Jun 8, 2026 · 28 min · 10 segments
Whether you work best solo or thrive in a team, you know collaboration is complicated — and it turns out AI agents face the same tensions. This episode dives into multi-agent systems, exploring how…
Katie MaloneHost
Do you work alone? Or when I say, how do you work, you think of work that you're doing with a team, maybe a group project, maybe it's a group at work, probably a little bit of both.
And I think you would also say, if I asked you, what's the most effective way for you to work, Well, sometimes I can be really effective alone and sometimes I can be really effective with a team, but also I can be distracted and not very effective and procrastinate and have all kinds of failure modes when I'm working alone.
And I can also have all kinds of pathologies when I'm working with other people, where the challenge of us collaborating with each other is offsetting any of the gains that we might have from having multiple minds working together on a problem.
Well, as it turns out, agents are not that different from you and me and all the other humans out there.
That when they're working alone on certain problems, they have limitations that they start to hit.
And one of the ways to get around those limitations is to... scale your systems out so that you have teams of agents.
But just like teams of humans, those start to hit their own types of failure modes.
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Do you work alone? Or when I say, how do you work, you think of work that you're doing with a team, maybe a group project, maybe it's a group at work, probably a little bit of both.
And I think you would also say, if I asked you, what's the most effective way for you to work, Well, sometimes I can be really effective alone and sometimes I can be really effective with a team, but also I can be distracted and not very effective and procrastinate and have all kinds of failure modes when I'm working alone.
And I can also have all kinds of pathologies when I'm working with other people, where the challenge of us collaborating with each other is offsetting any of the gains that we might have from having multiple minds working together on a problem.
Well, as it turns out, agents are not that different from you and me and all the other humans out there.
That when they're working alone on certain problems, they have limitations that they start to hit.
And one of the ways to get around those limitations is to... scale your systems out so that you have teams of agents.
But just like teams of humans, those start to hit their own types of failure modes.
