Step 6: The Phase Nobody Plans For

📍 Part 6 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

When we started, the model was simple.

Squad builds. Delivery uses.

That division felt right. Clean organizational lines. Clear ownership. A good model.

By Phase 5, it was gone, and it was the best thing that could have happened.

Delivery became builders.

Not because we told them to. Not as a program or initiative.

Organically…as the natural result of everything that came before.

People moved through the anxiety, saw agents make their days better, made the mindset shift from threat to tool to teammate. They started showing up with more than feedback. They showed up with half-built ideas. With sketches of agents they needed. With “I figured out how to make this work”

And with a low-code toolkit they built them. Themselves.

Why this works better than centralized roadmaps.

The people doing the work every day know the friction better than anyone. They know which task is genuinely painful versus just annoying. They know which data lives in the wrong place. They know what “good output” actually looks like for their specific context. They aren’t looking at a PowerPoint slide or a Figma, they are living the experience.

When they build the agent, it fits because it was designed by someone in the workflow it’s automating.

Mona is a great example. She didn’t come from a squad roadmap, she came from a delivery team member who was tired of the back and forth with humans scheduling meetings. She understood the problem completely. She had opinions about exactly what the output should look like. She came to demo days and the engineers said “that’s a great idea but it won’t work” and then she showed them the MVP…working. That day changed our world.

That’s the model. You can’t push it from the top down. It has to grow

The propagation effect.

When everyone in delivery is creating, velocity compounds. One agent spawns an idea for three more. A tool that worked for one person gets adapted for the whole team. The surface area of “problems we’ve automated” expands faster than any squad sitting in an ivory tower could imagine.

There’s not some special team that’s the only one creating. Everyone is. That’s the whole point.

The catch.

There is one. And it’s significant enough to become its own post.

When everyone is building, you get overlap. You get orphaned agents when the person who built them goes on vacation and something breaks. You get agents that don’t log to the dashboard, don’t meet governance requirements, don’t fit the responsible AI framework.

We hit all of this. And more.

Seven agents doing roughly the same thing. Nobody quite sure who owned what. A model update quietly breaking something nobody was watching.

Citizen development at scale without operational infrastructure eventually leads to chaos.

Which is exactly what led us to build the Garage.

Creativity without ops is a mess waiting to happen. Ops without creativity is a very well-governed nothing. You need both.

Next: The mess — and what we built to fix it.

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.

Part 1: Becoming Agent Native.

📍 Post 1 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

We Started in Our Worst Quarter. On Purpose. Q4. Our busiest quarter. The one where we’re all running flat out and nobody has margin for anything extra.

That’s when we decided to pull a small group off delivery and dedicate them to building AI agents.

People thought we were crazy. The timing was bad. But here’s the thing about timing: there’s never a good quarter to change how you work. If you wait for a slow moment, you’re waiting forever.

Three decisions made Phase 1 work. They’re worth naming clearly, because we got all three right (and had gotten them all wrong in an earlier attempt).

Decision 1: Delivery resources. Not new headcount.

The instinct is to hire specialists. Build a separate AI team. Find people with “AI” in their title.

We did the opposite.

We took people already doing the work – people who knew exactly where the friction was, who understood what “a bad Monday looks like” in our workflow – and we gave them dedicated time. Not 10% time. Not a side project. A real squad with a real mandate.

The people who know the pain are the ones motivated to build the cure.

Decision 2: Low-code or nothing.

We made it a mandate: no code-based solutions. No Foundry builds. No MCP servers. No deep engineering.

Partly practical; code means maintenance, and we didn’t have a team to own that. But mostly strategic. The platforms were moving faster than we ever could. Our edge wasn’t engineering. It was application. Low-code kept us in our lane.

Decision 3: Start embarrassingly small.

We had tried the big project approach before. A large-scale agent initiative run as a hobby by people with other jobs to do.

It failed. Not because the vision was wrong. Because nobody owned it, nobody had real time for it, and the scope was too big to make rapid, visible progress.

This time: small agents. Single tasks. The thing you do six times a day that shouldn’t require a human.

Not a meta-agent. Not a platform. Just: let’s automate that one thing that people hate doing.

Out of Phase 1, we had a handful of agents doing small, specific, daily automations. Unimpressive on a slide. Genuinely useful in a workday.

That was enough to move to Phase 2.

The biggest barrier to starting isn’t technology or budget. It’s the belief that you need a huge, perfect project to justify the investment. You don’t.

Next: What happened when those agents met the broader delivery team, and why it didn’t go the way we expected.