Step 5: The Day Anxiety Became Curiosity

📍 Part 5 of 8 · Becoming Agent-Native
An 8-part series on going from delivery team to agent-native organization — lessons earned, not borrowed.
Genesis · Anxiety · Names Matter · Proof of Value · → The Pivot · Co-Creation · The Garage · The Flywheel


There isn’t a single moment. It’s more like a temperature change.

Gradual. And then all at once. Exactly like Hemingway described bankruptcy.

The signal: someone stops asking “is this going to replace me?” and starts asking “what else could they do for me?”

That question – unsolicited, forward-looking, a little excited – is the pivot. And everything after it is different.


What caused it.

Not a single thing. An accumulation.

The email draft that was perfect. The research that came back before they’d finished their coffee. The weekly summary that was just there without anyone asking for it.

When those moments pile up, the mental model flips. The agent stops being a threat and starts being an asset.

And once it’s an asset, a very natural question follows: how do I get a better one?

That question is the whole game. Because it means your delivery team has become an active participant in the quality of their own AI teammates. They want them to improve. They have opinions about how. They’re invested.


The frame that accelerated it.

Our team always has more work than capacity. There are always more customers to serve, more research to run, more value we haven’t gotten to yet.

We are not, and have never been, trying to reduce headcount.

What we’re trying to do is amplify the headcount we have. Get more high-value work. Free people from the repetitive work that agents handle better anyway. Work on the hard stuff. Grow your career.

It’s like the tractor replacing the hand plow. You didn’t lose the farm. The farm got bigger.

When people understood that frame, agents as multipliers, the math became obvious. More impact, same team, better work.

That’s not a threat. That’s a competitive advantage for every person on the team.


What the pivot looked like in practice.

Feedback volume jumped. People who had never commented on an agent suddenly had opinions. Feature requests started flowing. Someone said “could Reese do this if we gave him this additional context?” and “I think George would be even better if he also pulled from this system.”

That’s not tool usage. That’s coaching. And you can’t coach something you’re afraid of.

When you see this shift starting, lean in fast. Turn that spark into a fire. Prioritize the feature requests that come from delivery. Make it visible that their input is landing in the roadmap. Create the fastest possible feedback loop.

The pivot is fragile at first. Feed it.

The moment your team starts coaching their agents instead of tolerating them, the phase change is real.

*Next: What happens when delivery stops requesting agents and starts building them.

Step 4: The Agent Dashboard

📍 Part 4 of 8 · Becoming Agent-Native

An 8-part series on going from delivery team to agent-native organization – lessons earned, not borrowed.
Genesis · Anxiety · Names Matter · → Proof of Value · The Pivot · Co-Creation · The Garage · The Flywheel

Early in Phase 2, before we knew if people would even use these agents, we built a usage dashboard and a small component that every agent had to include – Power Automate, Copilot Studio, M365 Copilot – it was table stakes to onboard.

It felt a bit like overhead at the time.

It became the foundation of everything.

What the dashboard tracked: which agents were being used, how often, by whom, and with what outcome.

Simple. But surprisingly revealing.

Some agents were hits. Usage climbed. Feedback was positive. The team became genuinely dependent on them. These got investment: more features, deeper integration, wider rollout.

Some were mediocre. Usage below expectation but not zero. The dashboard made us ask the right question: is the agent underperforming, or is there an onboarding gap? Is there a better design? Those are different problems. You can’t diagnose without the data.

Some just didn’t work out. And the dashboard gave us permission to retire them. No politics, no ego, just “the numbers say this isn’t earning its place.”


The data showed us insight about people, not just agents.

We saw a clear split emerge: pro users and skeptics.

Some team members were all in. They used agents daily, sending feedback all the time, acting like internal product managers for the agents they’d adopted. Others were lukewarm.

That visibility mattered. It let us find the right internal champions. It let us understand the gap between those two groups. It let us have a business conversation, with real numbers, about what was working.

ROI reporting doesn’t only justify the investment. It shows your team you’re taking this seriously. And them.


But the most important proof never showed up in the dashboard.

It was the moments.

The team member who realized they hadn’t manually changed that case status in weeks. Not because they forgot, but because Theo handled it.

The person who got their Friday afternoon back because George was doing the weekly summary.

The quiet relief of: oh, that’s just handled now.

When those moments accumulate, something shifts. The agent stops being an experiment and starts being infrastructure. The dashboard tracks the what. The moments explain why it matters.


If I were advising someone starting this today, I’d say: Build the measurement layer early, at the business group level, not deep in IT.

Once you have 10 agents and a skeptic asking “what’s the ROI on all this?” you’ll be very glad you have an answer.

“Measure early. The dashboard will make decisions for you that would otherwise become arguments.”

Next: The inflection point, when the team stopped worrying about agents and started wanting more of them.

The AI Revolution is here – and it is the savior

I saw some of the fallout of the interview with Dario Amodie yesterday and one of his key attention grabbers was:

“unemployment will spike to 20% in the near future”

On my team, we’re driving hard and fast into onboarding agents (more on that soon), and in doing so, we’re building earned wisdom, not just hypothetical or philosophical views.

His statement made me pause—not because it’s dramatic, but because it’s directionally right and emotionally wrong. There’s a better thought exercise to pursue:

AI won’t just disrupt jobs – it will accelerate the creation of their replacement.

The uncertainty around AI is due to the rate of change—and how fast that rate is itself accelerating.

If you consider past paradigm shifts, they all disrupted the existing workforce massively, but slowly:

  • The Mainframe
  • The PC
  • The Internet
  • Mobile
  • The wheel, fire, electricity…

These changes all transformed industries. They put people out of work—but not forever. No one today is training to be a switchboard operator. People adapted.

The fear with AI, especially Agentic AI, is that those changes are happening in days or weeks instead of years or decades. But this isn’t like past tech waves where new roles emerged slowly.

The technology that is disrupting everything is part of everything.

This means that AI will help design, build, and onboard the future of work in real time. It will empower people to adapt faster, create faster, and solve problems from every angle—not just the top down.

This is the key difference that gives me great hope from working in real time with AI ; the disruptor is the savior all in one, and it brings the power to help those that are disrupted.

AI is driving disruption centrally within organizations, but we are adapting in a decentralized way – AI is enabling those that are getting on board to create systems, training, opportunities, and resiliency for the new future.

This is the first decentralized industrial revolution. Don’t miss it

Dante Alighieri Quote: “Wisdom is earned, not given.”