TBM 412: Institutionalized Overload (Now With AI)

I guess I’m putting together an AI series of sorts. This is #3.

1. Hope, Context, and Control

2. Seeing Everything, Understanding Nothing (The Context Trap)

3. Institutionalized Overload (Now With AI) « THIS POST

4. Legibility and Legitimacy

5. Before You Fire All Your Glue People Because of AI

6. Simple-player to Mutliplayer: Context Through Collaboration

At the day job, I’m deep in the question of how AI can help teams do more effective work, hence all the thinking below. It has highs and lows these days, with enough inspiring stories to keep me curious and hopeful. If you and your team ever want to chat about this, reach out.

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We’ve gotten so acclimated to organizational overload, endless work in progress, and constant unplanned demands that it has become the norm. It is clearly too much for any person, but people adapt. Their defense mechanisms kick in, and over time that overloaded state just becomes what work feels like.

When I look at how people are using AI, I see the same pattern. People are not really questioning whether this massive amount of cognitive overload is healthy or even appropriate for achieving their goals. They are using the tools to navigate and sustain the overload that already exists. Success becomes processing ever more context, juggling ever more balls, and riding the dopamine hits of perceived navigation and progress. Like Syndrome from The Incredibles, the power feels real while you’re holding it, but it’s built on something external and fragile, and it quietly pulls you deeper into needing it.

New technology rarely breaks the paradigm on its own. It tends to reinforce whatever system it enters, even while claiming to disrupt it. As Tressie McMillan Cottom has argued in different ways, systems that promise to fix what is broken often end up reproducing the same underlying dynamics. You can see this playing out now. Leaders talk about “AI-ing all the things,” but stop short of anything that would actually change how power and decisions flow in the organization. The targets are familiar. A few jabs at middle management. Some efficiency gains. But the core structures remain intact.

Over time, people start to ground their professional identity in this. Being good at your job becomes being good at handling noise, juggling competing inputs, and staying afloat in the chaos. That becomes the work. And the “hit”.

At some point, people go further and begin to argue that this constant “soup” of inputs, interruptions, and competing demands is actually necessary. That it fuels innovation. That it keeps people sharp. That without it, progress would slow. What starts as adaptation turns into justification. The very conditions that make thoughtful work harder get reframed as the reason good work happens at all.

Herbert Simon captured the core constraint: “a wealth of information creates a poverty of attention.” What follows, as Chris Argyris observed, is that people and organizations develop “defensive routines” that protect the status quo rather than question it. And in Byung-Chul Han’s framing, this dynamic becomes internalized, where “the achievement subject exploits itself until it burns out.”

Taken together, the pattern is consistent:
1. overload is not just experienced…
2. it is normalized, defended, and ultimately…
3. sustained by the very people caught inside it.

One of the strange outcomes is that when you operate with calm, determined efficiency and real focus, it can feel uncomfortable. It feels like something should be happening. It feels like something is missing. Overload becomes so normalized and even celebrated that suggesting we do less, or process less, starts to sound almost heretical.

In Han’s framing, the mechanism is that external pressure becomes internalized. People begin to define competence as the ability to handle more, respond faster, and process more context. Feedback loops reward this behavior, and over time it becomes part of identity. Tools like AI then amplify the system by making it easier to cope with overload, which raises expectations further. The result is that people don’t just experience overload, they actively sustain it, and stepping out of it starts to feel uncomfortable or even wrong.

What I am observing is that instead of looking at new technology as a catalyst for being more effective at a deeper level, we assume things are (and will remain) the way they are. Then we use technology to help us cope with a reality that we have largely created. We’ve always done this. We adapt to overload, normalize it, and build systems that sustain it. What’s new is that AI gives us a tool that can amplify the pattern while making it feel like we’re finally taming it.

Work expands to fill the available space, and now context does too. Information, inputs, signals, all of it will grow to fill whatever you allow. In this maximalist phase of AI hype, resisting that expansion is part of the work.