with specialists that are being pulled from pillar to post, some of them are actually doing their other project, they're keeping one ear in the conversation and really how effective can you be?
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But what can change, and what we've seen with some uh both both ourselves and also reading a lot more about what's happening out in the wider world, as the capabilities of AI improves and what you can do on your own and the scale of what you can do improves, having that that many people in a team, you probably don't need as many now.
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Um and you know, I'll I'll share some personal anecdotes in in in in a minute of you know how I've found that the the kind of work that I'm able to do now on my own, which normally would have had like three, four, five people.
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It's it's you can do a lot more now if you're using these tools, right?
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Which means that you probably only need four or five you know generalists who are able to span that whole knowledge base for whatever it is that you're doing, but they've got those agents working with them.
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And so now the communication is yes, among those individual agents, but that's you know easier because it's computer to computer.
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You've got four or five people that you're coordinating now.
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And that starts to change things.
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Oh, exactly.
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And you know, where did that number five come from, Stephen?
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Um is it five fingers on a hand?
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Is that it?
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Yeah, I mean totally, totally.
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I know I've done a harsh left turn there.
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But when we think about this number five, it's pretty much how many um, I guess, meaningful communications and connections you can make with a group of people at once.
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So when you start to go out wildly, you can't have that connection anymore.
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So we're starting to see organizations use this.
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Okay, we're more efficient with these tools now.
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We use it as an excuse to let people go.
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But really, the ambition could be there to actually, you know, deliver more value.
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Let's do more strategy work.
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What can we actually do when we unlock our people and and pull them into those smaller team sizes, which isn't really a new concept, right?
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Yeah, well, I do what was coming up from there as you were saying this, you know, and I'm really showing my age here, but I remember when Facebook first came out, like you know, 15, 20 years ago, you know, et cetera.
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And right, and uh, and at the time I remember people saying, How many friends do you have?
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And I would say, I think I've got about three or four, maybe five at a push.
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And they're going, Oh, I've got 163.
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And it's like, what?
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No, you don't.
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They're not your real friends.
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So not your friends.
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Right, but that is a that's a good illustration of I I do have four or five good friends, and and I can't cognitively cope with any more of that.
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Um, so if there's anyone out there who actually wants to be my friend just now, actually, all the places are are filled at this moment in time.
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Um, but it that's just human human nature that there's only so much for most people um of you know what what you can cope with.
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And it's the five kind of people that you've got in your mind.
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Like it was funny when we were getting ready for this.
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I was thinking, oh, you really like those close interpersonal relationships you've got.
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And when you think about forming the chemistry of a team, so you're kind of looking for for those natural handoffs and connections.
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So if you're over overwhelming them with all these 1200 odd interactions, how can you possibly get that nice rhythm and flow and connection?
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So we're going back to, you know, it was a bit of a classic and we whisper the word adja.
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Um team structures where we talk about the concept of a perfect size team being, you know, seven plus or minus two, five or nine.
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And um, I was interested to know uh uh the fun bit of trivia here, and maybe everyone else uh, you know, knew this.
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The the phrase two pizza teams.
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Do you know where that came from, Stephen?
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I saw it was it was Google or Facebook or something like that, but basically um the the amount of food that you needed in order to feed feed a development team.
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Jeffrey Bezos, my friend, he coined this phrase apparently.
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Yes, and an off-site, right?
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Where he's like, oh, you know, we teams need to communicate more.
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And Bezos stood up and said, no, communication is terrible.
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Many wanted to talk about, you know, decentralizing a company where small teams innovate independently.
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So that's where that two pizza phrase came from.
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You just need a team um, you know, small enough that you can feed them with two pizzas.
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So this is a concept that's been around for a little while, but now we can really see how we can actually empower these teams of tools.
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Are they family-sized pizzas?
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I mean, are we we're talking the big ones here, do you think?
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Uh surely, right?
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With thin crust, would you go to thin crust?
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You would you you would think so.
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Yeah, it would have to it'd have to be the big ones because like two small ones, I don't think would I don't think that would do it.
