Why Your Best People Are Exhausted
And the infrastructure required to adapt amidst uncertainty.
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Today I’m writing about the infrastructure required to adapt amidst uncertainty.
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On to the show!
Untangled HQ
I’m kicking off a new consulting engagement this month — helping a foundation steward responsible AI implementation across its grantmaking.
The questions they’re asking are the same ones I keep hearing everywhere right now:
How do we make sure our use of AI serves our strategy and our vision for the future — rather than subtly reshaping it?
How do we redesign workflows so they strengthen human judgment while leveraging what AI actually does well?
How do we pattern the behaviors and group dynamics we want, rather than the ones the tool cultivates?
None of these has a checklist answer. They’re questions about systems, power, and how work actually gets done over time — which is the terrain I built STEWARD to walk through.
If you’re sitting with some version of these questions, three ways in:
Join the open cohort — work through the framework alongside peers across sectors.
Reach out for tailored support — for teams who want this adapted to their context.
Come to the next community event, where we’ll dig into S — See the System: learning to see AI not as a tool to deploy, but a set of relationships to steward.
Deep Dive
Why Your Best People Are Exhausted
Remember those nature documentaries where a single animal gets separated from the herd? It’s still strong, still fast, still doing everything right. And it doesn’t matter, because the thing that kept it alive was never its individual fitness. It was the herd. I think about that a lot lately, because almost all the advice going around about how to survive the coming years is advice for the lone animal.
In my work supporting leaders through complexity, I keep meeting the same person. She has personally metabolized everything you’re supposed to have metabolized. She’s traded planning, predicting, and optimizing for sensing, adapting, and learning. She treats uncertainty as a space for discovery rather than a thing to minimize away. She can host real disagreement without needing to resolve it, and she revisits her own mental models the moment they stop fitting. She is, by any reasonable measure, exactly the kind of person built for uncertainty and ongoing change.
And she is exhausted, because she’s doing all of it inside an organization that runs on the opposite settings — high control, low trust, fixed KPIs, evaluation saved for the end — where revisiting a mental model reads as flakiness and the thing she sensed last week dies somewhere between her and the people who’d need to act on it. She has the mindset. But the mindset was never the problem. The problem is that every capacity I just listed is one I’d normally describe as a property of a system, not a person — and she’s being asked to be a mature system all by herself. She’s the lone animal, and the structure around her is built to keep her that way.
I’ve been thinking about her while reading Kevin Kelly’s recent essay, “Our Uncertain Uncertainties.” Kelly is right that we’re heading into a long stretch of compounding uncertainty — what he calls the Age of Ambiguity. He argues that the familiar pattern — disruption, then resolution — won’t hold. Not just for AI, though AI is the most legible piece. Also for geopolitics, civic trust, the reliability of what we see and hear, our own sense of identity in relation to machines that increasingly act like us. We won’t just be uncertain about the world. We’ll be uncertain about our uncertainty. Couldn’t agree more.
What he prescribes, though, is a posture — a mindset. “Cultivate radical adaptability and radical optionality.” “Become at ease holding multiple contradictory possibilities at once.” “Get good at changing your mind.” Each of these is true. And each one describes the inner life of a person navigating ambiguity well. But none of them describes how an organization, or a coalition, or a field actually gets there. They’re a portrait of the destination with no account of the road. And the road has to be built, so let’s dig in.
Relational infrastructure
First, a quick definition, because the phrase can sound abstract. Most systems-change frameworks treat relationships as a means to an end — something you cultivate in order to execute strategy, pass a policy, or move resources. Relational infrastructure inverts that logic. The idea is that the success of a system doesn’t just depend on relationships — it actually evolves through them. The trust built between unlikely allies, the feedback loop between a funder and a grantee who’ve learned to disagree productively, the slow accumulation of shared meaning across organizations that once talked past each other — these aren’t inputs to change. They are the change. (I wrote about this with Michelle Shevin in Tech Policy Press earlier this year, building on the writing of Indy Johar, Donella Meadows, and others)
So why does this matter for Kelly’s advice? Because his entire inner life — holding contradictions, maximizing optionality, changing your mind — depends on a social architecture that lets you do those things without being punished for them. Picture a senior leader in a meeting who says, “I’ve actually changed my mind on this — here’s what I’m seeing now.” Two weeks later, a colleague describes her in passing as “a little inconsistent lately.” That’s what thin relational infrastructure costs. The pivot reads as instability. The optionality reads as a failure to commit. None of those readings are wrong inside a system optimized for certainty. They’re just totally incompatible with the capacity Kelly says we need.
Thick relational infrastructure is what lets a group hold tension without collapsing it. It’s what lets disagreement become productive rather than destabilizing, what lets a system pivot when something shifts without losing the trust that holds it together through the pivot. And you don’t build it overnight. You build it slowly, through small reciprocities, through visible follow-through on commitments, through the patient and frankly unglamorous work of showing people you mean what you say.