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You're right.
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You'd be pretty you're gonna eat some appetizers there.
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Some garlic bread.
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Two pizzas garley bread.
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We've really gone ridiculous.
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Getting back on track.
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That's what we're seeing as well, is that these smaller teams, because you can do more within these teams now.
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My experience over the last couple of weeks, I mean, we w we've been developing some systems that in the past would have maybe taken, I don't know, three, six months to pull together.
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That we've literally been able to do part-time in a week or two, using kind of you know the latest tools within Claude and Cloud Code and co-working.
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Uh, and that's been quite jarring to be honest.
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There's been times where we've been creating some of that, and I was remembering back 10, 15, 20 years ago when what we were doing there would literally be taking a whole weekend or you know, that's two weeks worth of work and the rest of it.
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And it was a it was a couple of sentences of vibe coding and suddenly it was there.
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I and and that's a bit shocking, to be honest.
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That that's and when you think about the different kinds of skills that used to be used, and that's what this really is about, right?
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You're reducing those external dependencies, you can do more yourself with these tools, you know, cover more of that surface area versus pulling in these separate specialists.
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So that's what it is quite mind-blowing when you actually get inside these tools and see what you can do just personally yourself.
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So it's it's not about kind of replacing the humans, it's actually just being, you know, uh delivering more value.
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We'll use the V-word here.
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Uh with these smaller teams.
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Yes, and quicker as well.
00:13:58.159 --> 00:14:03.679
So you you came up with you're finding some analogies around different ways of structuring these teams.
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Yeah, well that's what I found interesting too, because we're we're still like we're talking about some of these older concepts here.
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You've got the two pizza teams, we've just already talked about how you've got this uh coordination tax across the top, because you've still got many of these smaller teams.
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But we're starting to see these um uh new phrases coming out where we've got these concepts of scouts and strike teams, which I don't know, Stephen, did this made me think a little bit about we've all heard tiger teams before, right?
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Um the the tiger team thing doesn't really work for me, but okay, okay.
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But I don't know.
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But it feels a bit like that, but where you would, you know, someone who came along and go, We needed, we need a tiger team for this, and we'll get our five or six best people, um, you know, pull them out of a team and that other team doesn't matter what they're doing now.
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We've got our guns in this strike team.
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So, well, tiger team.
00:14:48.960 --> 00:14:52.480
Anyway, I've already I've segue, but you know, when you start to see these new phrases.
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Um, when we talk about these scout and strike teams, we're talking about the whole concept of exploration versus execution, you know, good old, you know, investing in some good quality discovery, which some organizations are hesitant to invest in because it's like, hang on, we just we know what the problem is, let's just fix it.
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So you've got this concept of these two operating modes, a scout and a strike team, which is pretty much as the name suggests, you've got a scout, but this time they're running solo and they've got a full AI toolkit, right?
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So they don't have to coordinate with anyone.
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Um, and they're gonna produce, you know, get those initial findings and produce, you know, something viable to work with.
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And then you've got the output coming back into the strike team.
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So what you can do is if you're fully kidding someone out, and then you're your leading person running out and scouting the environment, it's quite a good analogy.
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Um, they can do this within days and months with the right toolkit, right?
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Because they haven't got dependencies.
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They've got, you know, they're unto themselves, they've got a clear field to run.
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So when you've got that nice cheap, that's an interesting word, isn't it?
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Cheap exploration, you're gonna get more experiments and you know, more um volume to actually look at.
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And your cost actually reduces dramatically.
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And like you haven't got a team of people exploring for weeks and months.
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And that's that's what came up for me as you as you were talking through that there.
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You know, because previous language that we've used a lot, um, is it kind of common within the industry, you'd be doing a design spike, right?
00:16:17.840 --> 00:16:19.840
So you you you'd be off to doing a spike.
00:16:20.000 --> 00:16:22.399
But it's usually for a whole team.
00:16:22.559 --> 00:16:25.039
We'll take a sprint, as in you know, a couple of weeks.