It’s also what makes seeing the system possible in the first place.
Kelly’s signs of the Age of Ambiguity are striking: economists who can’t agree on whether productivity rose or fell, court decisions that leave as many questions as answers, employment data spiking in both directions. He argues that “we have to alter our ideas (and measurements) of employment, we have to amend our concepts (and measurements) of the economy, and we have to shift our ideas of what AI even is.” Again, true. But what’s needed to navigate uncertainty isn’t really a sharper definition or a better number. It’s a different practice of looking — done by more people, more often, with different perspectives, together.
That practice has a name: collective sense-making. It’s the process by which a group builds shared understanding by combining what each of them sees. No one sees the whole system. Engineers see one slice, frontline workers another, executives another, communities and regulators others still. Stitched together, those fragments reveal patterns no one could see alone. But the stitching only happens where the relationships are thick enough to hold it. Without trust, the actors fragment into mutual suspicion. Without a shared language for translating across roles and worldviews, they fall into parallel monologues — everyone narrating, no one listening.
So the work is to build structured spaces where this happens on a rhythm rather than by accident: a clear purpose, dialogue norms, a feedback loop that closes visibly so people can see what happened to what they said. And inside those spaces, you watch for leading signals rather than lagging outputs. Are new frames circulating? Are new alliances forming? Are small practices replicating on their own? Is information starting to flow differently, especially from the margins inward? These are the signs a system is shifting. They’re invisible to a dashboard. But they’re perfectly legible to a group that’s been practicing the art of seeing together.
Judgment infrastructure
Then there’s the moment of the call. The point at which someone — usually under time pressure, usually with incomplete information — has to actually decide.
I wrote recently about judgment infrastructure: the workflow-level design that makes scrutiny structurally inevitable rather than individually heroic. The argument went like this. The dominant story locates judgment in individuals, which conveniently lets the organization that designed the workflow, set the throughput target, and chose the AI tool recede from view. But judgment is the thing codification leaves behind. It can only be volunteered, never conscripted. It’s triggered by context, not retrieved from storage. Which means it isn’t a private capacity you can hire for, train into people, or hold them accountable for having. It’s an emergent property of the conditions you build around the decision.
This is exactly where Kelly’s ethic of “changing your mind” makes its hardest contact with reality. In most organizations, the person who flags a problem has to explain herself. The person who ratifies the dominant call doesn’t have to explain anything. Right — deference is the default; dissent is the exception that has to be justified. Now add an AI that hides its uncertainty inside a confident-sounding output. Add a throughput target that punishes deliberation. And “change your mind” quietly becomes a thing that costs you something. So, predictably, people stop doing it. What could possibly go wrong?
Well, you can fix this — but only structurally. By making active ratification part of the workflow, so waving something through is itself a recorded act, not the absence of one. By flipping the burden of justification onto the person who approved rather than the person who questioned. By keeping the feedback loop open long enough that decisions get reviewed for the quality of their reasoning, not just the luck of their outcome. By decoupling the signal from the messenger, so a junior reviewer’s flag doesn’t have to survive the office politics of being junior. Notice what none of these require: they don’t ask the person with the least power in the room to be braver than she was yesterday. That’s the actual test. If a fix depends on someone’s courage on a bad day, it isn’t infrastructure — it’s wishful thinking dressed up as design.
And the logic travels. The claims reviewer with an AI flag in front of her, the product manager reviewing an AI-drafted strategy memo, the program officer reviewing an AI-summarized grant proposal, the board member reviewing an algorithmically-generated risk report — they’re all the same person I keep meeting, in a different chair. Wherever someone is asked to exercise judgment under conditions that quietly punish judgment, the answer is never “be more courageous.” It’s “change the conditions.”
So here’s the thing. Adaptability you can feel but never act on isn’t really adaptability — it’s just a very calm way of staying stuck. What actually moves things is smaller and slower than a posture. It’s one relationship with someone who sees a part of your system you can’t, kept up outside the gravity of any single project. It’s one recurring room where the people who see different pieces make sense of what’s shifting before it shows up in the numbers. It’s one signal worth watching that no dashboard tracks. And it’s one workflow where compliance is doing the work judgment should be doing — where you flip a single default, or rotate a single reviewer, so the structure carries what you’ve been asking a person to carry alone.
We don’t get to choose whether we live in an age of ambiguity. We only get to choose what we build to hold each other inside it. The lone animal was never going to make it. It was always the herd.
Work With Me
Here are 3 ways I can help:
Advising: I can help you navigate uncertainty, make sense of AI, and steward change in your system.
Organizational Training: Everything you and your team need to cut through the tech-hype and implement strategies that catalyze true systems change. (For either Stewarding AI or Systems Change for Tech & Society Leaders)
1:1 Leadership Coaching: I can help you facilitate change — in yourself, your organization, and the system you work within.