00:16:25.279 --> 00:16:32.399
They will go off and do a design sprint for for a couple of weeks and and spike that and do a proof of concept and blah blah.
00:16:32.639 --> 00:16:37.600
But you do have you know a number of people doing it over, you know, probably a couple of weeks.
00:16:37.759 --> 00:16:38.799
Whereas this is different.
00:16:38.960 --> 00:16:45.919
This is somebody who's going off for a couple of days to scout ahead but with a full toolkit, as you were saying.
00:16:46.399 --> 00:16:46.720
Exactly.
00:16:46.799 --> 00:16:54.960
And if you think about the effort that's often involved where you're doing any kind of design or discovery work, you might be interviewing dozens of people, pulling all that doco back.
00:16:55.039 --> 00:17:01.600
But if you've got a fully catered um solo scout out there, the amount that can actually pull in using these tools is quite incredible.
00:17:01.840 --> 00:17:06.559
Again, it doesn't reduce the need to interact with humans, but it just helps you to cut through some of that processing.
00:17:06.720 --> 00:17:15.200
So the idea is you've got your scout running out, bringing it back with their findings, and then handing this over or working with the strike team, Stephen.
00:17:15.359 --> 00:17:16.640
The strike team.
00:17:16.880 --> 00:17:19.440
Um, this is where the number five reappears, right?
00:17:19.519 --> 00:17:29.440
So you've got your five uh generalists, which is, you know, uh when you think about generalists, sometimes we think, oh, hang on, we're not experts, but that's not the idea here, right?
00:17:29.519 --> 00:17:39.039
You've now got this really strong AI fluency and you can scale the outcomes from your scout because they've got those skills that you can actually drive that value on.
00:17:39.680 --> 00:17:45.920
So the whole idea being that you can actually scale your output using these tools and automation.
00:17:46.160 --> 00:17:49.440
So you can reduce the risk of loss.
00:17:49.759 --> 00:17:54.880
Oh, like look, look the face and the arms across what's coming up for you, Stephen, what's coming up?
00:17:56.000 --> 00:17:57.599
So I've got a question for you.
00:17:57.759 --> 00:18:07.839
So are you are you more are you more of a scout or are you more of a strike team person, or are you standing beside the sidelines, you know, coaching the scouts and the strike?
00:18:08.240 --> 00:18:09.039
Where would you like to be?
00:18:09.359 --> 00:18:10.960
Oh, it's an interesting one, isn't it?
00:18:11.119 --> 00:18:12.480
Look, I don't mind a bit of scouting.
00:18:12.559 --> 00:18:18.400
It's nice when you can kind of dig into a problem, like it probably leans into my old analyst um days.
00:18:18.559 --> 00:18:21.200
But you can also see if you're part of that strike team too.
00:18:21.279 --> 00:18:25.920
I'm thinking of the chemistry, like in a band of people, dare I say, where you're all coming together.
00:18:26.480 --> 00:18:28.160
The band of the solar singer, right?
00:18:28.400 --> 00:18:29.119
Okay, yeah.
00:18:29.359 --> 00:18:31.839
Um, but I think it would also, you know, be very exciting.
00:18:32.000 --> 00:18:34.559
Look at me, I'm like, all of the things everywhere all at once.
00:18:34.799 --> 00:18:43.279
It would be also really exciting if you can, you know, work with the team in these structures to see what you can really do in such a short period of time.
00:18:43.839 --> 00:18:46.400
I think for me it's overwhelmingly the scout.
00:18:46.559 --> 00:18:47.519
I would want to be the scout.
00:18:47.839 --> 00:18:48.799
Shock, Stephen.
00:18:49.119 --> 00:18:49.839
You shocked?
00:18:50.160 --> 00:18:50.640
Shocked.
00:18:50.880 --> 00:18:52.319
It's not like you at all.
00:18:52.880 --> 00:19:02.240
That that idea of of just on your own being able to go off and investigate and explore and play with stuff and pull it together and and then come back.
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